Publications plus anciennes

@article{rochoy_epidemiology_2019,
	title = {Epidemiology of neurocognitive disorders in {France}},
	volume = {17},
	issn = {2115-7863},
	doi = {10.1684/pnv.2018.0778},
	abstract = {Neurocognitive disorders are common: every year, any physician or health professional comes into contact with patients or relatives with early symptoms of dementia. Nevertheless, their epidemiology remains difficult to estimate, due to real differences in risk factors within a country or region (average age, genetics, level of education, socio-economic level, etc.), differences in data collection, in the interpretation of these data with regard to scientific findings and changes in diagnostic criteria. In this review, we present a state of knowledge of the epidemiology of dementia in France. Epidemiological data on neurocognitive disorders in France come mainly from 3 sources: two prospective cohorts (PAQUID and 3C) and large databases (SNIIRAM, RSI data, PMSI). Neurocognitive disorders are estimated to directly affect more than 1.2 million people in France and about 2 out of 3 cases are attributed to Alzheimer's disease. The prevalence rate is estimated at about 40/1,000 people after 60 years of age and gradually increases to 180/1,000 after 75 years of age, reaching almost one in two people after 90 years of age. The incidence rate is estimated at between 13 and 19/1,000 person-years, and seems to decrease slightly over the decades. The PAQUID and 3C cohorts are coming to an end; despite the development of large databases (SNIIRAM, PMSI, etc.), it seems necessary to continue to set up new prospective cohorts in the general population to monitor the epidemiology of neurocognitive disorders in France.},
	language = {eng},
	number = {1},
	journal = {Geriatrie Et Psychologie Neuropsychiatrie Du Vieillissement},
	author = {Rochoy, Michaël and Chazard, Emmanuel and Bordet, Régis},
	month = mar,
	year = {2019},
	pmid = {30907374},
	keywords = {France, cohort studies, dementia, epidemiology, incidence, prevalence},
	pages = {99--105},
}

Neurocognitive disorders are common: every year, any physician or health professional comes into contact with patients or relatives with early symptoms of dementia. Nevertheless, their epidemiology remains difficult to estimate, due to real differences in risk factors within a country or region (average age, genetics, level of education, socio-economic level, etc.), differences in data collection, in the interpretation of these data with regard to scientific findings and changes in diagnostic criteria. In this review, we present a state of knowledge of the epidemiology of dementia in France. Epidemiological data on neurocognitive disorders in France come mainly from 3 sources: two prospective cohorts (PAQUID and 3C) and large databases (SNIIRAM, RSI data, PMSI). Neurocognitive disorders are estimated to directly affect more than 1.2 million people in France and about 2 out of 3 cases are attributed to Alzheimer's disease. The prevalence rate is estimated at about 40/1,000 people after 60 years of age and gradually increases to 180/1,000 after 75 years of age, reaching almost one in two people after 90 years of age. The incidence rate is estimated at between 13 and 19/1,000 person-years, and seems to decrease slightly over the decades. The PAQUID and 3C cohorts are coming to an end; despite the development of large databases (SNIIRAM, PMSI, etc.), it seems necessary to continue to set up new prospective cohorts in the general population to monitor the epidemiology of neurocognitive disorders in France.

@article{bray_augmentation_2019,
	title = {Augmentation de l’incidence des cholécystectomies associées à une pathologie biliaire en {France} : analyse de 807 307 cholécystectomies sur 7 ans},
	issn = {1878-786X},
	shorttitle = {Augmentation de l’incidence des cholécystectomies associées à une pathologie biliaire en {France}},
	url = {http://www.sciencedirect.com/science/article/pii/S1878786X1830411X},
	doi = {10.1016/j.jchirv.2017.12.008},
	abstract = {Résumé
Introduction
Les calculs biliaires sont un des motifs abdominaux d’admission hospitalière les plus fréquents. Le but de cette étude était d’analyser les tendances et les suites des cholécystectomies pour pathologie biliaire, en France, de 2008 à 2014.
Patients et méthodes
Nous avons mené une étude rétrospective de cohorte, en utilisant des données extraites de la base de données nationale hospitalière Française (PMSI). Nous avons inclus tous les patients ayant bénéficié d’une cholécystectomie pour pathologie biliaire, de janvier 2008 à décembre 2014. Les caractéristiques démographiques, la voie d’abord, la durée de séjour, les complications et la mortalité intrahospitalière ont été analysées.
Résultats
Sur la période étudiée, 807 307 cholécystectomies ont été réalisées en France, avec une augmentation du taux national d’incidence de 167,5 (IC95 \% [166,5 ; 168,5]) à 182,6 (IC95 \% [181,6 ; 183,6]) pour 100 000 habitants. Les femmes représentaient 66,5 \% des interventions (p{\textless}0,001). La moyenne d’âge était plus basse pour les hommes que pour les femmes : 52,1 contre 60,2 ans (p{\textless}0,001). Le taux de cœlioscopies a augmenté significativement de 90 \% en 2008 à 94 \% en 2014 (p{\textless}0,001). La durée moyenne de séjour a significativement diminué, de 6,5 en 2008 à 4,7jours en 2014 (p{\textless}0,001). Les complications les plus fréquentes étaient intra-abdominales (23,1 \% pour les coelioscopies (IC95 \% [22,7 ; 23,5]), la mortalité intra-hospitalière a significativement baissé, de 0,45 \% en 2008 à 0,38 \% en 2014 (p{\textless}0,005).
Conclusion
Nos résultats ont montré une augmentation significative du taux national d’incidence des cholécystectomies pour pathologie biliaire, de 2008 à 2014.
Summary
Purpose
Gallstones are one of the most common abdominal reasons for admission to hospital. The aim of this study was to analyze trends and outcomes in patients undergoing cholecystectomy with gallbladder related disease in France from 2008 to 2014.
Patients and methods
We carried out a population-based, retrospective cohort study using data extracted from the French nationwide hospital discharge database (PMSI). We included all patients having a cholecystectomy related to gallbladder disease from January 2008 to December 2014. Patients’ demographics, primary diagnosis, procedure type, length of stay (LOS), admission in an intensive care unit, discharge disposition, complications, and in-hospital mortality were analyzed.
Results
Overall, 807,307 cholecystectomies were performed in France over the study period, with an increase in the national incidence rate from 167.5 (95\%CI [166.5; 168.5]) to 182.6 (95\%CI [181.6; 183.6]) per 100,000 inhabitants. Females accounted for 66.5\% of procedures (P{\textless}.001). The mean age was lower for females than for males: 52.1 versus 60.2 (P{\textless}.001). The ratio of laparoscopic cholecystectomy significantly increased from 90\% in 2008 to 94\% in 2014 (P{\textless}.001). Average inpatient LOS decreased significantly from 6.5 days in 2008 to 4.7 days in 2014 (P{\textless}.001). Most common complication type was intra-abdominal (23.1\% for laparoscopic procedure (95\%CI [22.7; 23.5]), and in-hospital mortality significantly decreased over time from 0.45\% in 2008 to 0.38\% in 2014 (P{\textless}.005).
Conclusion
Our results showed that the national incidence rate of cholecystectomy related to gallbladder disease increased from 2008 to 2014.},
	urldate = {2019-01-14},
	journal = {Journal de Chirurgie Viscérale},
	author = {Bray, F. and Balcaen, T. and Baro, E. and Gandon, A. and Ficheur, G. and Chazard, E.},
	month = jan,
	year = {2019},
	keywords = {Cholecystectomy, Cholécystectomies, Coelioscopie, Epidemiology, Laparoscopic cholecystectomy, Laparotomie, Nationwide database, Open cholecystectomy, PMSI, Épidémiologie},
}

Résumé Introduction Les calculs biliaires sont un des motifs abdominaux d’admission hospitalière les plus fréquents. Le but de cette étude était d’analyser les tendances et les suites des cholécystectomies pour pathologie biliaire, en France, de 2008 à 2014. Patients et méthodes Nous avons mené une étude rétrospective de cohorte, en utilisant des données extraites de la base de données nationale hospitalière Française (PMSI). Nous avons inclus tous les patients ayant bénéficié d’une cholécystectomie pour pathologie biliaire, de janvier 2008 à décembre 2014. Les caractéristiques démographiques, la voie d’abord, la durée de séjour, les complications et la mortalité intrahospitalière ont été analysées. Résultats Sur la période étudiée, 807 307 cholécystectomies ont été réalisées en France, avec une augmentation du taux national d’incidence de 167,5 (IC95 % [166,5 ; 168,5]) à 182,6 (IC95 % [181,6 ; 183,6]) pour 100 000 habitants. Les femmes représentaient 66,5 % des interventions (p\textless0,001). La moyenne d’âge était plus basse pour les hommes que pour les femmes : 52,1 contre 60,2 ans (p\textless0,001). Le taux de cœlioscopies a augmenté significativement de 90 % en 2008 à 94 % en 2014 (p\textless0,001). La durée moyenne de séjour a significativement diminué, de 6,5 en 2008 à 4,7jours en 2014 (p\textless0,001). Les complications les plus fréquentes étaient intra-abdominales (23,1 % pour les coelioscopies (IC95 % [22,7 ; 23,5]), la mortalité intra-hospitalière a significativement baissé, de 0,45 % en 2008 à 0,38 % en 2014 (p\textless0,005). Conclusion Nos résultats ont montré une augmentation significative du taux national d’incidence des cholécystectomies pour pathologie biliaire, de 2008 à 2014. Summary Purpose Gallstones are one of the most common abdominal reasons for admission to hospital. The aim of this study was to analyze trends and outcomes in patients undergoing cholecystectomy with gallbladder related disease in France from 2008 to 2014. Patients and methods We carried out a population-based, retrospective cohort study using data extracted from the French nationwide hospital discharge database (PMSI). We included all patients having a cholecystectomy related to gallbladder disease from January 2008 to December 2014. Patients’ demographics, primary diagnosis, procedure type, length of stay (LOS), admission in an intensive care unit, discharge disposition, complications, and in-hospital mortality were analyzed. Results Overall, 807,307 cholecystectomies were performed in France over the study period, with an increase in the national incidence rate from 167.5 (95%CI [166.5; 168.5]) to 182.6 (95%CI [181.6; 183.6]) per 100,000 inhabitants. Females accounted for 66.5% of procedures (P\textless.001). The mean age was lower for females than for males: 52.1 versus 60.2 (P\textless.001). The ratio of laparoscopic cholecystectomy significantly increased from 90% in 2008 to 94% in 2014 (P\textless.001). Average inpatient LOS decreased significantly from 6.5 days in 2008 to 4.7 days in 2014 (P\textless.001). Most common complication type was intra-abdominal (23.1% for laparoscopic procedure (95%CI [22.7; 23.5]), and in-hospital mortality significantly decreased over time from 0.45% in 2008 to 0.38% in 2014 (P\textless.005). Conclusion Our results showed that the national incidence rate of cholecystectomy related to gallbladder disease increased from 2008 to 2014.

@article{robert_community-acquired_2019,
	title = {Community-{Acquired} {Acute} {Kidney} {Injury} {Induced} {By} {Drugs} {In} {Older} {Patients}: {A} {Multifactorial} {Event}},
	volume = {Volume 14},
	issn = {1178-1998},
	shorttitle = {Community-{Acquired} {Acute} {Kidney} {Injury} {Induced} {By} {Drugs} {In} {Older} {Patients}},
	url = {https://www.dovepress.com/community-acquired-acute-kidney-injury-induced-by-drugs-in-older-patie-peer-reviewed-article-CIA},
	doi = {10.2147/CIA.S217567},
	abstract = {Purpose: Community-acquired acute kidney injury (CA-AKI) is a frequent and severe adverse drug reaction (ADR) among older patients. The combination of drugs and other CA-AKI risk factors was barely evaluated. The objectives of our study were to both accurately identify CA-AKI induced by drugs in older patients, and to describe their combination with other risk factors. Patients and methods: We conducted a retrospective, single-center study in a general hospital over a two-year period. An automated detection identified CA-AKI according to KDIGO criteria, amongst 4,767 eligible inpatient stays among patients aged 75 years or older. Two independent experts reviewed all CA-AKI events to adjudicate drug involvement (Naranjo scale), identify inappropriate prescriptions (STOPP criteria), evaluate avoidability (Hallas criteria) and identify combined risk factors.
Results: An expert review confirmed 713 CA-AKI (15.0\% of inpatient stays) and determined that 419 (58.8\%) CA-AKI were induced by drugs. A multifactorial cause (i.e., at least one drug with a precipitating factor) was found in 63.2\% of drug-induced CA-AKI. Most of the drug-induced events were avoidable (66.8\%), mainly in relation to a multifactorial cause.
Conclusion: Drug-induced CA-AKI were frequent, multifactorial events in hospitalized older patients and their prevention should focus on combinations with precipitating factors.},
	language = {en},
	urldate = {2019-12-05},
	journal = {Clinical Interventions in Aging},
	author = {Robert, Laurine and Ficheur, Grégoire and Gautier, Sophie and Servais, Alexandre and Luyckx, Michel and Soula, Julien and Decaudin, Bertrand and Glowacki, François and Puisieux, François and Chazard, Emmanuel and Beuscart, Jean-Baptiste},
	month = dec,
	year = {2019},
	pages = {2105--2113},
}

Purpose: Community-acquired acute kidney injury (CA-AKI) is a frequent and severe adverse drug reaction (ADR) among older patients. The combination of drugs and other CA-AKI risk factors was barely evaluated. The objectives of our study were to both accurately identify CA-AKI induced by drugs in older patients, and to describe their combination with other risk factors. Patients and methods: We conducted a retrospective, single-center study in a general hospital over a two-year period. An automated detection identified CA-AKI according to KDIGO criteria, amongst 4,767 eligible inpatient stays among patients aged 75 years or older. Two independent experts reviewed all CA-AKI events to adjudicate drug involvement (Naranjo scale), identify inappropriate prescriptions (STOPP criteria), evaluate avoidability (Hallas criteria) and identify combined risk factors. Results: An expert review confirmed 713 CA-AKI (15.0% of inpatient stays) and determined that 419 (58.8%) CA-AKI were induced by drugs. A multifactorial cause (i.e., at least one drug with a precipitating factor) was found in 63.2% of drug-induced CA-AKI. Most of the drug-induced events were avoidable (66.8%), mainly in relation to a multifactorial cause. Conclusion: Drug-induced CA-AKI were frequent, multifactorial events in hospitalized older patients and their prevention should focus on combinations with precipitating factors.

@article{rochoy_factors_2019,
	title = {Factors associated with the onset of {Alzheimer}'s disease: {Data} mining in the {French} nationwide discharge summary database between 2008 and 2014},
	volume = {14},
	issn = {1932-6203},
	shorttitle = {Factors associated with the onset of {Alzheimer}'s disease},
	doi = {10.1371/journal.pone.0220174},
	abstract = {INTRODUCTION: Identifying modifiable risk factors for Alzheimer's disease (AD) is critical for research. Data mining may be a useful tool for finding new AD associated factors.
METHODS: We included all patients over 49 years of age, hospitalized in France in 2008 (without dementia) and in 2014. Dependent variable was AD or AD dementia diagnosis in 2014. We recoded the diagnoses of hospital stays (in ICD-10) into 137 explanatory variables.To avoid overweighting the "age" variable, we divided the population into 7 sub-populations of 5 years.
RESULTS: We analyzed 1,390,307 patients in the PMSI in 2008 and 2014: 55,997 patients had coding for AD or AD dementia in 2014 (4.04\%). We associated Alzheimer disease in 2014 with about 20 variables including male sex, stroke, diabetes mellitus, mental retardation, bipolar disorder, intoxication, Parkinson disease, depression, anxiety disorders, alcohol, undernutrition, fall and 3 less explored variables: intracranial hypertension (odd radio [95\% confidence interval]: 1.16 [1.12-1.20] in 70-80 years group), psychotic disorder (OR: 1.09 [1.07-1.11] in 70-75 years group) and epilepsy (OR: 1.06 [1.05-1.07] after 70 years).
DISCUSSION: We analyzed 137 variables in the PMSI identified some well-known risk factors for AD, and highlighted a possible association with intracranial hypertension, which merits further investigation. Better knowledge of associations could lead to better targeting (identifying) at-risk patients, and better prevention of AD, in order to reduce its impact.},
	language = {eng},
	number = {7},
	journal = {PloS One},
	author = {Rochoy, Michaël and Bordet, Régis and Gautier, Sophie and Chazard, Emmanuel},
	year = {2019},
	pmid = {31344088},
	pmcid = {PMC6657866},
	pages = {e0220174},
}

INTRODUCTION: Identifying modifiable risk factors for Alzheimer's disease (AD) is critical for research. Data mining may be a useful tool for finding new AD associated factors. METHODS: We included all patients over 49 years of age, hospitalized in France in 2008 (without dementia) and in 2014. Dependent variable was AD or AD dementia diagnosis in 2014. We recoded the diagnoses of hospital stays (in ICD-10) into 137 explanatory variables.To avoid overweighting the "age" variable, we divided the population into 7 sub-populations of 5 years. RESULTS: We analyzed 1,390,307 patients in the PMSI in 2008 and 2014: 55,997 patients had coding for AD or AD dementia in 2014 (4.04%). We associated Alzheimer disease in 2014 with about 20 variables including male sex, stroke, diabetes mellitus, mental retardation, bipolar disorder, intoxication, Parkinson disease, depression, anxiety disorders, alcohol, undernutrition, fall and 3 less explored variables: intracranial hypertension (odd radio [95% confidence interval]: 1.16 [1.12-1.20] in 70-80 years group), psychotic disorder (OR: 1.09 [1.07-1.11] in 70-75 years group) and epilepsy (OR: 1.06 [1.05-1.07] after 70 years). DISCUSSION: We analyzed 137 variables in the PMSI identified some well-known risk factors for AD, and highlighted a possible association with intracranial hypertension, which merits further investigation. Better knowledge of associations could lead to better targeting (identifying) at-risk patients, and better prevention of AD, in order to reduce its impact.

@article{rochoy_shift_2019,
	title = {Shift in {Hospitalizations} for {Alzheimer}'s {Disease} to {Related} {Dementias} in {France} between 2007 and 2017},
	volume = {6},
	issn = {2426-0266},
	doi = {10.14283/jpad.2019.5},
	abstract = {INTRODUCTION: Alzheimer's disease (AD) is the first cause of dementia. Diagnostic criteria have evolved: proposals to revise the NINCDS-ADRDA criteria were published in 2007. Our aim was to analyze the evolution in the coding of AD in the French nationwide exhaustive hospital discharge database (PMSI) between 2007 and 2017.
METHODS: We analyzed evolution of International Classification of Diseases and Related Health Problems, 10th edition (ICD-10) coding for AD and AD dementia in the PMSI database from 2008 to 2017 (285,748,938 inpatient stays).
RESULTS: We observed a 44\% decrease in the number of inpatient stays with a principal diagnosis of AD or AD dementia from 2007 (46,313 inpatient stays) to 2017 (25,856 inpatient stays) in France. Over the same period, we observed a 49\% increase in the number of inpatient stays with a principal diagnosis of related dementias (other organic mental disorders or other degenerative disorders). Overall, the number of inpatient stays for dementia remained stable despite the increase in the total number of inpatient stays: 95,377 in 2007 (0.409\% of inpatient stays) and 99,190 in 2017 (0.344\%).
CONCLUSION: We therefore note a shift from AD and AD dementia to other dementia diagnoses since 2007. This study suggests a more accurate use of AD related ICD-10 codes since the revised criteria in 2007.},
	language = {eng},
	number = {2},
	journal = {The Journal of Prevention of Alzheimer's Disease},
	author = {Rochoy, M. and Chazard, E. and Gautier, S. and Bordet, R.},
	year = {2019},
	pmid = {30756117},
	keywords = {Alzheimer disease, Data reuse, PMSI, big data, vascular dementia},
	pages = {108--111},
}

INTRODUCTION: Alzheimer's disease (AD) is the first cause of dementia. Diagnostic criteria have evolved: proposals to revise the NINCDS-ADRDA criteria were published in 2007. Our aim was to analyze the evolution in the coding of AD in the French nationwide exhaustive hospital discharge database (PMSI) between 2007 and 2017. METHODS: We analyzed evolution of International Classification of Diseases and Related Health Problems, 10th edition (ICD-10) coding for AD and AD dementia in the PMSI database from 2008 to 2017 (285,748,938 inpatient stays). RESULTS: We observed a 44% decrease in the number of inpatient stays with a principal diagnosis of AD or AD dementia from 2007 (46,313 inpatient stays) to 2017 (25,856 inpatient stays) in France. Over the same period, we observed a 49% increase in the number of inpatient stays with a principal diagnosis of related dementias (other organic mental disorders or other degenerative disorders). Overall, the number of inpatient stays for dementia remained stable despite the increase in the total number of inpatient stays: 95,377 in 2007 (0.409% of inpatient stays) and 99,190 in 2017 (0.344%). CONCLUSION: We therefore note a shift from AD and AD dementia to other dementia diagnoses since 2007. This study suggests a more accurate use of AD related ICD-10 codes since the revised criteria in 2007.

@article{rochoy_factors_2019-1,
	title = {Factors {Associated} with {Alzheimer}'s {Disease}: {An} {Overview} of {Reviews}},
	volume = {6},
	issn = {2426-0266},
	shorttitle = {Factors {Associated} with {Alzheimer}'s {Disease}},
	doi = {10.14283/jpad.2019.7},
	abstract = {Alzheimer's disease (AD) is a frequent pathology, with a poor prognosis, for which no curative treatment is available in 2018. AD prevention is an important issue, and is an important research topic. In this manuscript, we have synthesized the literature reviews and meta-analyses relating to modifiable risk factors associated with AD. Smoking, diabetes, high blood pressure, obesity, hypercholesterolemia, physical inactivity, depression, head trauma, heart failure, bleeding and ischemic strokes, sleep apnea syndrome appeared to be associated with an increased risk of AD. In addition to these well-known associations, we highlight here the existence of associated factors less described: hyperhomocysteinemia, hearing loss, essential tremor, occupational exposure to magnetic fields. On the contrary, some oral antidiabetic drugs, education and intellectual activity, a Mediterranean-type diet or using Healthy Diet Indicator, consumption of unsaturated fatty acids seemed to have a protective effect. Better knowledge of risk factors for AD allows for better identification of patients at risk. This may contribute to the emergence of prevention policies to delay or prevent the onset of AD.},
	language = {eng},
	number = {2},
	journal = {The Journal of Prevention of Alzheimer's Disease},
	author = {Rochoy, M. and Rivas, V. and Chazard, E. and Decarpentry, E. and Saudemont, G. and Hazard, P.-A. and Puisieux, F. and Gautier, S. and Bordet, R.},
	year = {2019},
	pmid = {30756119},
	keywords = {Alzheimer’s disease, early intervention, prevention, risk factors},
	pages = {121--134},
}

Alzheimer's disease (AD) is a frequent pathology, with a poor prognosis, for which no curative treatment is available in 2018. AD prevention is an important issue, and is an important research topic. In this manuscript, we have synthesized the literature reviews and meta-analyses relating to modifiable risk factors associated with AD. Smoking, diabetes, high blood pressure, obesity, hypercholesterolemia, physical inactivity, depression, head trauma, heart failure, bleeding and ischemic strokes, sleep apnea syndrome appeared to be associated with an increased risk of AD. In addition to these well-known associations, we highlight here the existence of associated factors less described: hyperhomocysteinemia, hearing loss, essential tremor, occupational exposure to magnetic fields. On the contrary, some oral antidiabetic drugs, education and intellectual activity, a Mediterranean-type diet or using Healthy Diet Indicator, consumption of unsaturated fatty acids seemed to have a protective effect. Better knowledge of risk factors for AD allows for better identification of patients at risk. This may contribute to the emergence of prevention policies to delay or prevent the onset of AD.

@article{rochoy_evolution_2018,
	title = {Evolution of {Dementia} {Related} to the {Use} of {Alcohol} in the {French} {Nationwide} {Discharge} {Summary} {Database} {Between} 2007 and 2017},
	issn = {1938-2731},
	doi = {10.1177/1533317518822043},
	abstract = {BACKGROUND:: The French nationwide exhaustive hospital discharge database (PMSI) is used for activity-based payment of hospital services. We hypothesized that the release of articles about alcohol and dementia could influence the identification of these diagnoses in PMSI.
METHODS:: We analyzed temporal evolution of coding for dementia and other persistent or late-onset cognitive impairment (OPLOCI) due to alcohol and other psychoactive substances in the PMSI database from 2007 to 2017 (285 748 938 inpatient stays). These codings use the International Classification of Diseases, 10th revision (ICD-10).
RESULTS:: The number of inpatient stays with dementia and OPLOCI due to alcohol increased from 34 to 1704 from 2007 to 2017. While the number of diagnosed dementias remained stable at around 400 from 2013, the number of OPLOCIs increased 10-fold from 2013 to 2017. This increase was not found with dementia or OPLOCI due to other psychoactive substances than alcohol.
CONCLUSION:: Notoriety of a diagnosis in the literature seems to have an impact on the coding.},
	language = {eng},
	journal = {American Journal of Alzheimer's Disease and Other Dementias},
	author = {Rochoy, Michaël and Gautier, Sophie and Béné, Johana and Bordet, Régis and Chazard, Emmanuel},
	month = dec,
	year = {2018},
	pmid = {30595024},
	keywords = {alcoholism, clinical coding, data reuse, database, dementia},
	pages = {1533317518822043},
}

BACKGROUND:: The French nationwide exhaustive hospital discharge database (PMSI) is used for activity-based payment of hospital services. We hypothesized that the release of articles about alcohol and dementia could influence the identification of these diagnoses in PMSI. METHODS:: We analyzed temporal evolution of coding for dementia and other persistent or late-onset cognitive impairment (OPLOCI) due to alcohol and other psychoactive substances in the PMSI database from 2007 to 2017 (285 748 938 inpatient stays). These codings use the International Classification of Diseases, 10th revision (ICD-10). RESULTS:: The number of inpatient stays with dementia and OPLOCI due to alcohol increased from 34 to 1704 from 2007 to 2017. While the number of diagnosed dementias remained stable at around 400 from 2013, the number of OPLOCIs increased 10-fold from 2013 to 2017. This increase was not found with dementia or OPLOCI due to other psychoactive substances than alcohol. CONCLUSION:: Notoriety of a diagnosis in the literature seems to have an impact on the coding.

@article{poirier_real_2018,
	title = {Real {Time} {Influenza} {Monitoring} {Using} {Hospital} {Big} {Data} in {Combination} with {Machine} {Learning} {Methods}: {Comparison} {Study}},
	volume = {4},
	issn = {2369-2960},
	shorttitle = {Real {Time} {Influenza} {Monitoring} {Using} {Hospital} {Big} {Data} in {Combination} with {Machine} {Learning} {Methods}},
	doi = {10.2196/11361},
	abstract = {BACKGROUND: Traditional surveillance systems produce estimates of influenza-like illness (ILI) incidence rates, but with 1- to 3-week delay. Accurate real-time monitoring systems for influenza outbreaks could be useful for making public health decisions. Several studies have investigated the possibility of using internet users' activity data and different statistical models to predict influenza epidemics in near real time. However, very few studies have investigated hospital big data.
OBJECTIVE: Here, we compared internet and electronic health records (EHRs) data and different statistical models to identify the best approach (data type and statistical model) for ILI estimates in real time.
METHODS: We used Google data for internet data and the clinical data warehouse eHOP, which included all EHRs from Rennes University Hospital (France), for hospital data. We compared 3 statistical models-random forest, elastic net, and support vector machine (SVM).
RESULTS: For national ILI incidence rate, the best correlation was 0.98 and the mean squared error (MSE) was 866 obtained with hospital data and the SVM model. For the Brittany region, the best correlation was 0.923 and MSE was 2364 obtained with hospital data and the SVM model.
CONCLUSIONS: We found that EHR data together with historical epidemiological information (French Sentinelles network) allowed for accurately predicting ILI incidence rates for the entire France as well as for the Brittany region and outperformed the internet data whatever was the statistical model used. Moreover, the performance of the two statistical models, elastic net and SVM, was comparable.},
	language = {eng},
	number = {4},
	journal = {JMIR public health and surveillance},
	author = {Poirier, Canelle and Lavenu, Audrey and Bertaud, Valérie and Campillo-Gimenez, Boris and Chazard, Emmanuel and Cuggia, Marc and Bouzillé, Guillaume},
	month = dec,
	year = {2018},
	pmid = {30578212},
	keywords = {Sentinelles network, big data, electronic health records, influenza, infodemiology, infoveillance, machine learning},
	pages = {e11361},
}

BACKGROUND: Traditional surveillance systems produce estimates of influenza-like illness (ILI) incidence rates, but with 1- to 3-week delay. Accurate real-time monitoring systems for influenza outbreaks could be useful for making public health decisions. Several studies have investigated the possibility of using internet users' activity data and different statistical models to predict influenza epidemics in near real time. However, very few studies have investigated hospital big data. OBJECTIVE: Here, we compared internet and electronic health records (EHRs) data and different statistical models to identify the best approach (data type and statistical model) for ILI estimates in real time. METHODS: We used Google data for internet data and the clinical data warehouse eHOP, which included all EHRs from Rennes University Hospital (France), for hospital data. We compared 3 statistical models-random forest, elastic net, and support vector machine (SVM). RESULTS: For national ILI incidence rate, the best correlation was 0.98 and the mean squared error (MSE) was 866 obtained with hospital data and the SVM model. For the Brittany region, the best correlation was 0.923 and MSE was 2364 obtained with hospital data and the SVM model. CONCLUSIONS: We found that EHR data together with historical epidemiological information (French Sentinelles network) allowed for accurately predicting ILI incidence rates for the entire France as well as for the Brittany region and outperformed the internet data whatever was the statistical model used. Moreover, the performance of the two statistical models, elastic net and SVM, was comparable.

@article{bray_increased_2018,
	title = {Increased incidence of cholecystectomy related to gallbladder disease in {France}: {Analysis} of 807,307 cholecystectomy procedures over a period of seven years},
	issn = {1878-7886},
	shorttitle = {Increased incidence of cholecystectomy related to gallbladder disease in {France}},
	doi = {10.1016/j.jviscsurg.2018.12.003},
	abstract = {PURPOSE: Gallstones are one of the most common abdominal reasons for admission to hospital. The aim of this study was to analyze trends and outcomes in patients undergoing cholecystectomy with gallbladder related disease in France from 2008 to 2014.
PATIENTS AND METHODS: We carried out a population-based, retrospective cohort study using data extracted from the French nationwide hospital discharge database (PMSI). We included all patients having a cholecystectomy related to gallbladder disease from January 2008 to December 2014. Patients' demographics, primary diagnosis, procedure type, length of stay (LOS), admission in an intensive care unit, discharge disposition, complications, and in-hospital mortality were analyzed.
RESULTS: Overall, 807,307 cholecystectomies were performed in France over the study period, with an increase in the national incidence rate from 167.5 (95\%CI [166.5; 168.5]) to 182.6 (95\%CI [181.6; 183.6]) per 100,000 inhabitants. Females accounted for 66.5\% of procedures (P{\textless}0.001). The mean age was lower for females than for males: 52.1 versus 60.2 (P{\textless}0.001). The ratio of laparoscopic cholecystectomy significantly increased from 90\% in 2008 to 94\% in 2014 (P{\textless}0.001). Average inpatient LOS decreased significantly from 6.5 days in 2008 to 4.7 days in 2014 (P{\textless}0.001). Most common complication type was intra-abdominal (23.1\%) for laparoscopic procedure (95\%CI [22.7; 23.5]), and in-hospital mortality significantly decreased over time from 0.45\% in 2008 to 0.38\% in 2014 (P{\textless}0.005).
CONCLUSION: Our results showed that the national incidence rate of cholecystectomy related to gallbladder disease increased from 2008 to 2014.},
	language = {eng},
	journal = {Journal of Visceral Surgery},
	author = {Bray, F. and Balcaen, T. and Baro, E. and Gandon, A. and Ficheur, G. and Chazard, E.},
	month = dec,
	year = {2018},
	pmid = {30573436},
	keywords = {Cholecystectomy, Epidemiology, Laparoscopic cholecystectomy, Nationwide database, Open cholecystectomy},
}

PURPOSE: Gallstones are one of the most common abdominal reasons for admission to hospital. The aim of this study was to analyze trends and outcomes in patients undergoing cholecystectomy with gallbladder related disease in France from 2008 to 2014. PATIENTS AND METHODS: We carried out a population-based, retrospective cohort study using data extracted from the French nationwide hospital discharge database (PMSI). We included all patients having a cholecystectomy related to gallbladder disease from January 2008 to December 2014. Patients' demographics, primary diagnosis, procedure type, length of stay (LOS), admission in an intensive care unit, discharge disposition, complications, and in-hospital mortality were analyzed. RESULTS: Overall, 807,307 cholecystectomies were performed in France over the study period, with an increase in the national incidence rate from 167.5 (95%CI [166.5; 168.5]) to 182.6 (95%CI [181.6; 183.6]) per 100,000 inhabitants. Females accounted for 66.5% of procedures (P\textless0.001). The mean age was lower for females than for males: 52.1 versus 60.2 (P\textless0.001). The ratio of laparoscopic cholecystectomy significantly increased from 90% in 2008 to 94% in 2014 (P\textless0.001). Average inpatient LOS decreased significantly from 6.5 days in 2008 to 4.7 days in 2014 (P\textless0.001). Most common complication type was intra-abdominal (23.1%) for laparoscopic procedure (95%CI [22.7; 23.5]), and in-hospital mortality significantly decreased over time from 0.45% in 2008 to 0.38% in 2014 (P\textless0.005). CONCLUSION: Our results showed that the national incidence rate of cholecystectomy related to gallbladder disease increased from 2008 to 2014.

@article{rochoy_vascular_2018,
	title = {Vascular dementia encoding in the {French} nationwide discharge summary database ({PMSI}): {Variability} over the 2007-2017 period},
	issn = {1768-3181},
	shorttitle = {Vascular dementia encoding in the {French} nationwide discharge summary database ({PMSI})},
	doi = {10.1016/j.ancard.2018.10.011},
	abstract = {OBJECTIVE: Vascular dementia (VaD) is the second leading cause of dementia. Diagnostic criteria have evolved from the concept of multiple infarctions to different subtypes: acute onset VaD, subcortical VaD, mixed cortical and subcortical VaD. Our aim was to analyze the evolution in the coding of these different subtypes of VaD in the French nationwide exhaustive hospital discharge database (PMSI) between 2007 and 2017.
METHOD: We included all principal diagnoses of VaD in the PMSI hospital stays from 2007 to 2017.
RESULTS: Between 2007 and 2017, we show a relative decrease in the number of hospital stays for VaD compared to all hospital stays (0.0437\% to 0.0404\%). The 11,654 hospital stays for VaD in 2017 represent 13.5\% of mental organic disorders. Subtype analysis shows a decrease in hospital stays for multiple infarctions between 2007 and 2017 (-50\%), an increase for subcortical or mixed VaD (+20\%), acute onset VaD (+184\%) and an increase in "other VaD" (+85\%).
CONCLUSION: These data suggest a slight decrease in hospital stays for VaD, possibly related to better control of cardiovascular risk factors. They also suggest that the coding should be consistent with the evolution of diagnostic criteria.},
	language = {eng},
	journal = {Annales De Cardiologie Et D'angeiologie},
	author = {Rochoy, M. and Chazard, E. and Gautier, S. and Bordet, R.},
	month = nov,
	year = {2018},
	pmid = {30409382},
	keywords = {Base de données, Clinical coding, Codage clinique, Database, Dementia, Diagnosis, Diagnostic, Démence vasculaire, Vascular},
}

OBJECTIVE: Vascular dementia (VaD) is the second leading cause of dementia. Diagnostic criteria have evolved from the concept of multiple infarctions to different subtypes: acute onset VaD, subcortical VaD, mixed cortical and subcortical VaD. Our aim was to analyze the evolution in the coding of these different subtypes of VaD in the French nationwide exhaustive hospital discharge database (PMSI) between 2007 and 2017. METHOD: We included all principal diagnoses of VaD in the PMSI hospital stays from 2007 to 2017. RESULTS: Between 2007 and 2017, we show a relative decrease in the number of hospital stays for VaD compared to all hospital stays (0.0437% to 0.0404%). The 11,654 hospital stays for VaD in 2017 represent 13.5% of mental organic disorders. Subtype analysis shows a decrease in hospital stays for multiple infarctions between 2007 and 2017 (-50%), an increase for subcortical or mixed VaD (+20%), acute onset VaD (+184%) and an increase in "other VaD" (+85%). CONCLUSION: These data suggest a slight decrease in hospital stays for VaD, possibly related to better control of cardiovascular risk factors. They also suggest that the coding should be consistent with the evolution of diagnostic criteria.

@article{robert_hospital-acquired_2018,
	title = {Hospital-acquired hyperkalemia events in older patients are mostly due to avoidable, multifactorial, adverse drug reactions},
	issn = {1532-6535},
	doi = {10.1002/cpt.1239},
	abstract = {Drug-induced hyperkalemia is a frequent and severe complication in hospital setting. Other risk factors may also induce hyperkalemia but the combination of drugs and precipitating factors has not been extensively studied. The aim was to identify drug-induced hyperkalemia events in hospitalized older patients and to describe their combinations with precipitating factors. Two experts analyzed independently retrospective data of patients aged 75 years or more. Experts identified 471 hyperkalemia events and concluded that 379 (80.5\%) were induced by drugs. The cause was multifactorial (i.e. at least one drug with a precipitating factor) in 300 (79.2\%) of the 379 drug-induced hyperkalemia. Most of the drug-induced hyperkalemia events were avoidable (79.9\%) - mainly because of the multifactorial cause (e.g. dosage adaptation during acute kidney injury). Drug-induced hyperkalemia events are frequently combined with precipitating factors in hospitalized older patients and their prevention should focus on these combinations. This article is protected by copyright. All rights reserved.},
	language = {eng},
	journal = {Clinical Pharmacology and Therapeutics},
	author = {Robert, Laurine and Ficheur, Grégoire and Décaudin, Bertrand and Gellens, Juliette and Luyckx, Michel and Perichon, Renaud and Gautier, Sophie and Puisieux, François and Chazard, Emmanuel and Beuscart, Jean-Baptiste},
	month = sep,
	year = {2018},
	pmid = {30242829},
	keywords = {Adverse drug reactions, Elderly, Prevention},
}

Drug-induced hyperkalemia is a frequent and severe complication in hospital setting. Other risk factors may also induce hyperkalemia but the combination of drugs and precipitating factors has not been extensively studied. The aim was to identify drug-induced hyperkalemia events in hospitalized older patients and to describe their combinations with precipitating factors. Two experts analyzed independently retrospective data of patients aged 75 years or more. Experts identified 471 hyperkalemia events and concluded that 379 (80.5%) were induced by drugs. The cause was multifactorial (i.e. at least one drug with a precipitating factor) in 300 (79.2%) of the 379 drug-induced hyperkalemia. Most of the drug-induced hyperkalemia events were avoidable (79.9%) - mainly because of the multifactorial cause (e.g. dosage adaptation during acute kidney injury). Drug-induced hyperkalemia events are frequently combined with precipitating factors in hospitalized older patients and their prevention should focus on these combinations. This article is protected by copyright. All rights reserved.

@article{bensmaine_irisin_2018,
	title = {Irisin levels in {LMNA}-associated partial lipodystrophies},
	issn = {1878-1780},
	doi = {10.1016/j.diabet.2018.08.003},
	abstract = {AIM: The adipo-myokine irisin regulates energy expenditure and fat metabolism. LMNA-associated familial partial lipodystrophy (FPLD2) comprises insulin resistance, muscle hypertrophy and lipoatrophy. The aim of this study was to investigate whether irisin could be a biomarker of FPLD2.
PATIENTS AND METHODS: This case control study included 19 FPLD2 subjects, 13 obese non-diabetic (OND) patients and 19 healthy controls (HC) of normal weight (median BMI: 26, 39 and 22 kg/m2, respectively). Serum irisin and leptin levels, body composition (DXA/MRI) and metabolic/inflammatory parameters were compared in these three groups.
RESULTS: BMI and MRI intra-abdominal fat significantly differed among these three groups, whereas DXA total fat mass and leptin levels were higher in the OND group, but did not differ between HC and FPLD2. Lipodystrophy patients had higher intra-abdominal/total abdominal fat ratios than the other two groups. Irisin levels were higher in FPLD2 and OND patients than in HC (medians: 944, 934 and 804 ng/mL, respectively). However, irisin/leptin ratios and lean body mass percentages were strikingly higher, and lean mass indices lower, in FPLD2 and HC than in the OND (median irisin/leptin ratios: 137, 166 and 21, respectively). In the entire study group, irisin levels positively correlated with BMI, lean body mass and index, intra-abdominal/total abdominal fat ratio, triglyceride, cholesterol, insulin, glucose and HbA1c levels. Also, intra-abdominal/total abdominal fat ratio and lean body mass better differentiated the three groups only in female patients.
CONCLUSION: Circulating irisin is similarly increased in FPLD2 and OND patients, who are characterized by higher lean body mass regardless of their clearly different fat mass. However, irisin/leptin ratios, strikingly higher in FPLD2 than in OND patients, could help to make the diagnosis and prompt genetic testing in clinically atypical cases.},
	language = {eng},
	journal = {Diabetes \& Metabolism},
	author = {Bensmaïne, F. and Benomar, K. and Espiard, S. and Vahe, C. and Le Mapihan, K. and Lion, G. and Lemdani, M. and Chazard, E. and Ernst, O. and Vigouroux, C. and Pigny, P. and Vantyghem, M.-C.},
	month = aug,
	year = {2018},
	pmid = {30165155},
	keywords = {Fat mass, Irisin, Lamin A, Lean mass, Leptin, Lipodystrophy, Muscle, Obesity},
}

AIM: The adipo-myokine irisin regulates energy expenditure and fat metabolism. LMNA-associated familial partial lipodystrophy (FPLD2) comprises insulin resistance, muscle hypertrophy and lipoatrophy. The aim of this study was to investigate whether irisin could be a biomarker of FPLD2. PATIENTS AND METHODS: This case control study included 19 FPLD2 subjects, 13 obese non-diabetic (OND) patients and 19 healthy controls (HC) of normal weight (median BMI: 26, 39 and 22 kg/m2, respectively). Serum irisin and leptin levels, body composition (DXA/MRI) and metabolic/inflammatory parameters were compared in these three groups. RESULTS: BMI and MRI intra-abdominal fat significantly differed among these three groups, whereas DXA total fat mass and leptin levels were higher in the OND group, but did not differ between HC and FPLD2. Lipodystrophy patients had higher intra-abdominal/total abdominal fat ratios than the other two groups. Irisin levels were higher in FPLD2 and OND patients than in HC (medians: 944, 934 and 804 ng/mL, respectively). However, irisin/leptin ratios and lean body mass percentages were strikingly higher, and lean mass indices lower, in FPLD2 and HC than in the OND (median irisin/leptin ratios: 137, 166 and 21, respectively). In the entire study group, irisin levels positively correlated with BMI, lean body mass and index, intra-abdominal/total abdominal fat ratio, triglyceride, cholesterol, insulin, glucose and HbA1c levels. Also, intra-abdominal/total abdominal fat ratio and lean body mass better differentiated the three groups only in female patients. CONCLUSION: Circulating irisin is similarly increased in FPLD2 and OND patients, who are characterized by higher lean body mass regardless of their clearly different fat mass. However, irisin/leptin ratios, strikingly higher in FPLD2 than in OND patients, could help to make the diagnosis and prompt genetic testing in clinically atypical cases.

@article{bouzille_drug_2018,
	title = {Drug safety and big clinical data: {Detection} of drug-induced anaphylactic shock events},
	issn = {1365-2753},
	shorttitle = {Drug safety and big clinical data},
	url = {https://hal-univ-rennes1.archives-ouvertes.fr/hal-01833093/document},
	doi = {10.1111/jep.12908},
	abstract = {RATIONALE, AIMS, AND OBJECTIVES: The spontaneous reporting system currently used in pharmacovigilance is not sufficiently exhaustive to detect all adverse drug reactions (ADRs). With the widespread use of electronic health records, biomedical data collected during the clinical care process can be reused and analysed to better detect ADRs. The aim of this study was to assess whether querying a Clinical Data Warehouse (CDW) could increase the detection of drug-induced anaphylaxis.
METHODS: All known cases of drug-induced anaphylaxis that occurred or required hospitalization at Rennes Academic Hospital in 2011 (n = 19) were retrieved from the French pharmacovigilance database, which contains all reported ADR events. Then, from the Rennes Academic Hospital CDW, a training set (all patients hospitalized in 2011) and a test set (all patients hospitalized in 2012) were extracted. The training set was used to define an optimized query, by building a set of keywords (based on the known cases) and exclusion criteria to search structured and unstructured data within the CDW in order to identify at least all known cases of drug-induced anaphylaxis for 2011. Then, the real performance of the optimized query was tested in the test set.
RESULTS: Using the optimized query, 59 cases of drug-induced anaphylaxis were identified among the 253 patient records extracted from the test set as possible anaphylaxis cases. Specifically, the optimal query identified 41 drug-induced anaphylaxis cases that were not detected by searching the French pharmacovigilance database but missed 7 cases detected only by spontaneous reporting.
DISCUSSION: We proposed an information retrieval-based method for detecting drug-induced anaphylaxis, by querying structured and unstructured data in a CDW. CDW queries are less specific than spontaneous reporting and Diagnosis-related Groups queries, although their sensitivity is much higher. CDW queries can facilitate monitoring by pharmacovigilance experts. Our method could be easily incorporated in the routine practice.},
	language = {eng},
	journal = {Journal of Evaluation in Clinical Practice},
	author = {Bouzillé, Guillaume and Osmont, Marie-Noëlle and Triquet, Louise and Grabar, Natalia and Rochefort-Morel, Cécile and Chazard, Emmanuel and Polard, Elisabeth and Cuggia, Marc},
	month = mar,
	year = {2018},
	pmid = {29532572},
	keywords = {adverse drug reaction reporting systems, drug-related side effects and adverse reactions, electronic health records, information storage and retrieval},
}

RATIONALE, AIMS, AND OBJECTIVES: The spontaneous reporting system currently used in pharmacovigilance is not sufficiently exhaustive to detect all adverse drug reactions (ADRs). With the widespread use of electronic health records, biomedical data collected during the clinical care process can be reused and analysed to better detect ADRs. The aim of this study was to assess whether querying a Clinical Data Warehouse (CDW) could increase the detection of drug-induced anaphylaxis. METHODS: All known cases of drug-induced anaphylaxis that occurred or required hospitalization at Rennes Academic Hospital in 2011 (n = 19) were retrieved from the French pharmacovigilance database, which contains all reported ADR events. Then, from the Rennes Academic Hospital CDW, a training set (all patients hospitalized in 2011) and a test set (all patients hospitalized in 2012) were extracted. The training set was used to define an optimized query, by building a set of keywords (based on the known cases) and exclusion criteria to search structured and unstructured data within the CDW in order to identify at least all known cases of drug-induced anaphylaxis for 2011. Then, the real performance of the optimized query was tested in the test set. RESULTS: Using the optimized query, 59 cases of drug-induced anaphylaxis were identified among the 253 patient records extracted from the test set as possible anaphylaxis cases. Specifically, the optimal query identified 41 drug-induced anaphylaxis cases that were not detected by searching the French pharmacovigilance database but missed 7 cases detected only by spontaneous reporting. DISCUSSION: We proposed an information retrieval-based method for detecting drug-induced anaphylaxis, by querying structured and unstructured data in a CDW. CDW queries are less specific than spontaneous reporting and Diagnosis-related Groups queries, although their sensitivity is much higher. CDW queries can facilitate monitoring by pharmacovigilance experts. Our method could be easily incorporated in the routine practice.

@article{bouzille_leveraging_2018,
	title = {Leveraging hospital big data to monitor flu epidemics},
	volume = {154},
	copyright = {All rights reserved},
	issn = {1872-7565},
	doi = {10.1016/j.cmpb.2017.11.012},
	abstract = {BACKGROUND AND OBJECTIVE: Influenza epidemics are a major public health concern and require a costly and time-consuming surveillance system at different geographical scales. The main challenge is being able to predict epidemics. Besides traditional surveillance systems, such as the French Sentinel network, several studies proposed prediction models based on internet-user activity. Here, we assessed the potential of hospital big data to monitor influenza epidemics.
METHODS: We used the clinical data warehouse of the Academic Hospital of Rennes (France) and then built different queries to retrieve relevant information from electronic health records to gather weekly influenza-like illness activity.
RESULTS: We found that the query most highly correlated with Sentinel network estimates was based on emergency reports concerning discharged patients with a final diagnosis of influenza (Pearson's correlation coefficient (PCC) of 0.931). The other tested queries were based on structured data (ICD-10 codes of influenza in Diagnosis-related Groups, and influenza PCR tests) and performed best (PCC of 0.981 and 0.953, respectively) during the flu season 2014-15. This suggests that both ICD-10 codes and PCR results are associated with severe epidemics. Finally, our approach allowed us to obtain additional patients' characteristics, such as the sex ratio or age groups, comparable with those from the Sentinel network.
CONCLUSIONS: Conclusions: Hospital big data seem to have a great potential for monitoring influenza epidemics in near real-time. Such a method could constitute a complementary tool to standard surveillance systems by providing additional characteristics on the concerned population or by providing information earlier. This system could also be easily extended to other diseases with possible activity changes. Additional work is needed to assess the real efficacy of predictive models based on hospital big data to predict flu epidemics.},
	language = {eng},
	journal = {Computer Methods and Programs in Biomedicine},
	author = {Bouzillé, Guillaume and Poirier, Canelle and Campillo-Gimenez, Boris and Aubert, Marie-Laure and Chabot, Mélanie and Chazard, Emmanuel and Lavenu, Audrey and Cuggia, Marc},
	month = feb,
	year = {2018},
	pmid = {29249339},
	keywords = {Clinical data warehouse, Health Information Systems, Health big data, Influenza, Information retrieval system, Sentinel Surveillance, Sentinel surveillance},
	pages = {153--160},
}

BACKGROUND AND OBJECTIVE: Influenza epidemics are a major public health concern and require a costly and time-consuming surveillance system at different geographical scales. The main challenge is being able to predict epidemics. Besides traditional surveillance systems, such as the French Sentinel network, several studies proposed prediction models based on internet-user activity. Here, we assessed the potential of hospital big data to monitor influenza epidemics. METHODS: We used the clinical data warehouse of the Academic Hospital of Rennes (France) and then built different queries to retrieve relevant information from electronic health records to gather weekly influenza-like illness activity. RESULTS: We found that the query most highly correlated with Sentinel network estimates was based on emergency reports concerning discharged patients with a final diagnosis of influenza (Pearson's correlation coefficient (PCC) of 0.931). The other tested queries were based on structured data (ICD-10 codes of influenza in Diagnosis-related Groups, and influenza PCR tests) and performed best (PCC of 0.981 and 0.953, respectively) during the flu season 2014-15. This suggests that both ICD-10 codes and PCR results are associated with severe epidemics. Finally, our approach allowed us to obtain additional patients' characteristics, such as the sex ratio or age groups, comparable with those from the Sentinel network. CONCLUSIONS: Conclusions: Hospital big data seem to have a great potential for monitoring influenza epidemics in near real-time. Such a method could constitute a complementary tool to standard surveillance systems by providing additional characteristics on the concerned population or by providing information earlier. This system could also be easily extended to other diseases with possible activity changes. Additional work is needed to assess the real efficacy of predictive models based on hospital big data to predict flu epidemics.

@article{dhaenens_clinmine:_2018,
	title = {{ClinMine}: {Optimizing} the {Management} of {Patients} in {Hospital}},
	issn = {1959-0318},
	shorttitle = {{ClinMine}},
	url = {https://hal.inria.fr/hal-01692197/document},
	doi = {10.1016/j.irbm.2017.12.002},
	abstract = {Context
A better understanding of “patient pathway” thanks to data analysis can lead to better treatments for patients. The ClinMine project, supported by the French National Research Agency (ANR), aims at proposing, from various case studies, algorithmic and statistical models able to handle this type of pathway data, focusing primarily on hospital data.
Methods
This article presents two of these case studies, focusing on the integration of temporal data within analysis. First, the hypothesis that some aspects of the patient pathway can be described, even predicted, from the management process of the hospital medical mail is studied. Therefore a specific functional data analysis is driven, and several types of patients have been detected. The second case study deals with the detection of profiles through a biclustering of the patients. The difficulty to simultaneously deal with heterogeneous data, including temporal data is exposed and a method is proposed.
Results
Experiments are driven on real data coming from a hospital. Results on these data show the effectiveness of the two proposed methods.
Conclusion
The project ClinMine aimed at dealing with hospital data in order to provide a better understanding of “patient pathway”. The two methods proposed here show their ability to simultaneously deal with heterogeneous data, including temporal aspects, and manages to give information for the understanding of “patient pathway” (identification of interesting clusters of patients).},
	journal = {IRBM},
	author = {Dhaenens, C. and Jacques, J. and Vandewalle, V. and Vandromme, M. and Chazard, E. and Preda, C. and Amarioarei, A. and Chaiwuttisak, P. and Cozma, C. and Ficheur, G. and Kessaci, M. -E. and Perichon, R. and Taillard, J. and Bordet, R. and Lansiaux, A. and Jourdan, L. and Delerue, D. and Hansske, A.},
	month = jan,
	year = {2018},
	keywords = {Electronic Health Records, Heterogeneous data, Hospital information system, Optimization algorithms, Patient pathway, Temporal data, statistical analysis},
}

Context A better understanding of “patient pathway” thanks to data analysis can lead to better treatments for patients. The ClinMine project, supported by the French National Research Agency (ANR), aims at proposing, from various case studies, algorithmic and statistical models able to handle this type of pathway data, focusing primarily on hospital data. Methods This article presents two of these case studies, focusing on the integration of temporal data within analysis. First, the hypothesis that some aspects of the patient pathway can be described, even predicted, from the management process of the hospital medical mail is studied. Therefore a specific functional data analysis is driven, and several types of patients have been detected. The second case study deals with the detection of profiles through a biclustering of the patients. The difficulty to simultaneously deal with heterogeneous data, including temporal data is exposed and a method is proposed. Results Experiments are driven on real data coming from a hospital. Results on these data show the effectiveness of the two proposed methods. Conclusion The project ClinMine aimed at dealing with hospital data in order to provide a better understanding of “patient pathway”. The two methods proposed here show their ability to simultaneously deal with heterogeneous data, including temporal aspects, and manages to give information for the understanding of “patient pathway” (identification of interesting clusters of patients).

@article{engelmann_comparison_2018,
	title = {Comparison of two commercial quantitative {PCR} assays and correlation with the first {WHO} {International} {Standard} for human {CMV}},
	issn = {1879-0070},
	doi = {10.1016/j.diagmicrobio.2017.12.021},
	abstract = {Comparability between CMV assays could be facilitated by the first WHO International Standard for human CMV (standard). Standard dilutions were submitted to nucleic acid extraction with Versant kPCR Molecular systems SP or MagNA Pure LC System followed by the kPCR PLX™ CMV DNA (kPCR) or the CMV R-gene™ assay (R-gene), respectively; 139 clinical specimens were tested. Both assays correlated well with the standard (R2{\textgreater} 0.96) and a matrix effect was observed. Quantitative results correlated reasonably between both assays for whole blood (R2= 0.79) and well for other specimen types (R2= 0.93). Quantification differences were within one log10of the averaged log10results for 25/27 blood specimens and for 32/33 other specimens. Calibration to the standard did not increase this percentage. In conclusion, results of both assays showed reasonable correlation with each other and good correlation with the standard. Calibration to the standard did not improve comparability of quantitative results.},
	language = {eng},
	journal = {Diagnostic Microbiology and Infectious Disease},
	author = {Engelmann, Ilka and Alidjinou, Enagnon Kazali and Lazrek, Mouna and Ogiez, Judith and Pouillaude, Jean-Marie and Chazard, Emmanuel and Dewilde, Anny and Hober, Didier},
	month = jan,
	year = {2018},
	pmid = {29463426},
	keywords = {CMV, Molecular testing, PCR, Viral load, WHO standard, molecular testing, viral load},
}

Comparability between CMV assays could be facilitated by the first WHO International Standard for human CMV (standard). Standard dilutions were submitted to nucleic acid extraction with Versant kPCR Molecular systems SP or MagNA Pure LC System followed by the kPCR PLX™ CMV DNA (kPCR) or the CMV R-gene™ assay (R-gene), respectively; 139 clinical specimens were tested. Both assays correlated well with the standard (R2\textgreater 0.96) and a matrix effect was observed. Quantitative results correlated reasonably between both assays for whole blood (R2= 0.79) and well for other specimen types (R2= 0.93). Quantification differences were within one log10of the averaged log10results for 25/27 blood specimens and for 32/33 other specimens. Calibration to the standard did not increase this percentage. In conclusion, results of both assays showed reasonable correlation with each other and good correlation with the standard. Calibration to the standard did not improve comparability of quantitative results.

@article{sylvestre_combining_2018,
	title = {Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records},
	volume = {18},
	issn = {1472-6947},
	url = {https://hal-univ-rennes1.archives-ouvertes.fr/hal-01709604/document},
	doi = {10.1186/s12911-018-0586-x},
	abstract = {BACKGROUND: Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to detect comorbidities in electronic health records (EHR) by using a clinical data warehouse (CDW) and a knowledge database.
METHODS: We enriched the Theriaque pharmaceutical database with the French national Comorbidities List to identify drugs associated with at least one major comorbid condition and diagnoses associated with a drug indication. Then, we compared the drug indications in the Theriaque database with the ICD-10 billing codes in EHR to detect potentially missing comorbidities based on drug prescriptions. Finally, we improved comorbidity detection by matching drug prescriptions and laboratory test results. We tested the obtained algorithm by using two retrospective datasets extracted from the Rennes University Hospital (RUH) CDW. The first dataset included all adult patients hospitalized in the ear, nose, throat (ENT) surgical ward between October and December 2014 (ENT dataset). The second included all adult patients hospitalized at RUH between January and February 2015 (general dataset). We reviewed medical records to find written evidence of the suggested comorbidities in current or past stays.
RESULTS: Among the 22,132 Common Units of Dispensation (CUD) codes present in the Theriaque database, 19,970 drugs (90.2\%) were associated with one or several ICD-10 diagnoses, based on their indication, and 11,162 (50.4\%) with at least one of the 4878 comorbidities from the comorbidity list. Among the 122 patients of the ENT dataset, 75.4\% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 44.6\% of the cases. Among the 4312 patients of the general dataset, 68.4\% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 20.3\% of reviewed cases.
CONCLUSIONS: This simple algorithm based on combining accessible and immediately reusable data from knowledge databases, drug prescriptions and laboratory test results can detect comorbidities.},
	language = {eng},
	number = {1},
	journal = {BMC medical informatics and decision making},
	author = {Sylvestre, Emmanuelle and Bouzillé, Guillaume and Chazard, Emmanuel and His-Mahier, Cécil and Riou, Christine and Cuggia, Marc},
	year = {2018},
	pmid = {29368609},
	pmcid = {PMC5784648},
	keywords = {Billing codes, Clinical data warehouse, Comorbidity, Databases, Drug prescriptions, Laboratory test results, Pharmaceutical},
	pages = {9},
}

BACKGROUND: Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to detect comorbidities in electronic health records (EHR) by using a clinical data warehouse (CDW) and a knowledge database. METHODS: We enriched the Theriaque pharmaceutical database with the French national Comorbidities List to identify drugs associated with at least one major comorbid condition and diagnoses associated with a drug indication. Then, we compared the drug indications in the Theriaque database with the ICD-10 billing codes in EHR to detect potentially missing comorbidities based on drug prescriptions. Finally, we improved comorbidity detection by matching drug prescriptions and laboratory test results. We tested the obtained algorithm by using two retrospective datasets extracted from the Rennes University Hospital (RUH) CDW. The first dataset included all adult patients hospitalized in the ear, nose, throat (ENT) surgical ward between October and December 2014 (ENT dataset). The second included all adult patients hospitalized at RUH between January and February 2015 (general dataset). We reviewed medical records to find written evidence of the suggested comorbidities in current or past stays. RESULTS: Among the 22,132 Common Units of Dispensation (CUD) codes present in the Theriaque database, 19,970 drugs (90.2%) were associated with one or several ICD-10 diagnoses, based on their indication, and 11,162 (50.4%) with at least one of the 4878 comorbidities from the comorbidity list. Among the 122 patients of the ENT dataset, 75.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 44.6% of the cases. Among the 4312 patients of the general dataset, 68.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 20.3% of reviewed cases. CONCLUSIONS: This simple algorithm based on combining accessible and immediately reusable data from knowledge databases, drug prescriptions and laboratory test results can detect comorbidities.

@article{berkhout_randomized_2018,
	title = {Randomized controlled trial on promoting influenza vaccination in general practice waiting rooms},
	volume = {13},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0192155},
	abstract = {BACKGROUND: Most of general practitioners (GPs) use advertising in their waiting rooms for patient's education purposes. Patients vaccinated against seasonal influenza have been gradually lessening. The objective of this trial was to assess the effect of an advertising campaign for influenza vaccination using posters and pamphlets in GPs' waiting rooms.
METHODS AND FINDINGS: Registry based 2/1 cluster randomized controlled trial, a cluster gathering the enlisted patients of 75 GPs aged over 16 years. The trial, run during the 2014-2015 influenza vaccination campaign, compared patient's awareness from being in 50 GPs' standard waiting rooms (control group) versus that of waiting in 25 rooms from GPs who had received and exposed pamphlets and one poster on influenza vaccine (intervention group), in addition to standard mandatory information. The main outcome was the number of vaccination units delivered in pharmacies. Data were extracted from the SIAM-ERASME claim database of the Health Insurance Fund of Lille-Douai (France). The association between the intervention (yes/no) and the main outcome was assessed through a generalized estimating equation. Seventy-five GPs enrolled 10,597 patients over 65 years or suffering from long lasting diseases (intervention/control as of 3781/6816 patients) from October 15, 2014 to February 28, 2015. No difference was found regarding the number of influenza vaccination units delivered (Relative Risk (RR) = 1.01; 95\% Confidence interval: 0.97 to 1.05; p = 0.561).
CONCLUSION: Effects of the monothematic campaign promoting vaccination against influenza using a poster and pamphlets exposed in GPs' waiting rooms could not be demonstrated.},
	language = {eng},
	number = {2},
	journal = {PloS One},
	author = {Berkhout, Christophe and Willefert-Bouche, Amy and Chazard, Emmanuel and Zgorska-Maynard-Moussa, Suzanna and Favre, Jonathan and Peremans, Lieve and Ficheur, Grégoire and Van Royen, Paul},
	year = {2018},
	pmid = {29425226},
	pages = {e0192155},
}

BACKGROUND: Most of general practitioners (GPs) use advertising in their waiting rooms for patient's education purposes. Patients vaccinated against seasonal influenza have been gradually lessening. The objective of this trial was to assess the effect of an advertising campaign for influenza vaccination using posters and pamphlets in GPs' waiting rooms. METHODS AND FINDINGS: Registry based 2/1 cluster randomized controlled trial, a cluster gathering the enlisted patients of 75 GPs aged over 16 years. The trial, run during the 2014-2015 influenza vaccination campaign, compared patient's awareness from being in 50 GPs' standard waiting rooms (control group) versus that of waiting in 25 rooms from GPs who had received and exposed pamphlets and one poster on influenza vaccine (intervention group), in addition to standard mandatory information. The main outcome was the number of vaccination units delivered in pharmacies. Data were extracted from the SIAM-ERASME claim database of the Health Insurance Fund of Lille-Douai (France). The association between the intervention (yes/no) and the main outcome was assessed through a generalized estimating equation. Seventy-five GPs enrolled 10,597 patients over 65 years or suffering from long lasting diseases (intervention/control as of 3781/6816 patients) from October 15, 2014 to February 28, 2015. No difference was found regarding the number of influenza vaccination units delivered (Relative Risk (RR) = 1.01; 95% Confidence interval: 0.97 to 1.05; p = 0.561). CONCLUSION: Effects of the monothematic campaign promoting vaccination against influenza using a poster and pamphlets exposed in GPs' waiting rooms could not be demonstrated.

@article{chazard_secondary_2018,
	title = {Secondary {Use} of {Healthcare} {Structured} {Data}: {The} {Challenge} of {Domain}-{Knowledge} {Based} {Extraction} of {Features}},
	volume = {255},
	issn = {0926-9630},
	shorttitle = {Secondary {Use} of {Healthcare} {Structured} {Data}},
	abstract = {Secondary use of clinical structured data takes an important place in healthcare research. It was first described by Fayyad as "knowledge discovery in databases". Feature extraction is an important phase but received little attention. The objectives of this paper are: 1) to propose an updated representation of data reuse in healthcare, 2) to illustrate methods and objectives of feature extraction, and 3) to discuss the place of domain-specific knowledge.
MATERIAL AND METHODS: an updated representation is proposed. Then, a case study consists of automatically identifying acute renal failure and discovering risk factors, by secondary use of structured data. Finally, a literature review published par Meystre et al. is analyzed.
RESULTS: 1) we propose a description of data reuse in 5 phases. Phase 1 is data preprocessing (cleansing, linkage, terminological alignment, unit conversions, deidentification), it enables to construct a data warehouse. Phase 2 is feature extraction. Phase 3 is statistical and graphical mining. Phase 4 consists of expert filtering and reorganization of statistical results. Phase 5 is decision making. 2) The case study illustrates how time-dependent features can be extracted from laboratory results and drug administrations, using domain-specific knowledge. 3) Among the 200 papers cited by Meystre et al., the first and last authors were affiliated to health institutions in 74\% (68\% for methodological papers, and 79\% for applied papers).
DISCUSSION: features extraction has a major impact on success of data reuse. Specific knowledge-based reasoning takes an important place in feature extraction, which requires tight collaboration between computer scientists, statisticians, and health professionals.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Chazard, Emmanuel and Ficheur, Grégoire and Caron, Alexandre and Lamer, Antoine and Labreuche, Julien and Cuggia, Marc and Genin, Michaël and Bouzille, Guillaume and Duhamel, Alain},
	year = {2018},
	pmid = {30306898},
	keywords = {Data reuse, data transformation, feature extraction},
	pages = {15--19},
}

Secondary use of clinical structured data takes an important place in healthcare research. It was first described by Fayyad as "knowledge discovery in databases". Feature extraction is an important phase but received little attention. The objectives of this paper are: 1) to propose an updated representation of data reuse in healthcare, 2) to illustrate methods and objectives of feature extraction, and 3) to discuss the place of domain-specific knowledge. MATERIAL AND METHODS: an updated representation is proposed. Then, a case study consists of automatically identifying acute renal failure and discovering risk factors, by secondary use of structured data. Finally, a literature review published par Meystre et al. is analyzed. RESULTS: 1) we propose a description of data reuse in 5 phases. Phase 1 is data preprocessing (cleansing, linkage, terminological alignment, unit conversions, deidentification), it enables to construct a data warehouse. Phase 2 is feature extraction. Phase 3 is statistical and graphical mining. Phase 4 consists of expert filtering and reorganization of statistical results. Phase 5 is decision making. 2) The case study illustrates how time-dependent features can be extracted from laboratory results and drug administrations, using domain-specific knowledge. 3) Among the 200 papers cited by Meystre et al., the first and last authors were affiliated to health institutions in 74% (68% for methodological papers, and 79% for applied papers). DISCUSSION: features extraction has a major impact on success of data reuse. Specific knowledge-based reasoning takes an important place in feature extraction, which requires tight collaboration between computer scientists, statisticians, and health professionals.

@article{lamer_data_2018,
	title = {From {Data} {Extraction} to {Analysis}: {Proposal} of a {Methodology} to {Optimize} {Hospital} {Data} {Reuse} {Process}},
	volume = {247},
	issn = {0926-9630},
	shorttitle = {From {Data} {Extraction} to {Analysis}},
	abstract = {In the Lille University Hospital (North of France), data from the Anesthesia Information Management System (Diane® are linked to the Hospital Information System and stored in a dedicated data warehouse since 2010. These electronic medical records need to be reused and analyzed for observational studies. The aim of this paper is to describe the framework developed to structure the operation of that anesthesia data warehouse for research purposes. The presented framework is structured around three meetings between clinicians, computer scientists, and statisticians. The data scientist acts as a coordinator, leads meetings, and checks each milestone. Reuse of anesthesia-related electronic medical record for research purposes is only allowed through this framework. The aim of the first meeting is to decide the primary and secondary objectives of the study. The aim of the second meeting is to validate the statistical protocol. The data are extracted and the statistical analyses are performed. Finally, the results are presented, explained and discussed during the third meeting. During a 6 months period, 27 projects were included in the framework leading to 5 scientific communications. As a result, case studies with extraction and/or analysis situations are presented. This collaboration led to an empowerment process between all three actors, which increased efficiency of the workflow. Implementation of this framework will keep encouraging collaborative publication in order to provide reproducible research evidence.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Lamer, Antoine and Ficheur, Grégoire and Rousselet, Louis and van Berleere, Marine and Chazard, Emmanuel and Caron, Alexandre},
	year = {2018},
	pmid = {29677919},
	keywords = {Data Science, Electronic Medical Records, Healthcare Data Reuse, Reproducible Research, Statistical Analysis},
	pages = {41--45},
}

In the Lille University Hospital (North of France), data from the Anesthesia Information Management System (Diane® are linked to the Hospital Information System and stored in a dedicated data warehouse since 2010. These electronic medical records need to be reused and analyzed for observational studies. The aim of this paper is to describe the framework developed to structure the operation of that anesthesia data warehouse for research purposes. The presented framework is structured around three meetings between clinicians, computer scientists, and statisticians. The data scientist acts as a coordinator, leads meetings, and checks each milestone. Reuse of anesthesia-related electronic medical record for research purposes is only allowed through this framework. The aim of the first meeting is to decide the primary and secondary objectives of the study. The aim of the second meeting is to validate the statistical protocol. The data are extracted and the statistical analyses are performed. Finally, the results are presented, explained and discussed during the third meeting. During a 6 months period, 27 projects were included in the framework leading to 5 scientific communications. As a result, case studies with extraction and/or analysis situations are presented. This collaboration led to an empowerment process between all three actors, which increased efficiency of the workflow. Implementation of this framework will keep encouraging collaborative publication in order to provide reproducible research evidence.

@article{georges_enhancing_2018,
	title = {Enhancing {Nationwide} {Medico}-{Administrative} {Databases} {Analysis} with {SAF4SUHAD}: {A} {Statistical} {Analysis} {Framework} for {Secondary} {Use} of {Healthcare} {Administrative} {Databases}},
	volume = {255},
	issn = {0926-9630},
	shorttitle = {Enhancing {Nationwide} {Medico}-{Administrative} {Databases} {Analysis} with {SAF4SUHAD}},
	abstract = {Many epidemiological studies now rely on the reuse of large healthcare administrative databases. In those studies, most of the time is consumed in managing data and performing basic statistical analyses and is not available anymore for complex statistical and medical analysis, therefore the potential of such databases is sometimes underexploited. The objective of this work is to build SAF4SUHAD, a statistical analysis framework for secondary use of healthcare administrative databases, using literature-based specifications. A literature review was performed on PubMed in four different medical domains: caesarian deliveries, cholecystectomies, hip replacement surgeries and bariatric surgeries. We identified 22 papers relating analyses of large databases. They reported epidemiological indicators (e.g. mean age), that were abstracted to features (e.g. univariate description of a quantitative variable), and then were implemented through 32 functions available for the user in R programming language. For instance, a function will draw a histogram, compute the mean with confidence interval, quantiles, etc. Those functions comprehend 4 functions for data management, 9 for univariate analysis, 8 for bivariate analysis, 11 for multivariate analysis, and many other intermediate functions. Those functions were successfully used to analyze a French database of 250 million discharge summaries. The set of R ready-to-use functions defined in this work could enable to secure repetitive tasks, and to refocus efforts on expert analysis.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Georges, Alexandre and Balcaen, Thibaut and Caron, Alexandre and Ficheur, Gregoire and Chazard, Emmanuel},
	year = {2018},
	pmid = {30306900},
	keywords = {Healthcare epidemiology, Medico-administrative databases, Statistics},
	pages = {25--29},
}

Many epidemiological studies now rely on the reuse of large healthcare administrative databases. In those studies, most of the time is consumed in managing data and performing basic statistical analyses and is not available anymore for complex statistical and medical analysis, therefore the potential of such databases is sometimes underexploited. The objective of this work is to build SAF4SUHAD, a statistical analysis framework for secondary use of healthcare administrative databases, using literature-based specifications. A literature review was performed on PubMed in four different medical domains: caesarian deliveries, cholecystectomies, hip replacement surgeries and bariatric surgeries. We identified 22 papers relating analyses of large databases. They reported epidemiological indicators (e.g. mean age), that were abstracted to features (e.g. univariate description of a quantitative variable), and then were implemented through 32 functions available for the user in R programming language. For instance, a function will draw a histogram, compute the mean with confidence interval, quantiles, etc. Those functions comprehend 4 functions for data management, 9 for univariate analysis, 8 for bivariate analysis, 11 for multivariate analysis, and many other intermediate functions. Those functions were successfully used to analyze a French database of 250 million discharge summaries. The set of R ready-to-use functions defined in this work could enable to secure repetitive tasks, and to refocus efforts on expert analysis.

@article{dezetree_comparison_2018,
	title = {Comparison of {Changes} in the {Number} of {Included} {Patients} {Between} {Interventional} {Trials} and {Observational} {Studies} {Published} from 1995 to 2014 in {Three} {Leading} {Journals}},
	volume = {255},
	issn = {0926-9630},
	abstract = {INTRODUCTION: Since the late 1990s, research and administrative institutions have been developing health data warehouses and increasingly reusing claims data. The impact of these changes is not yet completely quantified. Our objective was to compare the change in the number of patients included per study between observational and interventional studies over a 20-year period starting in 1995.
MATERIALS AND METHODS: We extracted all abstracts from studies published in three leading medical journals over the period 1995-2014 (18,107 studies). Then, we divided our study into two steps. First, we constructed an SVM-based predictive model to categorize each abstract into "observational", "interventional" or "other" studies. In a second step, we built an algorithm based on regular expressions to automatically extract the number of included patients.
RESULTS: During the investigated period, the median number of enrolled patients per study increased for interventional studies, from 282 in 1995-1999 to 629 in 2010-2014. In the same time, the median number of patients increased more for observational studies, from 368 in 1995-1999 to 2078 in 2010-2014.
DISCUSSION: The routine storage of an increasing amount of data (from data warehouses or claims data) has had an impact in recent years on the number of patients included in observational studies. The recent development of "randomized registry trials" combining, on the one hand, an intervention and, on the other hand, the identification of the outcome through data reuse, may also have an impact, over the next decade, on the number of patients included in randomized clinical trials.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Dezetree, Arnaud and Chazard, Emmanuel and Schlegel, Daniel R. and Sakilay, Sylvester and Elkin, Peter L. and Ficheur, Grégoire},
	year = {2018},
	pmid = {30306905},
	keywords = {Data reuse, claims data, data warehouse, support vector machine},
	pages = {50--54},
}

INTRODUCTION: Since the late 1990s, research and administrative institutions have been developing health data warehouses and increasingly reusing claims data. The impact of these changes is not yet completely quantified. Our objective was to compare the change in the number of patients included per study between observational and interventional studies over a 20-year period starting in 1995. MATERIALS AND METHODS: We extracted all abstracts from studies published in three leading medical journals over the period 1995-2014 (18,107 studies). Then, we divided our study into two steps. First, we constructed an SVM-based predictive model to categorize each abstract into "observational", "interventional" or "other" studies. In a second step, we built an algorithm based on regular expressions to automatically extract the number of included patients. RESULTS: During the investigated period, the median number of enrolled patients per study increased for interventional studies, from 282 in 1995-1999 to 629 in 2010-2014. In the same time, the median number of patients increased more for observational studies, from 368 in 1995-1999 to 2078 in 2010-2014. DISCUSSION: The routine storage of an increasing amount of data (from data warehouses or claims data) has had an impact in recent years on the number of patients included in observational studies. The recent development of "randomized registry trials" combining, on the one hand, an intervention and, on the other hand, the identification of the outcome through data reuse, may also have an impact, over the next decade, on the number of patients included in randomized clinical trials.

@phdthesis{chazard_reutilisation_2017,
	address = {Lille, France},
	type = {Habilitation à {Diriger} des {Recherches}},
	title = {Réutilisation et fouille de données massives de santé produites en routine au cours du soin},
	url = {http://www.chazard.org/emmanuel/pdf_articles/thesis_HDR_2017_chazard.pdf},
	language = {Fr},
	school = {Université de Lille},
	author = {Chazard, Emmanuel},
	month = dec,
	year = {2017},
}

@article{ferret_inappropriate_2017,
	title = {Inappropriate anticholinergic drugs prescriptions in older patients: analysing a hospital database},
	copyright = {All rights reserved},
	issn = {2210-7703, 2210-7711},
	shorttitle = {Inappropriate anticholinergic drugs prescriptions in older patients},
	url = {https://link.springer.com/article/10.1007/s11096-017-0554-z},
	doi = {10.1007/s11096-017-0554-z},
	abstract = {Background Although many anticholinergics are inappropriate in older patients, the prescription of these drugs in a hospital setting has not been extensively studied. Objective To describe prescriptions of anticholinergic drugs in terms of frequency, at risk situations and constipation in hospitalized, older adults. Setting Using a database from a French general hospital (period 2009–2013), we extracted information on 14,090 hospital stays by patients aged 75 and over. Methods Anticholinergic drug prescriptions were automatically detected, with a focus on prescriptions in three well-known at-risk situations: falls, dementia, and benign prostatic hyperplasia. Cases of constipation that might have been causally related to the administration of anticholinergic drugs were screened for and reviewed. Main outcome measure Prescriptions with a high associated risk of anticholinergic related adverse reactions. Results Administration of an anticholinergic drug was detected in 1412 (10.0\%) of the hospital stays by older patients. At-risk situations were identified in 413 (36.5\%) of these stays: 137 (9.7\%) for falls, 243 (17.2\%) for dementia, and 114 (8.1\%) for benign prostatic hyperplasia; 78 (18.9\%) of these 413 stays featured a combination of two or three at-risk situations. Cases of constipation induced by anticholinergic drug administration were identified in 188 (13.3\%) patient stays by using validated adjudication rules for adverse drug reactions: 85 and 103 cases were respectively evaluated as “possible” or “probable” adverse drug reactions. Conclusions Anticholinergic drugs prescription was found in 10.0\% of hospitalized, older patients. More than one third of these prescriptions occurred in at-risk situations and more than one in ten prescriptions induced constipation.},
	language = {en},
	urldate = {2017-11-17},
	journal = {International Journal of Clinical Pharmacy},
	author = {Ferret, Laurie and Ficheur, Gregoire and Delaviez, Emeline and Luyckx, Michel and Quenton, Sophie and Beuscart, Regis and Chazard, Emmanuel and Beuscart, Jean-Baptiste},
	month = nov,
	year = {2017},
	pages = {1--7},
}

Background Although many anticholinergics are inappropriate in older patients, the prescription of these drugs in a hospital setting has not been extensively studied. Objective To describe prescriptions of anticholinergic drugs in terms of frequency, at risk situations and constipation in hospitalized, older adults. Setting Using a database from a French general hospital (period 2009–2013), we extracted information on 14,090 hospital stays by patients aged 75 and over. Methods Anticholinergic drug prescriptions were automatically detected, with a focus on prescriptions in three well-known at-risk situations: falls, dementia, and benign prostatic hyperplasia. Cases of constipation that might have been causally related to the administration of anticholinergic drugs were screened for and reviewed. Main outcome measure Prescriptions with a high associated risk of anticholinergic related adverse reactions. Results Administration of an anticholinergic drug was detected in 1412 (10.0%) of the hospital stays by older patients. At-risk situations were identified in 413 (36.5%) of these stays: 137 (9.7%) for falls, 243 (17.2%) for dementia, and 114 (8.1%) for benign prostatic hyperplasia; 78 (18.9%) of these 413 stays featured a combination of two or three at-risk situations. Cases of constipation induced by anticholinergic drug administration were identified in 188 (13.3%) patient stays by using validated adjudication rules for adverse drug reactions: 85 and 103 cases were respectively evaluated as “possible” or “probable” adverse drug reactions. Conclusions Anticholinergic drugs prescription was found in 10.0% of hospitalized, older patients. More than one third of these prescriptions occurred in at-risk situations and more than one in ten prescriptions induced constipation.

@article{putman_epidemiologie_2017,
	series = {92e {Réunion} annuelle de la {SOFCOT}},
	title = {Épidémiologie des prothèses de hanche en {France} : analyse de la base nationale du {PMSI} de 2008 à 2014},
	volume = {103},
	issn = {1877-0517},
	shorttitle = {Épidémiologie des prothèses de hanche en {France}},
	url = {http://www.sciencedirect.com/science/article/pii/S1877051717304525},
	doi = {10.1016/j.rcot.2017.09.158},
	abstract = {Introduction
L’incidence des arthroplasties de hanche est en augmentation en France. L’objectif de ce travail était d’étudier l’épidémiologie de la pose de prothèses de hanche en France de 2008 à 2014.
Matériel et méthodes
En utilisant la base de données hospitalière nationale du Programme de médicalisation des systèmes d’information (PMSI) pour les années 2008 à 2014, nous avons identifié tous les patients opérés d’une pose de prothèse de hanche en utilisant la Classification commune des actes médicaux (CCAM). Nous avons analysé les données démographiques des patients, la durée de séjour, le diagnostic principal, le type d’hôpital, le type de prothèse et la mortalité hospitalière.
Résultats
De 2008 à 2014, il y a eu 1 049 637 arthroplasties de hanche (incluant les arthroplasties primaires par prothèse totale, les hémiarthroplasties primaires, et les arthroplasties de remplacement). Le taux d’incidence annuel est passé de 222 en 2008 à 241 pour 100 000 habitants en 2014. L’âge moyen des patients était de 72,8 ans. Soixante pour cent des arthroplasties de la hanche ont été effectuées chez des femmes. Les principales causes de pose de prothèses de hanche étaient l’arthrose (62 \%), les fractures (23,8 \%) et les complications mécaniques des prothèses (8,3 \%). Il y a eu 72,1 \% d’arthroplasties primaires par prothèses totales de la hanche, 16,7 \% d’hémiarthroplasties primaires et 11,6 \% d’arthroplasties de révision. La durée moyenne de séjour des patients hospitalisés était de 11,2jours et 1,28 \% des patients a passé au moins une journée dans une unité de soins intensifs. Dans l’ensemble, 45,6 \% des arthroplasties de hanche ont été effectuées dans des hôpitaux sans but lucratif. La mortalité intrahospitalière est passée de 1,26 \% en 2008 à 0,96 \% en 2014.
Discussion
L’incidence des prothèses de hanche, bien qu’en augmentation en France, reste inférieur aux États-unis et en Angleterre. L’augmentation de l’incidence des prothèses de hanche était principalement le résultat de l’augmentation des arthroplasties de hanches.
Conclusion
L’incidence des prothèses de hanche est en augmentation, avec une diminution de la durée de séjour et une diminution de la mortalité hospitalière.},
	number = {7, Supplement},
	journal = {Revue de Chirurgie Orthopédique et Traumatologique},
	author = {Putman, Sophie and Girier, Nicolas and Girard, Julien and Pasquier, Gilles and Migaud, Henri and Chazard, Emmanuel},
	month = nov,
	year = {2017},
	pages = {S90},
}

Introduction L’incidence des arthroplasties de hanche est en augmentation en France. L’objectif de ce travail était d’étudier l’épidémiologie de la pose de prothèses de hanche en France de 2008 à 2014. Matériel et méthodes En utilisant la base de données hospitalière nationale du Programme de médicalisation des systèmes d’information (PMSI) pour les années 2008 à 2014, nous avons identifié tous les patients opérés d’une pose de prothèse de hanche en utilisant la Classification commune des actes médicaux (CCAM). Nous avons analysé les données démographiques des patients, la durée de séjour, le diagnostic principal, le type d’hôpital, le type de prothèse et la mortalité hospitalière. Résultats De 2008 à 2014, il y a eu 1 049 637 arthroplasties de hanche (incluant les arthroplasties primaires par prothèse totale, les hémiarthroplasties primaires, et les arthroplasties de remplacement). Le taux d’incidence annuel est passé de 222 en 2008 à 241 pour 100 000 habitants en 2014. L’âge moyen des patients était de 72,8 ans. Soixante pour cent des arthroplasties de la hanche ont été effectuées chez des femmes. Les principales causes de pose de prothèses de hanche étaient l’arthrose (62 %), les fractures (23,8 %) et les complications mécaniques des prothèses (8,3 %). Il y a eu 72,1 % d’arthroplasties primaires par prothèses totales de la hanche, 16,7 % d’hémiarthroplasties primaires et 11,6 % d’arthroplasties de révision. La durée moyenne de séjour des patients hospitalisés était de 11,2jours et 1,28 % des patients a passé au moins une journée dans une unité de soins intensifs. Dans l’ensemble, 45,6 % des arthroplasties de hanche ont été effectuées dans des hôpitaux sans but lucratif. La mortalité intrahospitalière est passée de 1,26 % en 2008 à 0,96 % en 2014. Discussion L’incidence des prothèses de hanche, bien qu’en augmentation en France, reste inférieur aux États-unis et en Angleterre. L’augmentation de l’incidence des prothèses de hanche était principalement le résultat de l’augmentation des arthroplasties de hanches. Conclusion L’incidence des prothèses de hanche est en augmentation, avec une diminution de la durée de séjour et une diminution de la mortalité hospitalière.

@article{ghenassia_generic_2017,
	title = {A generic method for improving the spatial interoperability of medical and ecological databases},
	volume = {16},
	copyright = {All rights reserved},
	issn = {1476-072X},
	doi = {10.1186/s12942-017-0109-5},
	abstract = {BACKGROUND: The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution.
METHODS: Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index.
RESULTS: We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3\% [0; 5.7]. The spatial continuity criterion was low (2.4\%), and the spatial resolution index was greater than for most French administrative areas.
CONCLUSIONS: Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.},
	language = {eng},
	number = {1},
	journal = {International Journal of Health Geographics},
	author = {Ghenassia, A. and Beuscart, J. B. and Ficheur, G. and Occelli, F. and Babykina, E. and Chazard, E. and Genin, M.},
	month = oct,
	year = {2017},
	pmid = {28974262},
	keywords = {Change-of-support problem, Data reuse, Interoperability, Spatial analysis},
	pages = {36},
}

BACKGROUND: The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. METHODS: Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. RESULTS: We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. CONCLUSIONS: Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.

@article{baclet_explicit_2017,
	title = {Explicit definitions of potentially inappropriate prescriptions of antibiotics in older patients: a compilation derived from a systematic review},
	copyright = {All rights reserved},
	issn = {1872-7913},
	shorttitle = {Explicit definitions of potentially inappropriate prescriptions of antibiotics in older patients},
	doi = {10.1016/j.ijantimicag.2017.08.011},
	abstract = {CONTEXT: Potentially inappropriate prescriptions (PIPs) of antibiotics (antibiotic-PIPs) are generally detected by applying implicit definitions based on expert opinion. Explicit definitions are less frequently used, even though this approach would enable the automated detection of antibiotic-PIPs in electronic health records. Here, we systematically reviewed explicit definitions of antibiotic-PIPs used in studies of older adults.
METHOD: We searched the MEDLINE(®), Scopus(®) and Web of Science(TM) core collection databases with a combination of three terms and their synonyms: "potentially inappropriate prescription" AND "antibiotic treatment" AND "older patients". After the standardized selection of publications, explicit definitions of antibiotic-PIPs were extracted and classified into infectious disease domains and sub-domains.
RESULTS: A total of 600 search queries identified 4,270 records, 93 of which were selected for review. We found 160 mentions of antibiotic-PIPs, corresponding to 62 distinct definitions in 19 infectious disease domains. Nearly half of the definitions were related to upper respiratory tract infections (n=11 definitions; 17.7\%), lower respiratory tract infections (n=8; 12.9\%) and drug-drug interactions (n=11; 17.7\%). Almost 75\% of the definitions (n=46) were mentioned in a single study only. Only three definitions concerned critically important antibiotics, such as third-generation cephalosporins and fluoroquinolones.
CONCLUSION: Our systematic review identified 62 explicit definitions of antibiotic-PIPs. Most of the definitions were not found in more than one study, and they varied in the degree of precision. We advocate the implementation of an expert consensus on explicit definitions of antibiotic-PIPs that correspond to today's challenges in public health.},
	language = {eng},
	journal = {International Journal of Antimicrobial Agents},
	author = {Baclet, Nicolas and Ficheur, Grégoire and Alfandari, Serge and Ferret, Laurie and Senneville, Eric and Chazard, Emmanuel and Beuscart, Jean-Baptiste},
	month = aug,
	year = {2017},
	pmid = {28803931},
	keywords = {Antibiotics, Elderly, Potentially Inappropriate Prescription},
}

CONTEXT: Potentially inappropriate prescriptions (PIPs) of antibiotics (antibiotic-PIPs) are generally detected by applying implicit definitions based on expert opinion. Explicit definitions are less frequently used, even though this approach would enable the automated detection of antibiotic-PIPs in electronic health records. Here, we systematically reviewed explicit definitions of antibiotic-PIPs used in studies of older adults. METHOD: We searched the MEDLINE(®), Scopus(®) and Web of Science(TM) core collection databases with a combination of three terms and their synonyms: "potentially inappropriate prescription" AND "antibiotic treatment" AND "older patients". After the standardized selection of publications, explicit definitions of antibiotic-PIPs were extracted and classified into infectious disease domains and sub-domains. RESULTS: A total of 600 search queries identified 4,270 records, 93 of which were selected for review. We found 160 mentions of antibiotic-PIPs, corresponding to 62 distinct definitions in 19 infectious disease domains. Nearly half of the definitions were related to upper respiratory tract infections (n=11 definitions; 17.7%), lower respiratory tract infections (n=8; 12.9%) and drug-drug interactions (n=11; 17.7%). Almost 75% of the definitions (n=46) were mentioned in a single study only. Only three definitions concerned critically important antibiotics, such as third-generation cephalosporins and fluoroquinolones. CONCLUSION: Our systematic review identified 62 explicit definitions of antibiotic-PIPs. Most of the definitions were not found in more than one study, and they varied in the degree of precision. We advocate the implementation of an expert consensus on explicit definitions of antibiotic-PIPs that correspond to today's challenges in public health.

@article{chazard_how_2017,
	title = {How to {Compare} the {Length} of {Stay} of {Two} {Samples} of {Inpatients}? {A} {Simulation} {Study} to {Compare} {Type} {I} and {Type} {II} {Errors} of 12 {Statistical} {Tests}},
	volume = {20},
	copyright = {All rights reserved},
	issn = {1524-4733},
	shorttitle = {How to {Compare} the {Length} of {Stay} of {Two} {Samples} of {Inpatients}?},
	doi = {10.1016/j.jval.2017.02.009},
	abstract = {BACKGROUND: Although many researchers in the field of health economics and quality of care compare the length of stay (LOS) in two inpatient samples, they often fail to check whether the sample meets the assumptions made by their chosen statistical test. In fact, LOS data show a highly right-skewed, discrete distribution in which most of the observations are tied; this violates the assumptions of most statistical tests.
OBJECTIVES: To estimate the type I and type II errors associated with the application of 12 different statistical tests to a series of LOS samples.
METHODS: The LOS distribution was extracted from an exhaustive French national database of inpatient stays. The type I error was estimated using 19 sample sizes and 1,000,000 simulations per sample. The type II error was estimated in three alternative scenarios. For each test, the type I and type II errors were plotted as a function of the sample size.
RESULTS: Gamma regression with log link, the log rank test, median regression, Poisson regression, and Weibull survival analysis presented an unacceptably high type I error. In contrast, the Student standard t test, linear regression with log link, and the Cox models had an acceptable type I error but low power.
CONCLUSIONS: When comparing the LOS for two balanced inpatient samples, the Student t test with logarithmic or rank transformation, the Wilcoxon test, and the Kruskal-Wallis test are the only methods with an acceptable type I error and high power.},
	language = {eng},
	number = {7},
	journal = {Value in Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research},
	author = {Chazard, Emmanuel and Ficheur, Grégoire and Beuscart, Jean-Baptiste and Preda, Cristian},
	month = aug,
	year = {2017},
	pmid = {28712630},
	keywords = {Length of Stay, METHODOLOGY, Statistics, length of stay, methodology, outcome measurement, statistics},
	pages = {992--998},
}

BACKGROUND: Although many researchers in the field of health economics and quality of care compare the length of stay (LOS) in two inpatient samples, they often fail to check whether the sample meets the assumptions made by their chosen statistical test. In fact, LOS data show a highly right-skewed, discrete distribution in which most of the observations are tied; this violates the assumptions of most statistical tests. OBJECTIVES: To estimate the type I and type II errors associated with the application of 12 different statistical tests to a series of LOS samples. METHODS: The LOS distribution was extracted from an exhaustive French national database of inpatient stays. The type I error was estimated using 19 sample sizes and 1,000,000 simulations per sample. The type II error was estimated in three alternative scenarios. For each test, the type I and type II errors were plotted as a function of the sample size. RESULTS: Gamma regression with log link, the log rank test, median regression, Poisson regression, and Weibull survival analysis presented an unacceptably high type I error. In contrast, the Student standard t test, linear regression with log link, and the Cox models had an acceptable type I error but low power. CONCLUSIONS: When comparing the LOS for two balanced inpatient samples, the Student t test with logarithmic or rank transformation, the Wilcoxon test, and the Kruskal-Wallis test are the only methods with an acceptable type I error and high power.

@article{averlant_underuse_2017,
	title = {Underuse of {Oral} {Anticoagulants} and {Inappropriate} {Prescription} of {Antiplatelet} {Therapy} in {Older} {Inpatients} with {Atrial} {Fibrillation}},
	copyright = {All rights reserved},
	issn = {1179-1969},
	doi = {10.1007/s40266-017-0477-3},
	abstract = {BACKGROUND: Several studies have shown that the prescription of antiplatelet therapy (APT) is associated with an increased risk of oral anticoagulant (OAC) underuse in patients aged 75 years and over with atrial fibrillation (AF). An associated atheromatous disease may be the underlying reason for APT prescription. The objective of the study was to determine whether the association between underuse of OAC and APT prescription was explained by the presence of an atheromatous disease.
METHODS AND RESULTS: We performed a retrospective, observational, single-centre study between 2009 and 2013 based on administrative data. Patients aged 75 years and over with non-valvular AF were identified in a database of 72,090 hospital stays. Prescriptions of anti-thrombotic medications and their association with the presence of atheromatous disease were evaluated by the mean of a logistic regression. A total of 2034 hospital stays were included (mean age 84.3 ± 5.2 years). The overall prevalence of known atheromatous disease was 25.9\%. OAC underuse was observed in 58.5\% of the stays. In multivariable analysis, the prescription of an APT was associated with an increased risk of OAC underuse [odds ratio (OR) 6.85; 95\% confidence interval (CI) 5.50-8.58], independently of the presence of a concomitant known atheromatous disease (OR 0.78; 95\% CI 0.60-1.01). Among the 692 stays with APT monotherapy (34.0\%), 232 (33.5\%) displayed an atheromatous disease.
CONCLUSIONS: The underuse of OAC is associated with the prescription of APT in older patients with AF, regardless of the presence or absence of known atheromatous disease. Our results suggest that APT is often inappropriately prescribed instead of OAC.},
	language = {eng},
	journal = {Drugs \& Aging},
	author = {Averlant, Lorette and Ficheur, Grégoire and Ferret, Laurie and Boulé, Stéphane and Puisieux, François and Luyckx, Michel and Soula, Julien and Georges, Alexandre and Beuscart, Régis and Chazard, Emmanuel and Beuscart, Jean-Baptiste},
	month = jul,
	year = {2017},
	pmid = {28702928},
}

BACKGROUND: Several studies have shown that the prescription of antiplatelet therapy (APT) is associated with an increased risk of oral anticoagulant (OAC) underuse in patients aged 75 years and over with atrial fibrillation (AF). An associated atheromatous disease may be the underlying reason for APT prescription. The objective of the study was to determine whether the association between underuse of OAC and APT prescription was explained by the presence of an atheromatous disease. METHODS AND RESULTS: We performed a retrospective, observational, single-centre study between 2009 and 2013 based on administrative data. Patients aged 75 years and over with non-valvular AF were identified in a database of 72,090 hospital stays. Prescriptions of anti-thrombotic medications and their association with the presence of atheromatous disease were evaluated by the mean of a logistic regression. A total of 2034 hospital stays were included (mean age 84.3 ± 5.2 years). The overall prevalence of known atheromatous disease was 25.9%. OAC underuse was observed in 58.5% of the stays. In multivariable analysis, the prescription of an APT was associated with an increased risk of OAC underuse [odds ratio (OR) 6.85; 95% confidence interval (CI) 5.50-8.58], independently of the presence of a concomitant known atheromatous disease (OR 0.78; 95% CI 0.60-1.01). Among the 692 stays with APT monotherapy (34.0%), 232 (33.5%) displayed an atheromatous disease. CONCLUSIONS: The underuse of OAC is associated with the prescription of APT in older patients with AF, regardless of the presence or absence of known atheromatous disease. Our results suggest that APT is often inappropriately prescribed instead of OAC.

@article{caron_it-cares:_2017,
	title = {{IT}-{CARES}: an interactive tool for case-crossover analyses of electronic medical records for patient safety},
	volume = {24},
	issn = {1527-974X},
	shorttitle = {{IT}-{CARES}},
	doi = {10.1093/jamia/ocw132},
	abstract = {Background: The significant risk of adverse events following medical procedures supports a clinical epidemiological approach based on the analyses of collections of electronic medical records. Data analytical tools might help clinical epidemiologists develop more appropriate case-crossover designs for monitoring patient safety.
Objective: To develop and assess the methodological quality of an interactive tool for use by clinical epidemiologists to systematically design case-crossover analyses of large electronic medical records databases.
Material and Methods: We developed IT-CARES, an analytical tool implementing case-crossover design, to explore the association between exposures and outcomes. The exposures and outcomes are defined by clinical epidemiologists via lists of codes entered via a user interface screen. We tested IT-CARES on data from the French national inpatient stay database, which documents diagnoses and medical procedures for 170 million inpatient stays between 2007 and 2013. We compared the results of our analysis with reference data from the literature on thromboembolic risk after delivery and bleeding risk after total hip replacement.
Results: IT-CARES provides a user interface with 3 columns: (i) the outcome criteria in the left-hand column, (ii) the exposure criteria in the right-hand column, and (iii) the estimated risk (odds ratios, presented in both graphical and tabular formats) in the middle column. The estimated odds ratios were consistent with the reference literature data.
Discussion: IT-CARES may enhance patient safety by facilitating clinical epidemiological studies of adverse events following medical procedures. The tool's usability must be evaluated and improved in further research.},
	language = {eng},
	number = {2},
	journal = {Journal of the American Medical Informatics Association: JAMIA},
	author = {Caron, Alexandre and Chazard, Emmanuel and Muller, Joris and Perichon, Renaud and Ferret, Laurie and Koutkias, Vassilis and Beuscart, Régis and Beuscart, Jean-Baptiste and Ficheur, Grégoire},
	month = mar,
	year = {2017},
	pmid = {27678461},
	pmcid = {PMC5391728},
	keywords = {Cross-Over Studies, Databases, Factual, Electronic Health Records, Epidemiologic Methods, Hemorrhage, Humans, Medical Informatics, Patient Safety, Patient safety, Risk, Software, Thromboembolism, adverse event, big data, clinical epidemiology, data analytics, medical informatics},
	pages = {323--330},
}

Background: The significant risk of adverse events following medical procedures supports a clinical epidemiological approach based on the analyses of collections of electronic medical records. Data analytical tools might help clinical epidemiologists develop more appropriate case-crossover designs for monitoring patient safety. Objective: To develop and assess the methodological quality of an interactive tool for use by clinical epidemiologists to systematically design case-crossover analyses of large electronic medical records databases. Material and Methods: We developed IT-CARES, an analytical tool implementing case-crossover design, to explore the association between exposures and outcomes. The exposures and outcomes are defined by clinical epidemiologists via lists of codes entered via a user interface screen. We tested IT-CARES on data from the French national inpatient stay database, which documents diagnoses and medical procedures for 170 million inpatient stays between 2007 and 2013. We compared the results of our analysis with reference data from the literature on thromboembolic risk after delivery and bleeding risk after total hip replacement. Results: IT-CARES provides a user interface with 3 columns: (i) the outcome criteria in the left-hand column, (ii) the exposure criteria in the right-hand column, and (iii) the estimated risk (odds ratios, presented in both graphical and tabular formats) in the middle column. The estimated odds ratios were consistent with the reference literature data. Discussion: IT-CARES may enhance patient safety by facilitating clinical epidemiological studies of adverse events following medical procedures. The tool's usability must be evaluated and improved in further research.

@article{balcaen_validite_2017,
	series = {{XXXe} {Congrès} national Émois, {Nancy}, 23 et 24 mars 2017},
	title = {Validité de la mesure de l’incidence des cancers en {France} à partir de la base de données du {Programme} de médicalisation des systèmes d’information : revue systématique de la littérature de 2001 à 2015},
	volume = {65, Supplement 1},
	issn = {0398-7620},
	shorttitle = {Validité de la mesure de l’incidence des cancers en {France} à partir de la base de données du {Programme} de médicalisation des systèmes d’information},
	url = {http://www.sciencedirect.com/science/article/pii/S039876201730069X},
	doi = {10.1016/j.respe.2017.01.066},
	abstract = {Introduction
L’incidence des cancers est estimée à partir des données des registres des cancers qui couvrent environ 20 \% de la population. La base de données du Programme de médicalisation des systèmes d’information (PMSI) contient des données médico-administratives liées aux hospitalisations pour cancer. Le PMSI est potentiellement exploitable pour mesurer leur incidence. L’objectif de ce travail est de réaliser une revue systématique de la littérature sur l’utilisation de la base PMSI pour mesurer l’incidence des cancers en France.
Méthodes
=Une recherche bibliographique systématique, selon les recommandations PRISMA, a été faite à partir des thèmes « incidence », « cancer » et « pmsi ». Nous avons exploré plusieurs bases de données bibliographiques, dont Pubmed, Web of science, Springer Link, Science Direct. Nous avons retenu les articles qui comparaient la mesure de l’incidence des cancers à partir du PMSI à une mesure de référence. Les critères d’inclusion étaient : une année de production de la base PMSI postérieure à 2000, la nature du cancer (primitif uniquement) et des données issues de la base nationale du PMSI. Une synthèse qualitative des articles inclus a été réalisée.
Résultats
Sur 1428 références analysées, 12 études originales ont été retenues. L’année médiane de production des bases était 2004, une seule étude a analysé les bases postérieures à 2007. Les résultats des études montrent une fiabilité satisfaisante du PMSI, surtout pour les années de production les plus récentes.
Discussion/conclusion
Ceci est en faveur de l’exploitation des données PMSI dans un cadre de recherche épidémiologique destiné à documenter les incidences de cancers. Toutefois, il est important de prendre en compte les contraintes inhérentes à la production de ces données dans les analyses. Il sera nécessaire de compléter ce travail avec des données plus récentes afin de confirmer cette fiabilité. Le développement d’algorithmes utilisant l’ensemble des informations disponibles (les diagnostics, les actes et le croisement des données des différents séjours d’un même patient) améliorerait certainement la détection des cas.},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Balcaen, T. and Chazard, E. and Ganry, O. and Caillet, P.},
	month = mar,
	year = {2017},
	keywords = {Epidémiologie, PMSI, ésCancer},
	pages = {S28},
}

Introduction L’incidence des cancers est estimée à partir des données des registres des cancers qui couvrent environ 20 % de la population. La base de données du Programme de médicalisation des systèmes d’information (PMSI) contient des données médico-administratives liées aux hospitalisations pour cancer. Le PMSI est potentiellement exploitable pour mesurer leur incidence. L’objectif de ce travail est de réaliser une revue systématique de la littérature sur l’utilisation de la base PMSI pour mesurer l’incidence des cancers en France. Méthodes =Une recherche bibliographique systématique, selon les recommandations PRISMA, a été faite à partir des thèmes « incidence », « cancer » et « pmsi ». Nous avons exploré plusieurs bases de données bibliographiques, dont Pubmed, Web of science, Springer Link, Science Direct. Nous avons retenu les articles qui comparaient la mesure de l’incidence des cancers à partir du PMSI à une mesure de référence. Les critères d’inclusion étaient : une année de production de la base PMSI postérieure à 2000, la nature du cancer (primitif uniquement) et des données issues de la base nationale du PMSI. Une synthèse qualitative des articles inclus a été réalisée. Résultats Sur 1428 références analysées, 12 études originales ont été retenues. L’année médiane de production des bases était 2004, une seule étude a analysé les bases postérieures à 2007. Les résultats des études montrent une fiabilité satisfaisante du PMSI, surtout pour les années de production les plus récentes. Discussion/conclusion Ceci est en faveur de l’exploitation des données PMSI dans un cadre de recherche épidémiologique destiné à documenter les incidences de cancers. Toutefois, il est important de prendre en compte les contraintes inhérentes à la production de ces données dans les analyses. Il sera nécessaire de compléter ce travail avec des données plus récentes afin de confirmer cette fiabilité. Le développement d’algorithmes utilisant l’ensemble des informations disponibles (les diagnostics, les actes et le croisement des données des différents séjours d’un même patient) améliorerait certainement la détection des cas.

@article{martincic_chirurgie_2017,
	series = {{XXXe} {Congrès} national Émois, {Nancy}, 23 et 24 mars 2017},
	title = {La chirurgie bariatrique en {France} de 2008 à 2014 : triplement de l’activité et fort recul de l’anneau gastrique},
	volume = {65, Supplement 1},
	issn = {0398-7620},
	shorttitle = {La chirurgie bariatrique en {France} de 2008 à 2014},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762017300470},
	doi = {10.1016/j.respe.2017.01.044},
	abstract = {Introduction
La chirurgie de l’obésité augmente sans cesse en France. Les techniques chirurgicales évoluent. L’objectif est de décrire les patients et les interventions.
Méthodes
La base nationale du PMSI de 2008 à 2014 est analysée à l’aide du langage de programmation en statistiques R. Les séjours d’un même patient sont chaînés. Des analyses descriptives et multivariées sont réalisées (Cox, régressions logistiques et arbres de décision).
Résultats
Le nombre d’intervention passe de 17 659 en 2008 à 47 544 à 2014. Les interventions sont des sleeve gastrectomies (45,2 \%), des bypass gastriques (29,8 \%), des anneaux gastriques (23,0 \%) et des dérivations biliopancréatiques (0,81 \%) ; 66 \% sont réalisées en établissement lucratif (diminue, p = 0). Les patients sont pour 83 \% des femmes, l’âge moyen est de 40 ans L’IMC est compris entre 40 et 50 kg/m2 dans au moins 59,1 \% des cas, mais diminue régulièrement (p = 0). Les patients sont hospitalisés en médiane six journées consécutives. L’hospitalisation ambulatoire passe de 1 \% en 2008 à 3,4 \% en 2014 (p = 0), principalement dans le secteur lucratif (p = 0) et pour les anneaux gastriques (p = 0) ; 4,5 \% des patients passent en réanimation ou soins intensif, mais cette proportion diminue (p = 0) ; 98,2 \% rentrent directement à domicile. L’anneau gastrique passe de 55,4 \% en 2008 à 9,2 \% en 2014, tandis que la sleeve gastrectomie passe de 16,9 à 60,7 \%. En 2014, 25,7 \% des patients opérés en lucratif, âgés de moins de 30 ans et d’IMC \< 40 ont bénéficié d’un anneau, contre 8,3 \% chez les autres. En 2014, 41 \% des patients âgés de plus de 40 ans et diabétiques ont reçu une technique créant une malabsorption, contre 28,5 \% chez les autres. Les réhospitalisations sont fréquentes et se répartissent ainsi : complications mécaniques d’anneaux (27,1 \%), occlusions (22,6 \%), hernies ou éventrations (15,3 \%), fistules (12,7 \%), infections (9,6 \%), saignements (7,6 \%) et abdominoplasties (5,7 \%). La mortalité observée en court séjour est de 0,18 \% à 1 an et 0,55 \% à 5 ans.
Discussion/conclusion
L’accès direct aux bases nationales à l’aide d’outils d’analyse choisis par les chercheurs eux-mêmes est dans l’intérêt général.},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Martincic, C. and Balcaen, T. and Georges, A. and Baro, E. and Ficheur, G. and Chazard, E.},
	month = mar,
	year = {2017},
	keywords = {Base nationale du PMSI, big data, ésChirurgie bariatrique},
	pages = {S20},
}

Introduction La chirurgie de l’obésité augmente sans cesse en France. Les techniques chirurgicales évoluent. L’objectif est de décrire les patients et les interventions. Méthodes La base nationale du PMSI de 2008 à 2014 est analysée à l’aide du langage de programmation en statistiques R. Les séjours d’un même patient sont chaînés. Des analyses descriptives et multivariées sont réalisées (Cox, régressions logistiques et arbres de décision). Résultats Le nombre d’intervention passe de 17 659 en 2008 à 47 544 à 2014. Les interventions sont des sleeve gastrectomies (45,2 %), des bypass gastriques (29,8 %), des anneaux gastriques (23,0 %) et des dérivations biliopancréatiques (0,81 %) ; 66 % sont réalisées en établissement lucratif (diminue, p = 0). Les patients sont pour 83 % des femmes, l’âge moyen est de 40 ans L’IMC est compris entre 40 et 50 kg/m2 dans au moins 59,1 % des cas, mais diminue régulièrement (p = 0). Les patients sont hospitalisés en médiane six journées consécutives. L’hospitalisation ambulatoire passe de 1 % en 2008 à 3,4 % en 2014 (p = 0), principalement dans le secteur lucratif (p = 0) et pour les anneaux gastriques (p = 0) ; 4,5 % des patients passent en réanimation ou soins intensif, mais cette proportion diminue (p = 0) ; 98,2 % rentrent directement à domicile. L’anneau gastrique passe de 55,4 % en 2008 à 9,2 % en 2014, tandis que la sleeve gastrectomie passe de 16,9 à 60,7 %. En 2014, 25,7 % des patients opérés en lucratif, âgés de moins de 30 ans et d’IMC < 40 ont bénéficié d’un anneau, contre 8,3 % chez les autres. En 2014, 41 % des patients âgés de plus de 40 ans et diabétiques ont reçu une technique créant une malabsorption, contre 28,5 % chez les autres. Les réhospitalisations sont fréquentes et se répartissent ainsi : complications mécaniques d’anneaux (27,1 %), occlusions (22,6 %), hernies ou éventrations (15,3 %), fistules (12,7 %), infections (9,6 %), saignements (7,6 %) et abdominoplasties (5,7 %). La mortalité observée en court séjour est de 0,18 % à 1 an et 0,55 % à 5 ans. Discussion/conclusion L’accès direct aux bases nationales à l’aide d’outils d’analyse choisis par les chercheurs eux-mêmes est dans l’intérêt général.

@article{beuscart_co-prescriptions_2017,
	title = {Co-prescriptions of psychotropic drugs to older patients in a general hospital},
	volume = {8},
	issn = {1878-7649},
	url = {http://www.sciencedirect.com/science/article/pii/S1878764916301917},
	doi = {10.1016/j.eurger.2016.11.012},
	abstract = {Introduction
The prescription of psychotropic drugs to older patients in a hospital setting has not been extensively characterized. The objective was to describe the inappropriate co-prescriptions of psychotropic drugs in hospitalized patients aged 75 and over.
Methods
By analysing the medical database from 222-bed general hospital in France, we reviewed a total of 11,929 stays of at least 3 days by patients aged 75 and over. Prescriptions and co-prescriptions of psychotropic drugs were identified automatically. Anticholinergic drugs with sedative effects were considered as psychotropic drugs. An expert review was performed for stays with the co-prescription of three or more psychotropic drugs to identify inappropriate co-prescriptions.
Results
Administration of a psychotropic drug was identified in 5475 stays (45.9\% of the total number of stays), of which 1526 (12.8\% of the total) featured at least one co-prescription. Co-prescriptions of three or more psychotropic drugs for at least 3 days were identified in 374 stays (3.1\% of the total). Most of these co-prescriptions (n = 334; 89.2\%) were considered inappropriate because of the combination of at least two drugs from the same psychotropic class (n = 269), the absence of a clear indication for a psychotropic drug (n = 173) and a history of falls (n = 86). However, the co-prescriptions were maintained after hospital discharge in 77.4\% of cases.
Conclusion
The co-prescriptions of psychotropic drugs should be re-evaluated in older hospitalized patients.},
	number = {1},
	journal = {European Geriatric Medicine},
	author = {Beuscart, J. -B. and Ficheur, G. and Miqueu, M. and Luyckx, M. and Perichon, R. and Puisieux, F. and Beuscart, R. and Chazard, E. and Ferret, L.},
	month = feb,
	year = {2017},
	keywords = {Data reuse, Inappropriate prescribing, Psychotropic Drugs},
	pages = {84--89},
}

Introduction The prescription of psychotropic drugs to older patients in a hospital setting has not been extensively characterized. The objective was to describe the inappropriate co-prescriptions of psychotropic drugs in hospitalized patients aged 75 and over. Methods By analysing the medical database from 222-bed general hospital in France, we reviewed a total of 11,929 stays of at least 3 days by patients aged 75 and over. Prescriptions and co-prescriptions of psychotropic drugs were identified automatically. Anticholinergic drugs with sedative effects were considered as psychotropic drugs. An expert review was performed for stays with the co-prescription of three or more psychotropic drugs to identify inappropriate co-prescriptions. Results Administration of a psychotropic drug was identified in 5475 stays (45.9% of the total number of stays), of which 1526 (12.8% of the total) featured at least one co-prescription. Co-prescriptions of three or more psychotropic drugs for at least 3 days were identified in 374 stays (3.1% of the total). Most of these co-prescriptions (n = 334; 89.2%) were considered inappropriate because of the combination of at least two drugs from the same psychotropic class (n = 269), the absence of a clear indication for a psychotropic drug (n = 173) and a history of falls (n = 86). However, the co-prescriptions were maintained after hospital discharge in 77.4% of cases. Conclusion The co-prescriptions of psychotropic drugs should be re-evaluated in older hospitalized patients.

@article{ficheur_case-crossover_2017,
	title = {Case-crossover study to examine the change in postpartum risk of pulmonary embolism over time},
	volume = {17},
	issn = {1471-2393},
	doi = {10.1186/s12884-017-1283-y},
	abstract = {BACKGROUND: Although the current guidelines recommend anticoagulation up until 6 weeks after delivery in women at high risk of venous thromboembolism (VTE), the risk of VTE may extend beyond 6 weeks. Our objective was to estimate the risk of a pulmonary embolism in successive 2-week intervals during the postpartum period.
METHODS: In a population-based, case-crossover study, we analyzed the French national inpatient database from 2007 to 2013 (n = 5,517,680 singleton deliveries). Using ICD-10 codes, we identified women who were diagnosed with a postpartum pulmonary embolism between July 1st, 2008, and December 31st, 2013. Deliveries were identified during a case "period" immediately before the pulmonary embolism, and five different control periods one year before the pulmonary embolism. Using conditional logistic regression, Odds ratios (ORs) and 95\% confidential intervals (CIs) were estimated for ten successive 2-week intervals that preceded the diagnosis of pulmonary embolism.
RESULTS: We identified 167,103 cases with a pulmonary embolism during the inclusion period. After delivery, the risk of pulmonary embolism declined progressively over time, with an OR [95\%CI] of 17.2 [14.0-21.3] in postpartum weeks 1 to 2 and 1.9 [1.4-2.7] in postpartum weeks 11 to 12. The OR [95\%CI] in postpartum weeks 13 to 14 was 1.4 [0.9-2.0], and the OR did not fall significantly after postpartum week 14.
CONCLUSIONS: Our findings indicate that women are at risk of a pulmonary embolism up to 12 weeks after delivery. The shape of the risk curve suggests that the risk decreases exponentially over time. Future research is needed to establish whether the duration of postpartum anticoagulation should be extended beyond 6 weeks.},
	language = {eng},
	number = {1},
	journal = {BMC pregnancy and childbirth},
	author = {Ficheur, Grégoire and Caron, Alexandre and Beuscart, Jean-Baptiste and Ferret, Laurie and Jung, Yu-Jin and Garabedian, Charles and Beuscart, Régis and Chazard, Emmanuel},
	year = {2017},
	pmid = {28410584},
	pmcid = {PMC5391590},
	keywords = {Adult, Case-Control Studies, Female, France, Humans, Odds Ratio, Population Surveillance, Pregnancy, Pregnancy Complications, Cardiovascular, Puerperal Disorders, Pulmonary Embolism, Risk Factors, Young Adult},
	pages = {119},
}

BACKGROUND: Although the current guidelines recommend anticoagulation up until 6 weeks after delivery in women at high risk of venous thromboembolism (VTE), the risk of VTE may extend beyond 6 weeks. Our objective was to estimate the risk of a pulmonary embolism in successive 2-week intervals during the postpartum period. METHODS: In a population-based, case-crossover study, we analyzed the French national inpatient database from 2007 to 2013 (n = 5,517,680 singleton deliveries). Using ICD-10 codes, we identified women who were diagnosed with a postpartum pulmonary embolism between July 1st, 2008, and December 31st, 2013. Deliveries were identified during a case "period" immediately before the pulmonary embolism, and five different control periods one year before the pulmonary embolism. Using conditional logistic regression, Odds ratios (ORs) and 95% confidential intervals (CIs) were estimated for ten successive 2-week intervals that preceded the diagnosis of pulmonary embolism. RESULTS: We identified 167,103 cases with a pulmonary embolism during the inclusion period. After delivery, the risk of pulmonary embolism declined progressively over time, with an OR [95%CI] of 17.2 [14.0-21.3] in postpartum weeks 1 to 2 and 1.9 [1.4-2.7] in postpartum weeks 11 to 12. The OR [95%CI] in postpartum weeks 13 to 14 was 1.4 [0.9-2.0], and the OR did not fall significantly after postpartum week 14. CONCLUSIONS: Our findings indicate that women are at risk of a pulmonary embolism up to 12 weeks after delivery. The shape of the risk curve suggests that the risk decreases exponentially over time. Future research is needed to establish whether the duration of postpartum anticoagulation should be extended beyond 6 weeks.

@article{joly_success_2017,
	title = {Success rates in smoking cessation: {Psychological} preparation plays a critical role and interacts with other factors such as psychoactive substances},
	volume = {12},
	copyright = {All rights reserved},
	issn = {1932-6203},
	shorttitle = {Success rates in smoking cessation},
	url = {https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0184800&type=printable},
	doi = {10.1371/journal.pone.0184800},
	abstract = {INTRODUCTION: The aim of this study was to identify factors associated with the results of smoking cessation attempts.
METHODS: Data were collected in Clermont-Ferrand from a smoking cessation clinic between 1999 and 2009 (1,361 patients). Smoking cessation was considered a success when patients were abstinent 6 months after the beginning of cessation. Multivariate logistic regression was used to investigate the association between abstinence and different factors.
RESULTS: The significant factors were a history of depression (ORadjusted = 0.57, p = 0.003), state of depression at the initial consultation (ORa = 0.64, p = 0.005), other psychoactive substances (ORa = 0.52, p{\textless}0.0001), heart, lung and Ear-Nose-Throat diseases (ORa = 0.65, p = 0.005), age (ORa = 1.04, p{\textless}0.0001), the Richmond test (p{\textless}0.0001; when the patient's motivation went from insufficient to moderate, the frequency of abstinence was twice as high) and the Prochaska algorithm (p{\textless}0.0001; when the patient went from the 'pre-contemplation' to the 'contemplation' level, the frequency of success was four times higher). A high score in the Richmond test had a greater impact on success with increasing age (significant interaction: p = 0.01). In exclusive smokers, the contemplation level in the Prochaska algorithm was enough to obtain a satisfactory abstinence rate (65.5\%) whereas among consumers of other psychoactive substances, it was necessary to reach the preparation level in the Prochaska algorithm to achieve a success rate greater than 50\% (significant interaction: p = 0.02).
CONCLUSION: The psychological preparation of the smoker plays a critical role. The management of smoking cessation must be personalized, especially for consumers of other psychoactive substances and/or smokers with a history of depression.},
	language = {eng},
	number = {10},
	journal = {PloS One},
	author = {Joly, Bertrand and Perriot, Jean and d'Athis, Philippe and Chazard, Emmanuel and Brousse, Georges and Quantin, Catherine},
	year = {2017},
	pmid = {29020085},
	keywords = {Algorithms, Anxiety, Depression, Female, Heart, Humans, Male, Multivariate Analysis, Nicotine replacement therapy, Patients, Psychotropic Drugs, Smoking Cessation, Smoking habits, Smoking related disorders},
	pages = {e0184800},
}

INTRODUCTION: The aim of this study was to identify factors associated with the results of smoking cessation attempts. METHODS: Data were collected in Clermont-Ferrand from a smoking cessation clinic between 1999 and 2009 (1,361 patients). Smoking cessation was considered a success when patients were abstinent 6 months after the beginning of cessation. Multivariate logistic regression was used to investigate the association between abstinence and different factors. RESULTS: The significant factors were a history of depression (ORadjusted = 0.57, p = 0.003), state of depression at the initial consultation (ORa = 0.64, p = 0.005), other psychoactive substances (ORa = 0.52, p\textless0.0001), heart, lung and Ear-Nose-Throat diseases (ORa = 0.65, p = 0.005), age (ORa = 1.04, p\textless0.0001), the Richmond test (p\textless0.0001; when the patient's motivation went from insufficient to moderate, the frequency of abstinence was twice as high) and the Prochaska algorithm (p\textless0.0001; when the patient went from the 'pre-contemplation' to the 'contemplation' level, the frequency of success was four times higher). A high score in the Richmond test had a greater impact on success with increasing age (significant interaction: p = 0.01). In exclusive smokers, the contemplation level in the Prochaska algorithm was enough to obtain a satisfactory abstinence rate (65.5%) whereas among consumers of other psychoactive substances, it was necessary to reach the preparation level in the Prochaska algorithm to achieve a success rate greater than 50% (significant interaction: p = 0.02). CONCLUSION: The psychological preparation of the smoker plays a critical role. The management of smoking cessation must be personalized, especially for consumers of other psychoactive substances and/or smokers with a history of depression.

@article{ficheur_risks_2016,
	title = {The risks of pulmonary embolism and upper gastrointestinal bleeding beyond 35days after total hip replacement for coxarthrosis among middle-aged patients: {A} cross-over cohort},
	volume = {93},
	issn = {1096-0260},
	shorttitle = {The risks of pulmonary embolism and upper gastrointestinal bleeding beyond 35days after total hip replacement for coxarthrosis among middle-aged patients},
	doi = {10.1016/j.ypmed.2016.09.010},
	abstract = {Prophylactic anticoagulation is recommended up to 35days after total hip replacement (THR). Although several observational studies have assessed the incidence of thrombotic events or bleeding events after THR, the corresponding measures of association have never been studied concomitantly. Here, we evaluated the duration of the elevated risks (relative to the baseline risk) of both venous thromboembolic events and bleeding events after THR for coxarthrosis among middle-aged patients. This was a population-based, cross-over cohort study of data extracted from the French national inpatient database between 2007 and 2013. We included middle-aged patients (aged 45 to 69) having undergone THR for coxarthrosis. We compared the numbers of pulmonary embolisms (PEs) (respectively upper gastrointestinal bleedings (UGIBs)) following the THR with the numbers occurring during three unexposed periods one year later. This enabled us to estimate the odds ratio (OR) [95\% confidence interval (CI)] for each of six successive 35-day intervals. The study included 108,099 patients. The ORs for PE were respectively 12.4 (95\% CI, 8.6-17.8) (absolute risk difference rate per 100,000 (ARD/100,000)=130) and 5.0 (95\% CI, 3.4-7.4) (ARD/100,000=52) for the first two 35-day intervals, and the risk was close to 1 thereafter. The risk of UGIB fell quickly, with an OR of 6.5 (95\% CI, 4.6-9.1) (ARD/100,000=83) and 0.8 (95\% CI, 0.4-1.6) for the first two 35-day intervals, respectively. The majority of UGIBs occurred during the inpatient stay for THR. Among middle-aged patients, the risk of a PE remains elevated beyond 35days after THR for coxarthrosis, whereas the risk of a UGIB remains elevated for the first 35days only.},
	language = {eng},
	journal = {Preventive Medicine},
	author = {Ficheur, Grégoire and Caron, Alexandre and Beuscart, Jean-Baptiste and Ferret, Laurie and Putman, Sophie and Beuscart, Régis and Chazard, Emmanuel},
	month = dec,
	year = {2016},
	pmid = {27612575},
	keywords = {Arthroplasty, Replacement, Hip, Bleeding event, Cohort Studies, Cross-Over Studies, Female, Hemorrhage, Humans, Incidence, Male, Middle Aged, Osteoarthritis, Hip, Patient Safety, Patient safety, Postoperative Complications, Pulmonary Embolism, Risk Factors, Time Factors, Total hip arthroplasty, Total hip replacement, United States, Venous Thromboembolism, Venous thromboembolic event},
	pages = {121--127},
}

Prophylactic anticoagulation is recommended up to 35days after total hip replacement (THR). Although several observational studies have assessed the incidence of thrombotic events or bleeding events after THR, the corresponding measures of association have never been studied concomitantly. Here, we evaluated the duration of the elevated risks (relative to the baseline risk) of both venous thromboembolic events and bleeding events after THR for coxarthrosis among middle-aged patients. This was a population-based, cross-over cohort study of data extracted from the French national inpatient database between 2007 and 2013. We included middle-aged patients (aged 45 to 69) having undergone THR for coxarthrosis. We compared the numbers of pulmonary embolisms (PEs) (respectively upper gastrointestinal bleedings (UGIBs)) following the THR with the numbers occurring during three unexposed periods one year later. This enabled us to estimate the odds ratio (OR) [95% confidence interval (CI)] for each of six successive 35-day intervals. The study included 108,099 patients. The ORs for PE were respectively 12.4 (95% CI, 8.6-17.8) (absolute risk difference rate per 100,000 (ARD/100,000)=130) and 5.0 (95% CI, 3.4-7.4) (ARD/100,000=52) for the first two 35-day intervals, and the risk was close to 1 thereafter. The risk of UGIB fell quickly, with an OR of 6.5 (95% CI, 4.6-9.1) (ARD/100,000=83) and 0.8 (95% CI, 0.4-1.6) for the first two 35-day intervals, respectively. The majority of UGIBs occurred during the inpatient stay for THR. Among middle-aged patients, the risk of a PE remains elevated beyond 35days after THR for coxarthrosis, whereas the risk of a UGIB remains elevated for the first 35days only.

@article{petit_changes_2016,
	title = {Changes in drug management of {Alzheimer}'s disease in nursing homes: {Impact} of the media campaign against specific drugs for {Alzheimer}'s disease},
	copyright = {All rights reserved},
	issn = {0013-7006},
	shorttitle = {Changes in drug management of {Alzheimer}'s disease in nursing homes},
	doi = {10.1016/j.encep.2015.03.006},
	abstract = {CONTEXT: Alzheimer's disease is a common disease in nursing homes. Evolution is constantly negative and specific treatments, which are only symptomatic, are subject to controversy. In a context of media exposure, the Transparency Committee of the Haute Autorité de santé (HAS) downgraded their medical service in October 2011, seeing it as weak.
AIM: Assess the evolution of the consumption of specific treatments for Alzheimer's disease; assess changes in the quality of monitoring in specific consultation.
METHODS: This is a retrospective and descriptive study, cross-sectional in three times (T0 January 2011, T1 October 2011 and T2 June 2012), in 6 nursing homes of Lille and its surroundings.
RESULTS: In total, 262 residents with dementia and present at least once during the three times of the study were included. Their mean age was 85.8 years. Among them, 40 \% had Alzheimer's disease clearly identified. At T0, 76.7 \% of patients present who were supposed to receive a specific treatment of Alzheimer's disease were actually receiving such treatment, 73.6 \% at T1 and 71.6 \% at T2. After 17 months of observation, the discontinuation rate of anticholinesterase was 34 \%, 24 \% for anti-glutamate. The monitoring in specific consultations decreased slightly between the three stages.
CONCLUSION: Our work did not show major impact of the media campaign against specific drugs for Alzheimer's disease. There is however a trend towards a decrease of their consumption in people with dementia living in nursing homes with no obvious link between monitoring in specific consultation and specific prescription. This trend would ask to be confirmed by a study on a larger scale.},
	language = {FRE},
	journal = {L'Encephale},
	author = {Petit, A.-E. and Mangeard, H. and Chazard, E. and Puisieux, F.},
	month = mar,
	year = {2016},
	pmid = {27039155},
}

CONTEXT: Alzheimer's disease is a common disease in nursing homes. Evolution is constantly negative and specific treatments, which are only symptomatic, are subject to controversy. In a context of media exposure, the Transparency Committee of the Haute Autorité de santé (HAS) downgraded their medical service in October 2011, seeing it as weak. AIM: Assess the evolution of the consumption of specific treatments for Alzheimer's disease; assess changes in the quality of monitoring in specific consultation. METHODS: This is a retrospective and descriptive study, cross-sectional in three times (T0 January 2011, T1 October 2011 and T2 June 2012), in 6 nursing homes of Lille and its surroundings. RESULTS: In total, 262 residents with dementia and present at least once during the three times of the study were included. Their mean age was 85.8 years. Among them, 40 % had Alzheimer's disease clearly identified. At T0, 76.7 % of patients present who were supposed to receive a specific treatment of Alzheimer's disease were actually receiving such treatment, 73.6 % at T1 and 71.6 % at T2. After 17 months of observation, the discontinuation rate of anticholinesterase was 34 %, 24 % for anti-glutamate. The monitoring in specific consultations decreased slightly between the three stages. CONCLUSION: Our work did not show major impact of the media campaign against specific drugs for Alzheimer's disease. There is however a trend towards a decrease of their consumption in people with dementia living in nursing homes with no obvious link between monitoring in specific consultation and specific prescription. This trend would ask to be confirmed by a study on a larger scale.

@article{houyengah_departements_2016,
	series = {Colloque {Adelf}-{Emois} « {Système} d’information hospitalier et {Epidémiologie} »},
	title = {Les départements de l’information médicale, alerteurs dans le parcours des patients à risque à l’hôpital. {Expérience} des {CH} de {Valenciennes}, {Dunkerque} et {Romorantin}},
	volume = {64, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762016000717},
	doi = {10.1016/j.respe.2016.01.070},
	abstract = {Introduction
Face à la maladie, une bonne gestion du temps est un facteur protecteur. Les départements de l’information médicale (DIM) sont en capacité d’analyser des données hétérogènes et massives (big data) issues du cours normal du soin. Cette analyse (data reuse) peut contribuer à améliorer les soins en informant les soignants en temps réel 24/7.
Méthodes
Le système des vigilances est basé sur un principe de pots de peinture virtuels. Chaque peinture virtuelle est fabriquée pour un groupe de vigilants. Une peinture est versée sur un patient à l’occasion de déclencheurs. Lorsque le patient arrive dans une unité, change de chambre ou de lit, il laisse une trace. Au moment souhaité par le groupe référent de la peinture, une alerte reprenant toutes les traces est envoyée aux abonnés à la peinture. Il est, par ailleurs, possible en sélectionnant une unité fonctionnelle ou une période de retrouver par type de peinture les traces des patients. Ce système permet de mettre en place des précautions particulières sur les chambres éventuellement contaminées a posteriori ou de retrouver les patients qui sont passés dans ces lits ainsi que leurs voisins.
Résultats
Les utilisateurs ont en moyenne gagné :

– deux jours sur les hospitalisations (1000 euros d’économie) ;

– des soins de qualité précoces et ciblés.

Pour les patients dénutris suivis par les diététiciennes, on met en évidence un gain de deux jours et un suivi rapproché. Il apparaît déjà que dans plus de 50 \% des cas, les patients réadmis sont plus dénutris qu’au moment de leur sortie antérieure. L’outil permet également pour les patients BMR, BHRe et CONTACTS de juguler le risque dès l’entrée, cela 24/7.
Discussion/Conclusion
L’analyse de données massives à l’hôpital permet aux DIM dotés d’un entrepôt de données de faciliter les soins. Il est aujourd’hui possible d’identifier certains patients dès leur admission et d’alerter les différents acteurs afin d’orienter la prise en charge, ou simplement de gagner du temps et d’améliorer les chances du patient.},
	urldate = {2016-03-18},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Houyengah, F. and Kyndt, X. and Durand-Joly, I. and Blanckaert, K. and Janssoone, N. and Chazard, E.},
	month = mar,
	year = {2016},
	keywords = {Entrepôt de données, Vigilance, ésBig data \& data reuse},
	pages = {S22},
}

Introduction Face à la maladie, une bonne gestion du temps est un facteur protecteur. Les départements de l’information médicale (DIM) sont en capacité d’analyser des données hétérogènes et massives (big data) issues du cours normal du soin. Cette analyse (data reuse) peut contribuer à améliorer les soins en informant les soignants en temps réel 24/7. Méthodes Le système des vigilances est basé sur un principe de pots de peinture virtuels. Chaque peinture virtuelle est fabriquée pour un groupe de vigilants. Une peinture est versée sur un patient à l’occasion de déclencheurs. Lorsque le patient arrive dans une unité, change de chambre ou de lit, il laisse une trace. Au moment souhaité par le groupe référent de la peinture, une alerte reprenant toutes les traces est envoyée aux abonnés à la peinture. Il est, par ailleurs, possible en sélectionnant une unité fonctionnelle ou une période de retrouver par type de peinture les traces des patients. Ce système permet de mettre en place des précautions particulières sur les chambres éventuellement contaminées a posteriori ou de retrouver les patients qui sont passés dans ces lits ainsi que leurs voisins. Résultats Les utilisateurs ont en moyenne gagné : – deux jours sur les hospitalisations (1000 euros d’économie) ; – des soins de qualité précoces et ciblés. Pour les patients dénutris suivis par les diététiciennes, on met en évidence un gain de deux jours et un suivi rapproché. Il apparaît déjà que dans plus de 50 % des cas, les patients réadmis sont plus dénutris qu’au moment de leur sortie antérieure. L’outil permet également pour les patients BMR, BHRe et CONTACTS de juguler le risque dès l’entrée, cela 24/7. Discussion/Conclusion L’analyse de données massives à l’hôpital permet aux DIM dotés d’un entrepôt de données de faciliter les soins. Il est aujourd’hui possible d’identifier certains patients dès leur admission et d’alerter les différents acteurs afin d’orienter la prise en charge, ou simplement de gagner du temps et d’améliorer les chances du patient.

@article{chazard_comparer_2016,
	series = {Colloque {Adelf}-{Emois} « {Système} d’information hospitalier et {Epidémiologie} »},
	title = {Comparer la durée de séjour de deux groupes de patients : quel test choisir ? {Comparaison} des risques alpha et bêta de douze tests statistiques},
	volume = {64, Supplement 1},
	issn = {0398-7620},
	shorttitle = {Comparer la durée de séjour de deux groupes de patients},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762016000146},
	doi = {10.1016/j.respe.2016.01.013},
	abstract = {Introduction
De nombreuses études PMSI ou qualité des soins comparent la durée moyenne de séjour (DMS) de deux groupes de séjours. La distribution est pourtant particulière : discrète, nombreux ex-aequo sur les valeurs faibles et fortement asymétrique avec quelques valeurs extrêmement élevées. Elle est en théorie incompatible avec de nombreux tests statistiques, qui sont généralement réalisés sans vérifier ni les conditions de validité, ni l’impact sur le risque alpha (probabilité d’observer une différence significative à tort) et la puissance. L’objectif est de comparer, à l’aide de simulations, les risques alpha et bêta empiriques de 12 méthodes statistiques utilisables pour comparer deux DMS.
Méthodes
La loi de distribution de la durée de séjour (DS) est extraite de la base nationale du PMSI (ex-DGF, hors séances). Le risque alpha est estimé pour 16 tailles d’échantillons : deux échantillons sont tirés au sort, les 12 tests sont exécutés et les « p valeurs » sont stockées. Le processus est répété 1 000 000 fois. Le risque bêta (et donc la puissance) est estimé de manière similaire sous trois scénarios d’hypothèse alternative, avec 100 000 itérations.
Résultats
Certaines méthodes présentent une inflation inacceptable du risque alpha : la régression gamma avec un lien Log, le Log Rank, la régression quantile (médiane), la régression de Poisson et l’analyse de survie de Weibull. Certaines méthodes ont un risque alpha conservé mais une faible puissance : le test de Student, la régression linéaire avec un lien Log et le modèle de Cox. Les auteurs recommandent des méthodes dont le risque alpha est conservé et la puissance optimale : le test de Student sur les rangs ou avec transformation logarithmique, le test de Wilcoxon et le test de Kruskal-Wallis.
Discussion/conclusion
La méthode statistique doit donc être bien choisie ou, à défaut, ré-étalonnée par bootstrap. Le test de Student, le plus fréquemment utilisé, est peu puissant mais présent dans ce cas un risque alpha nettement inférieur à celui attendu.},
	urldate = {2016-03-18},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Preda, C. and Beuscart, R.},
	month = mar,
	year = {2016},
	keywords = {Erreurs des tests, Test statistique, ésDurée de séjour},
	pages = {S32--S33},
}

Introduction De nombreuses études PMSI ou qualité des soins comparent la durée moyenne de séjour (DMS) de deux groupes de séjours. La distribution est pourtant particulière : discrète, nombreux ex-aequo sur les valeurs faibles et fortement asymétrique avec quelques valeurs extrêmement élevées. Elle est en théorie incompatible avec de nombreux tests statistiques, qui sont généralement réalisés sans vérifier ni les conditions de validité, ni l’impact sur le risque alpha (probabilité d’observer une différence significative à tort) et la puissance. L’objectif est de comparer, à l’aide de simulations, les risques alpha et bêta empiriques de 12 méthodes statistiques utilisables pour comparer deux DMS. Méthodes La loi de distribution de la durée de séjour (DS) est extraite de la base nationale du PMSI (ex-DGF, hors séances). Le risque alpha est estimé pour 16 tailles d’échantillons : deux échantillons sont tirés au sort, les 12 tests sont exécutés et les « p valeurs » sont stockées. Le processus est répété 1 000 000 fois. Le risque bêta (et donc la puissance) est estimé de manière similaire sous trois scénarios d’hypothèse alternative, avec 100 000 itérations. Résultats Certaines méthodes présentent une inflation inacceptable du risque alpha : la régression gamma avec un lien Log, le Log Rank, la régression quantile (médiane), la régression de Poisson et l’analyse de survie de Weibull. Certaines méthodes ont un risque alpha conservé mais une faible puissance : le test de Student, la régression linéaire avec un lien Log et le modèle de Cox. Les auteurs recommandent des méthodes dont le risque alpha est conservé et la puissance optimale : le test de Student sur les rangs ou avec transformation logarithmique, le test de Wilcoxon et le test de Kruskal-Wallis. Discussion/conclusion La méthode statistique doit donc être bien choisie ou, à défaut, ré-étalonnée par bootstrap. Le test de Student, le plus fréquemment utilisé, est peu puissant mais présent dans ce cas un risque alpha nettement inférieur à celui attendu.

@article{chazard_risque_2016,
	series = {Colloque {Adelf}-{Emois} « {Système} d’information hospitalier et {Epidémiologie} »},
	title = {Risque hémorragique sous anti-vitamines {K} : quelles sont réellement les interactions prioritaires ?},
	volume = {64, Supplement 1},
	issn = {0398-7620},
	shorttitle = {Risque hémorragique sous anti-vitamines {K}},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762016000420},
	doi = {10.1016/j.respe.2016.01.041},
	abstract = {Introduction
Les anti-vitamine K (AVK) induisent de nombreux effets indésirables médicamenteux (EIM), hémorragiques ou thrombotiques. Afin de les prévenir, les logiciels de prescription connectée sont couplés à des systèmes d’aide à la décision (« Clinical Decision Support Systems » [CDSS]), qui émettent des alertes notamment en cas d’interaction médicamenteuse avec les AVK. Ces systèmes n’améliorent cependant pas la morbi-mortalité. À l’inverse, leurs alertes non-justifiées (« over-alerting ») interrompent les prescripteurs et leur apportent un sentiment injustifié de sécurité. Notre hypothèse est que, compte tenu des connaissances des médecins, le risque réel peut être différent du risque théorique, ce dont les CDSS devraient tenir compte. Notre objectif est de quantifier empiriquement ce risque d’EIM.
Méthodes
Cette étude utilise plus de 169 000 séjours hospitaliers, issus d’hôpitaux danois et français, incluant les données médico-administratives, les résultats de biologie et les médicaments administrés. Nous utilisons également une liste d’interactions avec les AVK, issue d’un article de référence (Holbrook et al.) rapportant une revue systématique de 181 articles scientifiques. Le surdosage en AVK est notamment recherché via la présence d’un INR supérieur à 4. Des modèles de Cox à variables dépendantes du temps et événements répétés sont itérativement construits.
Résultats
Au total, 3248 séjours comportaient un AVK, dont 5,2 \% [4,5;6] un surdosage et 5,8 \% [5;6,6] un sous-dosage. L’interaction des AVK avec 51 médicaments a pu être évaluée. Les médicaments suivants augmentent significativement le risque de surdosage en AVK : le fenofibrate (HR = 3,09 [1,34 ; 7,13]), la méthylprednisolone (HR = 3,02 [1,37 ; 6,68]) et la simvastatine (HR = 2,52 [1,36 ; 4,67]). La comparaison des résultats détaillés ne montre que peu de relations avec les niveaux de probabilité et de sévérité décrits par les experts dans la littérature.
Discussion/Conclusion
Ces résultats montrent l’importance du niveau de connaissance des médecins : lorsque des EIM sont décrits comme probables et sévères, les médecins en sont conscients et surveillent de près la survenue de l’EIM, et de fait, ce dernier ne survient pas. Les situations justifiant des alertes concerneraient donc des EIM décrits comme peu probables ou peu sévères.},
	urldate = {2016-03-18},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Ficheur, G. and Beuscart, R.},
	month = mar,
	year = {2016},
	keywords = {Analyses de survie, Réutilisation de données, ésEffets indésirables du médicament},
	pages = {S11--S12},
}

Introduction Les anti-vitamine K (AVK) induisent de nombreux effets indésirables médicamenteux (EIM), hémorragiques ou thrombotiques. Afin de les prévenir, les logiciels de prescription connectée sont couplés à des systèmes d’aide à la décision (« Clinical Decision Support Systems » [CDSS]), qui émettent des alertes notamment en cas d’interaction médicamenteuse avec les AVK. Ces systèmes n’améliorent cependant pas la morbi-mortalité. À l’inverse, leurs alertes non-justifiées (« over-alerting ») interrompent les prescripteurs et leur apportent un sentiment injustifié de sécurité. Notre hypothèse est que, compte tenu des connaissances des médecins, le risque réel peut être différent du risque théorique, ce dont les CDSS devraient tenir compte. Notre objectif est de quantifier empiriquement ce risque d’EIM. Méthodes Cette étude utilise plus de 169 000 séjours hospitaliers, issus d’hôpitaux danois et français, incluant les données médico-administratives, les résultats de biologie et les médicaments administrés. Nous utilisons également une liste d’interactions avec les AVK, issue d’un article de référence (Holbrook et al.) rapportant une revue systématique de 181 articles scientifiques. Le surdosage en AVK est notamment recherché via la présence d’un INR supérieur à 4. Des modèles de Cox à variables dépendantes du temps et événements répétés sont itérativement construits. Résultats Au total, 3248 séjours comportaient un AVK, dont 5,2 % [4,5;6] un surdosage et 5,8 % [5;6,6] un sous-dosage. L’interaction des AVK avec 51 médicaments a pu être évaluée. Les médicaments suivants augmentent significativement le risque de surdosage en AVK : le fenofibrate (HR = 3,09 [1,34 ; 7,13]), la méthylprednisolone (HR = 3,02 [1,37 ; 6,68]) et la simvastatine (HR = 2,52 [1,36 ; 4,67]). La comparaison des résultats détaillés ne montre que peu de relations avec les niveaux de probabilité et de sévérité décrits par les experts dans la littérature. Discussion/Conclusion Ces résultats montrent l’importance du niveau de connaissance des médecins : lorsque des EIM sont décrits comme probables et sévères, les médecins en sont conscients et surveillent de près la survenue de l’EIM, et de fait, ce dernier ne survient pas. Les situations justifiant des alertes concerneraient donc des EIM décrits comme peu probables ou peu sévères.

@article{rosier_personalized_2016,
	title = {Personalized and automated remote monitoring of atrial fibrillation},
	volume = {18},
	issn = {1532-2092},
	url = {https://hal-univ-rennes1.archives-ouvertes.fr/hal-01331019/document},
	doi = {10.1093/europace/euv234},
	abstract = {AIMS: Remote monitoring of cardiac implantable electronic devices is a growing standard; yet, remote follow-up and management of alerts represents a time-consuming task for physicians or trained staff. This study evaluates an automatic mechanism based on artificial intelligence tools to filter atrial fibrillation (AF) alerts based on their medical significance.
METHODS AND RESULTS: We evaluated this method on alerts for AF episodes that occurred in 60 pacemaker recipients. AKENATON prototype workflow includes two steps: natural language-processing algorithms abstract the patient health record to a digital version, then a knowledge-based algorithm based on an applied formal ontology allows to calculate the CHA2DS2-VASc score and evaluate the anticoagulation status of the patient. Each alert is then automatically classified by importance from low to critical, by mimicking medical reasoning. Final classification was compared with human expert analysis by two physicians. A total of 1783 alerts about AF episode {\textgreater}5 min in 60 patients were processed. A 1749 of 1783 alerts (98\%) were adequately classified and there were no underestimation of alert importance in the remaining 34 misclassified alerts.
CONCLUSION: This work demonstrates the ability of a pilot system to classify alerts and improves personalized remote monitoring of patients. In particular, our method allows integration of patient medical history with device alert notifications, which is useful both from medical and resource-management perspectives. The system was able to automatically classify the importance of 1783 AF alerts in 60 patients, which resulted in an 84\% reduction in notification workload, while preserving patient safety.},
	language = {eng},
	number = {3},
	journal = {Europace: European Pacing, Arrhythmias, and Cardiac Electrophysiology: Journal of the Working Groups on Cardiac Pacing, Arrhythmias, and Cardiac Cellular Electrophysiology of the European Society of Cardiology},
	author = {Rosier, Arnaud and Mabo, Philippe and Temal, Lynda and Van Hille, Pascal and Dameron, Olivier and Deléger, Louise and Grouin, Cyril and Zweigenbaum, Pierre and Jacques, Julie and Chazard, Emmanuel and Laporte, Laure and Henry, Christine and Burgun, Anita},
	month = mar,
	year = {2016},
	pmid = {26487670},
	keywords = {Action Potentials, Algorithms, Anticoagulants, Artificial Intelligence, Artificial intelligence, Atrial Fibrillation, Atrial fibrillation, Automation, Cardiac implantable electronic devices, Decision Support Systems, Decision Support Techniques, Decision support systems, Electrocardiography, France, Heart Conduction System, Heart Rate, Humans, Pacemaker, Artificial, Pilot Projects, Predictive Value of Tests, Remote monitoring, Reproducibility of Results, Retrospective Studies, Risk Assessment, Signal Processing, Computer-Assisted, Telemetry, Workflow, Workload},
	pages = {347--352},
}

AIMS: Remote monitoring of cardiac implantable electronic devices is a growing standard; yet, remote follow-up and management of alerts represents a time-consuming task for physicians or trained staff. This study evaluates an automatic mechanism based on artificial intelligence tools to filter atrial fibrillation (AF) alerts based on their medical significance. METHODS AND RESULTS: We evaluated this method on alerts for AF episodes that occurred in 60 pacemaker recipients. AKENATON prototype workflow includes two steps: natural language-processing algorithms abstract the patient health record to a digital version, then a knowledge-based algorithm based on an applied formal ontology allows to calculate the CHA2DS2-VASc score and evaluate the anticoagulation status of the patient. Each alert is then automatically classified by importance from low to critical, by mimicking medical reasoning. Final classification was compared with human expert analysis by two physicians. A total of 1783 alerts about AF episode \textgreater5 min in 60 patients were processed. A 1749 of 1783 alerts (98%) were adequately classified and there were no underestimation of alert importance in the remaining 34 misclassified alerts. CONCLUSION: This work demonstrates the ability of a pilot system to classify alerts and improves personalized remote monitoring of patients. In particular, our method allows integration of patient medical history with device alert notifications, which is useful both from medical and resource-management perspectives. The system was able to automatically classify the importance of 1783 AF alerts in 60 patients, which resulted in an 84% reduction in notification workload, while preserving patient safety.

@article{ferret_evaluation_2016,
	title = {Evaluation of a {Computer} {Application} for {Retrospective} {Detection} of {Vitamin} {K} {Antagonist} {Treatment} {Imbalance}},
	copyright = {All rights reserved},
	issn = {1549-8425},
	doi = {10.1097/PTS.0000000000000182},
	abstract = {OBJECTIVE: Management of vitamin K antagonists (VKAs) is difficult, and overdoses can have dramatic hemorrhagic consequences. The adverse drug event (ADE) scorecards is a tool intended for the detection and description of adverse drug reaction/ADE developed during a European computerized medical data processing project. It is used in a quality assurance process. Our objective was to evaluate the performance of the ADE scorecards in the detection of the contributing factors for VKA overdoses, among the cases where a VKA overdose is observed.
METHODS: Twenty-eight rules allow the detection of VKA treatment overdose related to drug or a clinical situation. They were applied on 14,748 electronic medical records from a community hospital. Among 582 records including a VKA prescription, 59 cases of VKA overdoses (international normalized ratio ≥ 5) during the hospital stay have been identified. The ADE scorecards detected 49 of them. We evaluated the positive predictive value and sensitivity of these rules, by an expert review of the cases.
RESULTS: The expert review confirmed the contribution of a detected risk factor to the VKA overdose in 11 cases. Therefore, the precision of the rules is 22.4\%. The sensitivity is 84.6\%. The risk factors were mainly infection and amiodarone introduction. The 4 cases of clinical injury related to a drug were properly designated by the rules.
CONCLUSIONS: Our study shows the great potential of the ADE scorecards for detecting cofactors of VKA overdoses and gives an argument to include complex rules in the knowledge bases used for the detection and identification of ADEs in large medical databases.},
	language = {ENG},
	journal = {Journal of Patient Safety},
	author = {Ferret, Laurie and Luyckx, Michel and Ficheur, Grégoire and Chazard, Emmanuel and Beuscart, Régis},
	month = jan,
	year = {2016},
	pmid = {27336190},
}

OBJECTIVE: Management of vitamin K antagonists (VKAs) is difficult, and overdoses can have dramatic hemorrhagic consequences. The adverse drug event (ADE) scorecards is a tool intended for the detection and description of adverse drug reaction/ADE developed during a European computerized medical data processing project. It is used in a quality assurance process. Our objective was to evaluate the performance of the ADE scorecards in the detection of the contributing factors for VKA overdoses, among the cases where a VKA overdose is observed. METHODS: Twenty-eight rules allow the detection of VKA treatment overdose related to drug or a clinical situation. They were applied on 14,748 electronic medical records from a community hospital. Among 582 records including a VKA prescription, 59 cases of VKA overdoses (international normalized ratio ≥ 5) during the hospital stay have been identified. The ADE scorecards detected 49 of them. We evaluated the positive predictive value and sensitivity of these rules, by an expert review of the cases. RESULTS: The expert review confirmed the contribution of a detected risk factor to the VKA overdose in 11 cases. Therefore, the precision of the rules is 22.4%. The sensitivity is 84.6%. The risk factors were mainly infection and amiodarone introduction. The 4 cases of clinical injury related to a drug were properly designated by the rules. CONCLUSIONS: Our study shows the great potential of the ADE scorecards for detecting cofactors of VKA overdoses and gives an argument to include complex rules in the knowledge bases used for the detection and identification of ADEs in large medical databases.

@article{ficheur_elderly_2016,
	title = {Elderly {Surgical} {Patients}: {Automated} {Computation} of {Healthcare} {Quality} {Indicators} by {Data} {Reuse} of {EHR}},
	volume = {221},
	issn = {0926-9630},
	shorttitle = {Elderly {Surgical} {Patients}},
	abstract = {The objective of the work is to implement and evaluate the automated computation of 9 healthcare quality indicators, by data reuse of electronic health records, in the field of elderly surgical patients.
METHODS: Data are extracted from EHR, including administrative data, ICD10 diagnoses, laboratory results, procedures, administered drugs, and free-text letters. The indicators are implemented by a medical data reuse specialist. The conformity rate is automatically computed (3.5 minutes for 15,000 inpatient stays and 9 indicators). A medical expert reviews 45 stays per indicator. The precision is the proportion of non-conform inpatient stays among the cases detected as non-conform by the algorithms.
RESULTS: the paper describes the implemented algorithms, the conformity rates and the precisions. Two indicators have a precision of 0\%, 3 indicators have a precision of 40 to 60\%, and four indicators have a precision from 80 to 100\% (for 2 of them, the conformity rate is lower than 2.5\%!). This demonstrates that automated quality screening is possible and enables to detect threatening situations. The implementation of the indicators requires special skills in medicine, medical information sciences, and algorithmics. Failures of precision are mainly due to defaults of information quality (missing codes), and could benefit from text analysis.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ficheur, Grégoire and Schaffar, Aurélien and Caron, Alexandre and Balcaen, Thibaut and Beuscart, Jean-Baptiste and Chazard, Emmanuel},
	year = {2016},
	pmid = {27071884},
	keywords = {Aged, Aged, 80 and over, Data Curation, Electronic Health Records, Female, France, General Surgery, Guideline Adherence, Hospitalization, Humans, Male, Natural Language Processing, Practice Guidelines as Topic, Quality Indicators, Health Care},
	pages = {92--96},
}

The objective of the work is to implement and evaluate the automated computation of 9 healthcare quality indicators, by data reuse of electronic health records, in the field of elderly surgical patients. METHODS: Data are extracted from EHR, including administrative data, ICD10 diagnoses, laboratory results, procedures, administered drugs, and free-text letters. The indicators are implemented by a medical data reuse specialist. The conformity rate is automatically computed (3.5 minutes for 15,000 inpatient stays and 9 indicators). A medical expert reviews 45 stays per indicator. The precision is the proportion of non-conform inpatient stays among the cases detected as non-conform by the algorithms. RESULTS: the paper describes the implemented algorithms, the conformity rates and the precisions. Two indicators have a precision of 0%, 3 indicators have a precision of 40 to 60%, and four indicators have a precision from 80 to 100% (for 2 of them, the conformity rate is lower than 2.5%!). This demonstrates that automated quality screening is possible and enables to detect threatening situations. The implementation of the indicators requires special skills in medicine, medical information sciences, and algorithmics. Failures of precision are mainly due to defaults of information quality (missing codes), and could benefit from text analysis.

@article{rosier_remote_2016,
	title = {Remote {Monitoring} of {Cardiac} {Implantable} {Devices}: {Ontology} {Driven} {Classification} of the {Alerts}},
	volume = {221},
	issn = {0926-9630},
	shorttitle = {Remote {Monitoring} of {Cardiac} {Implantable} {Devices}},
	abstract = {The number of patients that benefit from remote monitoring of cardiac implantable electronic devices, such as pacemakers and defibrillators, is growing rapidly. Consequently, the huge number of alerts that are generated and transmitted to the physicians represents a challenge to handle. We have developed a system based on a formal ontology that integrates the alert information and the patient data extracted from the electronic health record in order to better classify the importance of alerts. A pilot study was conducted on atrial fibrillation alerts. We show some examples of alert processing. The results suggest that this approach has the potential to significantly reduce the alert burden in telecardiology. The methods may be extended to other types of connected devices.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Rosier, Arnaud and Mabo, Philippe and Temal, Lynda and Van Hille, Pascal and Dameron, Olivier and Deleger, Louise and Grouin, Cyril and Zweigenbaum, Pierre and Jacques, Julie and Chazard, Emmanuel and Laporte, Laure and Henry, Christine and Burgun, Anita},
	year = {2016},
	pmid = {27071877},
	keywords = {Atrial Fibrillation, Biological Ontologies, Clinical Alarms, Decision Support Systems, Clinical, Defibrillators, Implantable, Diagnosis, Computer-Assisted, Electrocardiography, Ambulatory, Electronic Health Records, Humans, Natural Language Processing, Pacemaker, Artificial, Pilot Projects, Reproducibility of Results, Sensitivity and Specificity, Telemedicine, Therapy, Computer-Assisted},
	pages = {59--63},
}

The number of patients that benefit from remote monitoring of cardiac implantable electronic devices, such as pacemakers and defibrillators, is growing rapidly. Consequently, the huge number of alerts that are generated and transmitted to the physicians represents a challenge to handle. We have developed a system based on a formal ontology that integrates the alert information and the patient data extracted from the electronic health record in order to better classify the importance of alerts. A pilot study was conducted on atrial fibrillation alerts. We show some examples of alert processing. The results suggest that this approach has the potential to significantly reduce the alert burden in telecardiology. The methods may be extended to other types of connected devices.

@article{frely_impact_2015,
	title = {Impact of acute geriatric care in elderly patients according to the {Screening} {Tool} of {Older} {Persons}' {Prescriptions}/{Screening} {Tool} to {Alert} doctors to {Right} {Treatment} criteria in northern {France}},
	copyright = {All rights reserved},
	issn = {1447-0594},
	doi = {10.1111/ggi.12474},
	abstract = {INTRODUCTION: In France, over 20\% of hospitalizations of elderly people are a result of adverse drug events, of which 50\% are considered preventable. Tools have been developed to detect inappropriate prescriptions. The Screening Tool of Older Persons' Prescriptions/Screening Tool to Alert doctors to Right Treatment (STOPP/START) criteria are innovative and adapted to French prescriptions. This is one of the first French prospective studies to evaluate the impact of acute geriatric care on prescriptions at discharge in elderly patients using the STOPP/START criteria.
METHOD: The evaluation of prescriptions according to STOPP/START was carried out on admission and at discharge of patients in acute geriatric units at three hospitals in the Nord-Pas de Calais region, France. A total of 202 elderly hospitalized patients were included during the 4.5 months of the study (1.5 months per center).
RESULTS: The mean number of drugs was seven on admission and at discharge. Over half of the prescriptions at admission contained at least one potentially inappropriate medication or one potential prescription omission. The prescriptions at discharge contained significantly fewer potentially inappropriate medications than prescriptions on admission (P {\textless} 0.001). In contrast, there was no difference between prescriptions at discharge in terms of potential prescription omissions.
CONCLUSION: Acute geriatric hospitalization in France improves prescriptions in terms of potentially inappropriate medication, but has no impact on potential prescription omissions. Further studies must be carried out to see if STOPP/START could be used as a tool in French prescription. Geriatr Gerontol Int 2015; ●●: ●●-●●.},
	language = {ENG},
	journal = {Geriatrics \& Gerontology International},
	author = {Frély, Anne and Chazard, Emmanuel and Pansu, Aymeric and Beuscart, Jean-Baptiste and Puisieux, François},
	month = mar,
	year = {2015},
	pmid = {25809727},
}

INTRODUCTION: In France, over 20% of hospitalizations of elderly people are a result of adverse drug events, of which 50% are considered preventable. Tools have been developed to detect inappropriate prescriptions. The Screening Tool of Older Persons' Prescriptions/Screening Tool to Alert doctors to Right Treatment (STOPP/START) criteria are innovative and adapted to French prescriptions. This is one of the first French prospective studies to evaluate the impact of acute geriatric care on prescriptions at discharge in elderly patients using the STOPP/START criteria. METHOD: The evaluation of prescriptions according to STOPP/START was carried out on admission and at discharge of patients in acute geriatric units at three hospitals in the Nord-Pas de Calais region, France. A total of 202 elderly hospitalized patients were included during the 4.5 months of the study (1.5 months per center). RESULTS: The mean number of drugs was seven on admission and at discharge. Over half of the prescriptions at admission contained at least one potentially inappropriate medication or one potential prescription omission. The prescriptions at discharge contained significantly fewer potentially inappropriate medications than prescriptions on admission (P \textless 0.001). In contrast, there was no difference between prescriptions at discharge in terms of potential prescription omissions. CONCLUSION: Acute geriatric hospitalization in France improves prescriptions in terms of potentially inappropriate medication, but has no impact on potential prescription omissions. Further studies must be carried out to see if STOPP/START could be used as a tool in French prescription. Geriatr Gerontol Int 2015; ●●: ●●-●●.

@article{djennaoui_construction_2015,
	series = {{XXVIIIe} {Congrès} national Émois, {Nancy}, 26 et 27 mars 2015},
	title = {Construction et évaluation de règles de prédiction de diagnostics à partir des bases de données hospitalières : application au contrôle qualité des données médico-administratives},
	volume = {63, Supplement 1},
	issn = {0398-7620},
	shorttitle = {Construction et évaluation de règles de prédiction de diagnostics à partir des bases de données hospitalières},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762015000218},
	doi = {10.1016/j.respe.2015.01.020},
	abstract = {Introduction
Dans le cadre du « Programme de médicalisation du système d’information » (PMSI), l’instauration de la tarification à l’activité (T2A) a incité les établissements de santé à établir des procédures de contrôle optimisant la rémunération des séjours, le recodage de complications et morbidités associées (CMA) constituant une de ces procédures. Les méthodes de data mining suscitent beaucoup d’intérêt dans l’analyse des bases de données et produisent des règles prédictives simples d’application. Notre objectif était de produire par data mining à partir des données de la base nationale PMSI des règles de prédiction de CMA applicables au contrôle qualité des séjours.
Méthodes
Notre échantillon provenait de la base nationale PMSI pour les années 2007 à 2010. Les CMA prédites devaient être fréquentes et caractériser une pathologie chronique, la prédiction se basant sur les codes diagnostiques et d’actes. Les règles construites étaient de type séquentiel, avec pour seuils de support et de confiance 0,00075 et 0,5 respectivement. Les règles produites étaient sélectionnées selon leur confiance et leur support puis évaluées par une revue de cas réels à partir des courriers de sortie ; le pouvoir prédictif des règles était confronté au pouvoir prédictif des CMA seules et évalué par le calcul du lift (rapport de la valeur prédictive positive de la règle sur la valeur prédictive positive de la CMA seule).
Résultats
Notre échantillon comportait 59 170 séjours. Les CMA ciblées étaient les codes E11 « diabète sucré type 2 », I48 « fibrillation atriale » et I50 « insuffisance cardiaque ». Nous avons extrait six règles séquentielles et validé à l’issue de la procédure de contrôle (432 cas revus) trois règles prédictives ayant toutes un lift supérieur ou égal à 1,30 :

– \{E11,I10,DZQM006\} =\> \{E11\} ;

– \{E11,I10,I48\} =\> \{E11\} ;

– \{I48,I69\} =\> \{I48\}.
Discussion/conclusion
Notre étude a permis d’extraire à partir de la base nationale PMSI, par data mining, des règles de prédiction de CMA valides, fiables et simples d’application dans le cadre du contrôle qualité des séjours.},
	urldate = {2015-04-04},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Djennaoui, M. and Ficheur, G. and Aernout, E. and Beuscart, R. and Chazard, E.},
	month = mar,
	year = {2015},
	keywords = {Base nationale PMSI, Contrôle qualité T2A, Règles séquentielles},
	pages = {S11},
}

Introduction Dans le cadre du « Programme de médicalisation du système d’information » (PMSI), l’instauration de la tarification à l’activité (T2A) a incité les établissements de santé à établir des procédures de contrôle optimisant la rémunération des séjours, le recodage de complications et morbidités associées (CMA) constituant une de ces procédures. Les méthodes de data mining suscitent beaucoup d’intérêt dans l’analyse des bases de données et produisent des règles prédictives simples d’application. Notre objectif était de produire par data mining à partir des données de la base nationale PMSI des règles de prédiction de CMA applicables au contrôle qualité des séjours. Méthodes Notre échantillon provenait de la base nationale PMSI pour les années 2007 à 2010. Les CMA prédites devaient être fréquentes et caractériser une pathologie chronique, la prédiction se basant sur les codes diagnostiques et d’actes. Les règles construites étaient de type séquentiel, avec pour seuils de support et de confiance 0,00075 et 0,5 respectivement. Les règles produites étaient sélectionnées selon leur confiance et leur support puis évaluées par une revue de cas réels à partir des courriers de sortie ; le pouvoir prédictif des règles était confronté au pouvoir prédictif des CMA seules et évalué par le calcul du lift (rapport de la valeur prédictive positive de la règle sur la valeur prédictive positive de la CMA seule). Résultats Notre échantillon comportait 59 170 séjours. Les CMA ciblées étaient les codes E11 « diabète sucré type 2 », I48 « fibrillation atriale » et I50 « insuffisance cardiaque ». Nous avons extrait six règles séquentielles et validé à l’issue de la procédure de contrôle (432 cas revus) trois règles prédictives ayant toutes un lift supérieur ou égal à 1,30 : – \E11,I10,DZQM006\ => \E11\ ; – \E11,I10,I48\ => \E11\ ; – \I48,I69\ => \I48\. Discussion/conclusion Notre étude a permis d’extraire à partir de la base nationale PMSI, par data mining, des règles de prédiction de CMA valides, fiables et simples d’application dans le cadre du contrôle qualité des séjours.

@article{muller_reutilisation_2015,
	series = {{XXVIIIe} {Congrès} national Émois, {Nancy}, 26 et 27 mars 2015},
	title = {Réutilisation du fichier {FichComp} de la base nationale du {Programme} de médicalisation de systèmes d’information pour explorer les complications mécaniques des prothèses totales de hanche},
	volume = {63, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762015000309},
	doi = {10.1016/j.respe.2015.01.029},
	abstract = {Introduction
Le fichier Fichcomp de la base nationale du Programme de médicalisation de systèmes d’information (PMSI) permet de tracer certains dispositifs médicaux implantables (DMI) depuis 2008, incluant les prothèses totales de hanche (PTH). L’objectif de notre étude était d’évaluer le risque de réhospitalisation pour complication mécanique secondaire à la pose d’une PTH.
Méthodes
Le fichier Fichcomp de la base nationale du PMSI de 2008 à 2010 est réutilisé. Une cohorte rétrospective est constituée par l’inclusion de patients hospitalisés en 2008 dans le secteur ex-DGF pour la pose d’une PTH. Les codes de la liste des produits et prestations (LPP) sont regroupés de manière experte pour identifier trois types de PTH : métal sur métal, métal sur polyéthylène et céramique sur céramique. Ces séjours inclus sont chaînes grâce au numéro ANO avec les données PMSI MCO (ex-DGF et ex-OQN). L’événement recherché était une hospitalisation pour complication mécanique d’une prothèse à l’aide du code CIM-10 T84.0. Les patients étaient suivis pendant deux ans.
Résultats
Les 37 449 patients inclus avaient un âge moyen de 75 ans et 35,5 \% étaient des hommes. Nous avons observé 4,03 \% de réhospitalisations pour une complication mécanique de PTH dans les deux ans. Une première courbe de Kaplan–Meier représentait le risque de réhospitalisation au cours du temps en jours. Deux phases d’évolution du risque apparaissaient : une phase initiale rapide de deux mois puis une deuxième phase plus lente. Une seconde courbe stratifiée en fonction du type de prothèse montrait globalement un risque plus faible pour les prothèses de type métal sur polyéthylène. Les prothèses céramiques sur céramique présentaient un risque plus important la première année que pour le type métal sur métal, puis cette tendance s’inversait.
Discussion/conclusion
Le type de PTH influence le risque de réhospitalisation pour complication mécanique. Nos résultats sont comparables à ceux de cohortes spécifiques. L’algorithme permettant d’identifier les évènements pourrait inclure des codes d’actes. Sa sensibilité et sa spécificité devraient être évaluées. Le diamètre des prothèses qui est un facteur de risque connu et leur identification unique amélioreraient ce type d’étude.},
	urldate = {2015-04-04},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Muller, J. and Ficheur, G. and Ferreira Carreira, L. and Chazard, E. and Beuscart, R.},
	month = mar,
	year = {2015},
	keywords = {Base nationale PMSI, Prothèse totale de hanche, Réutilisation de données},
	pages = {S14--S15},
}

Introduction Le fichier Fichcomp de la base nationale du Programme de médicalisation de systèmes d’information (PMSI) permet de tracer certains dispositifs médicaux implantables (DMI) depuis 2008, incluant les prothèses totales de hanche (PTH). L’objectif de notre étude était d’évaluer le risque de réhospitalisation pour complication mécanique secondaire à la pose d’une PTH. Méthodes Le fichier Fichcomp de la base nationale du PMSI de 2008 à 2010 est réutilisé. Une cohorte rétrospective est constituée par l’inclusion de patients hospitalisés en 2008 dans le secteur ex-DGF pour la pose d’une PTH. Les codes de la liste des produits et prestations (LPP) sont regroupés de manière experte pour identifier trois types de PTH : métal sur métal, métal sur polyéthylène et céramique sur céramique. Ces séjours inclus sont chaînes grâce au numéro ANO avec les données PMSI MCO (ex-DGF et ex-OQN). L’événement recherché était une hospitalisation pour complication mécanique d’une prothèse à l’aide du code CIM-10 T84.0. Les patients étaient suivis pendant deux ans. Résultats Les 37 449 patients inclus avaient un âge moyen de 75 ans et 35,5 % étaient des hommes. Nous avons observé 4,03 % de réhospitalisations pour une complication mécanique de PTH dans les deux ans. Une première courbe de Kaplan–Meier représentait le risque de réhospitalisation au cours du temps en jours. Deux phases d’évolution du risque apparaissaient : une phase initiale rapide de deux mois puis une deuxième phase plus lente. Une seconde courbe stratifiée en fonction du type de prothèse montrait globalement un risque plus faible pour les prothèses de type métal sur polyéthylène. Les prothèses céramiques sur céramique présentaient un risque plus important la première année que pour le type métal sur métal, puis cette tendance s’inversait. Discussion/conclusion Le type de PTH influence le risque de réhospitalisation pour complication mécanique. Nos résultats sont comparables à ceux de cohortes spécifiques. L’algorithme permettant d’identifier les évènements pourrait inclure des codes d’actes. Sa sensibilité et sa spécificité devraient être évaluées. Le diamètre des prothèses qui est un facteur de risque connu et leur identification unique amélioreraient ce type d’étude.

@article{ficheur_epihosp_2015,
	series = {{XXVIIIe} {Congrès} national Émois, {Nancy}, 26 et 27 mars 2015},
	title = {{EpiHosp} : un outil web permettant l’exploration des poses de dispositifs médicaux implantables et de leurs complications par la réutilisation de la base nationale du {PMSI}},
	volume = {63, Supplement 1},
	issn = {0398-7620},
	shorttitle = {{EpiHosp}},
	url = {http://www.sciencedirect.com/science/article/pii/S039876201500019X},
	doi = {10.1016/j.respe.2015.01.018},
	abstract = {Introduction
Le groupe de travail « dispositifs médicaux » des assises du médicament a insisté en 2012 sur l’intérêt des données du Programme de médicalisation des systèmes d’information (PMSI) pour la surveillance des dispositifs médicaux implantables (DMI). L’objectif de ce travail est de construire un outil web réutilisant la base nationale du PMSI afin de permettre une analyse exploratoire des séjours des patients ayant eu une pose de DMI.
Méthodes
La base nationale du PMSI dans le secteur MCO pour les années 2008 à 2013 est réutilisée. Les DMI sont tracés dans le secteur ex-DGF par l’utilisation du fichier Fichcomp, les caractéristiques de ces séjours sont obtenues par l’exploitation du résumé de sortie anonymisé. Une éventuelle réhospitalisation et son motif (diagnostic principal du séjour ultérieur) est recherchée à l’aide du numéro ANO, dans les secteurs ex-DGF et ex-OQN. Les données sont prétraitées. Un outil web est développé en PHP, MySQL et Javacript.
Résultats
L’utilisateur choisit un DMI ou un groupe de DMI depuis l’arborescence de la liste des produits et prestations remboursables. La granularité de la requête correspond à l’année et au numéro FINESS. Le temps d’exécution de la requête la plus volumineuse comprenant l’ensemble des années, des numéros FINESS et des DMI est de quelques secondes. Trois résultats sont obtenus au niveau du séjour :

– une description temporelle, démographique et géographique incluant le lieu d’hospitalisation et de vie du patient ;

– une description des informations du séjour de pose ;

– un tableau présentant les motifs de réhospitalisation par fréquence décroissante. Enfin, les motifs de réhospitalisation d’intérêt peuvent être sélectionnés et une courbe de Kaplan–Meier présentant la probabilité de réhospitalisation est générée.
Discussion/conclusion
Ce travail démontre la faisabilité technique d’un outil web exploratoire et l’intérêt de la base nationale du PMSI pour le suivi des DMI. Les limites sont :

– la variabilité temporelle de la liste des DMI suivis dans Fichcomp ;

– l’absence d’identifiant unique pour chaque DMI posé ;

– le fait que chaque prothèse puisse être composée de plusieurs DMI distincts.},
	urldate = {2015-04-04},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Ficheur, G. and Ferreira Carreira, L. and Chazard, E. and Beuscart, R.},
	month = mar,
	year = {2015},
	keywords = {Base nationale du PMSI, Dispositif médical implantable, EpiHosp},
	pages = {S10},
}

Introduction Le groupe de travail « dispositifs médicaux » des assises du médicament a insisté en 2012 sur l’intérêt des données du Programme de médicalisation des systèmes d’information (PMSI) pour la surveillance des dispositifs médicaux implantables (DMI). L’objectif de ce travail est de construire un outil web réutilisant la base nationale du PMSI afin de permettre une analyse exploratoire des séjours des patients ayant eu une pose de DMI. Méthodes La base nationale du PMSI dans le secteur MCO pour les années 2008 à 2013 est réutilisée. Les DMI sont tracés dans le secteur ex-DGF par l’utilisation du fichier Fichcomp, les caractéristiques de ces séjours sont obtenues par l’exploitation du résumé de sortie anonymisé. Une éventuelle réhospitalisation et son motif (diagnostic principal du séjour ultérieur) est recherchée à l’aide du numéro ANO, dans les secteurs ex-DGF et ex-OQN. Les données sont prétraitées. Un outil web est développé en PHP, MySQL et Javacript. Résultats L’utilisateur choisit un DMI ou un groupe de DMI depuis l’arborescence de la liste des produits et prestations remboursables. La granularité de la requête correspond à l’année et au numéro FINESS. Le temps d’exécution de la requête la plus volumineuse comprenant l’ensemble des années, des numéros FINESS et des DMI est de quelques secondes. Trois résultats sont obtenus au niveau du séjour : – une description temporelle, démographique et géographique incluant le lieu d’hospitalisation et de vie du patient ; – une description des informations du séjour de pose ; – un tableau présentant les motifs de réhospitalisation par fréquence décroissante. Enfin, les motifs de réhospitalisation d’intérêt peuvent être sélectionnés et une courbe de Kaplan–Meier présentant la probabilité de réhospitalisation est générée. Discussion/conclusion Ce travail démontre la faisabilité technique d’un outil web exploratoire et l’intérêt de la base nationale du PMSI pour le suivi des DMI. Les limites sont : – la variabilité temporelle de la liste des DMI suivis dans Fichcomp ; – l’absence d’identifiant unique pour chaque DMI posé ; – le fait que chaque prothèse puisse être composée de plusieurs DMI distincts.

@article{caron_determination_2015,
	series = {{XXVIIIe} {Congrès} national Émois, {Nancy}, 26 et 27 mars 2015},
	title = {Détermination de l’exposition de 394 979 nouveau-nés par imputation multiple de données manquantes dans une étude épidémiologique},
	volume = {63, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762015000176},
	doi = {10.1016/j.respe.2015.01.016},
	abstract = {Introduction
L’utilisation de bases de données administratives à visée épidémiologique est limitée par l’existence de données manquantes. Nous avons étudié l’effet des perchlorates contenus dans l’eau sur la TSH (Thyroid Stimulating Hormone) des nouveau-nés. Nous disposions des données informatisées du dépistage néonatal systématique dosant la TSH. La commune de résidence de la mère permettait d’attribuer l’exposition au perchlorate mais était rarement saisie. L’objectif de ce travail était d’évaluer une méthode d’imputation de la commune de résidence permettant d’attribuer une exposition aux nouveau-nés.
Méthodes
La population d’étude était composée de l’ensemble des nouveau-nés dans le Nord Pas-de-Calais entre 2004 et 2012. Pour une maternité donnée, nous avons calculé la probabilité de résidence dans chacune des communes de son recrutement géographique à partir d’une extraction PMSI de l’ensemble des naissances de la période (GHM d’accouchement par voie basse ou césarienne). Le gold standard (GS) était établi pour l’année 2012 par saisie informatique systématique des communes de résidence. L’imputation multiple des données manquantes était réalisée par équations chaînées (MICE) pour les variables d’ajustement disponibles (\> 15 \% de manquantes) et par tirage au sort pondéré pour la commune de résidence. Le GS était comparé aux imputations à l’aide des odds ratios (OR) d’un modèle linéaire mixte. Ce modèle était ensuite réalisé sur l’ensemble des données.
Résultats
Les six OR obtenus par l’imputation sont similaires à ceux obtenus par imputation en 2012. Les statistiques de test (donc les intervalles de confiance) sont analogues : la plus grande variation est de l’ordre de 0,001 (OR = 1,047 [1,029–1,065] versus 1,042 [1,024–1,059]). Un OR non significatif change de polarité. Le modèle réalisé sur l’ensemble des naissances retrouve des coefficients comparables dont l’intervalle de confiance est plus précis.
Discussion/conclusion
Ce travail permet de valider notre méthode d’imputation multiple. L’utilisation de MICE permet d’obtenir des estimateurs non biaisés et dont la variance est préservée. Les résultats obtenus sur les 394 979 nouveau-nés appuient nos conclusions avec une taille d’échantillon dix fois supérieure.},
	urldate = {2015-04-04},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Caron, A. and Clément, G. and Heyman, C. and Aernout, E. and Chazard, E. and Le Tertre, A.},
	month = mar,
	year = {2015},
	keywords = {Bases administratives, Imputations multiples, Épidémiologie},
	pages = {S9},
}

Introduction L’utilisation de bases de données administratives à visée épidémiologique est limitée par l’existence de données manquantes. Nous avons étudié l’effet des perchlorates contenus dans l’eau sur la TSH (Thyroid Stimulating Hormone) des nouveau-nés. Nous disposions des données informatisées du dépistage néonatal systématique dosant la TSH. La commune de résidence de la mère permettait d’attribuer l’exposition au perchlorate mais était rarement saisie. L’objectif de ce travail était d’évaluer une méthode d’imputation de la commune de résidence permettant d’attribuer une exposition aux nouveau-nés. Méthodes La population d’étude était composée de l’ensemble des nouveau-nés dans le Nord Pas-de-Calais entre 2004 et 2012. Pour une maternité donnée, nous avons calculé la probabilité de résidence dans chacune des communes de son recrutement géographique à partir d’une extraction PMSI de l’ensemble des naissances de la période (GHM d’accouchement par voie basse ou césarienne). Le gold standard (GS) était établi pour l’année 2012 par saisie informatique systématique des communes de résidence. L’imputation multiple des données manquantes était réalisée par équations chaînées (MICE) pour les variables d’ajustement disponibles (> 15 % de manquantes) et par tirage au sort pondéré pour la commune de résidence. Le GS était comparé aux imputations à l’aide des odds ratios (OR) d’un modèle linéaire mixte. Ce modèle était ensuite réalisé sur l’ensemble des données. Résultats Les six OR obtenus par l’imputation sont similaires à ceux obtenus par imputation en 2012. Les statistiques de test (donc les intervalles de confiance) sont analogues : la plus grande variation est de l’ordre de 0,001 (OR = 1,047 [1,029–1,065] versus 1,042 [1,024–1,059]). Un OR non significatif change de polarité. Le modèle réalisé sur l’ensemble des naissances retrouve des coefficients comparables dont l’intervalle de confiance est plus précis. Discussion/conclusion Ce travail permet de valider notre méthode d’imputation multiple. L’utilisation de MICE permet d’obtenir des estimateurs non biaisés et dont la variance est préservée. Les résultats obtenus sur les 394 979 nouveau-nés appuient nos conclusions avec une taille d’échantillon dix fois supérieure.

@article{caron_original_2015,
	title = {An original imputation technique of missing data for assessing exposure of newborns to perchlorate in drinking water},
	volume = {210},
	issn = {0926-9630},
	abstract = {INTRODUCTION: Incompleteness of epidemiological databases is a major drawback when it comes to analyzing data. We conceived an epidemiological study to assess the association between newborn thyroid function and the exposure to perchlorates found in the tap water of the mother's home. Only 9\% of newborn's exposure to perchlorate was known. The aim of our study was to design, test and evaluate an original method for imputing perchlorate exposure of newborns based on their maternity of birth.
METHODS: In a first database, an exhaustive collection of newborn's thyroid function measured during a systematic neonatal screening was collected. In this database the municipality of residence of the newborn's mother was only available for 2012. Between 2004 and 2011, the closest data available was the municipality of the maternity of birth. Exposure was assessed using a second database which contained the perchlorate levels for each municipality. We computed the catchment area of every maternity ward based on the French nationwide exhaustive database of inpatient stay. Municipality, and consequently perchlorate exposure, was imputed by a weighted draw in the catchment area. Missing values for remaining covariates were imputed by chained equation. A linear mixture model was computed on each imputed dataset. We compared odds ratios (ORs) and 95\% confidence intervals (95\% CI) estimated on real versus imputed 2012 data. The same model was then carried out for the whole imputed database.
RESULTS: The ORs estimated on 36,695 observations by our multiple imputation method are comparable to the real 2012 data. On the 394,979 observations of the whole database, the ORs remain stable but the 95\% CI tighten considerably.
DISCUSSION: The model estimates computed on imputed data are similar to those calculated on real data. The main advantage of multiple imputation is to provide unbiased estimate of the ORs while maintaining their variances. Thus, our method will be used to increase the statistical power of future studies by including all 394,979 newborns.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Caron, Alexandre and Clement, Guillaume and Heyman, Christophe and Aernout, Eva and Chazard, Emmanuel and Le Tertre, Alain},
	year = {2015},
	pmid = {25991277},
	keywords = {Adolescent, Adult, Computer Simulation, Drinking Water, Environmental Exposure, Female, France, Humans, Infant, Newborn, Infant, Newborn, Diseases, Middle Aged, Models, Statistical, Perchlorates, Pregnancy, Prenatal Exposure Delayed Effects, Prevalence, Reproducibility of Results, Risk Assessment, Sample Size, Sensitivity and Specificity, Thyroid Diseases, Treatment Outcome, Water Pollutants, Chemical, Water Pollution, Chemical, Young Adult},
	pages = {860--864},
}

INTRODUCTION: Incompleteness of epidemiological databases is a major drawback when it comes to analyzing data. We conceived an epidemiological study to assess the association between newborn thyroid function and the exposure to perchlorates found in the tap water of the mother's home. Only 9% of newborn's exposure to perchlorate was known. The aim of our study was to design, test and evaluate an original method for imputing perchlorate exposure of newborns based on their maternity of birth. METHODS: In a first database, an exhaustive collection of newborn's thyroid function measured during a systematic neonatal screening was collected. In this database the municipality of residence of the newborn's mother was only available for 2012. Between 2004 and 2011, the closest data available was the municipality of the maternity of birth. Exposure was assessed using a second database which contained the perchlorate levels for each municipality. We computed the catchment area of every maternity ward based on the French nationwide exhaustive database of inpatient stay. Municipality, and consequently perchlorate exposure, was imputed by a weighted draw in the catchment area. Missing values for remaining covariates were imputed by chained equation. A linear mixture model was computed on each imputed dataset. We compared odds ratios (ORs) and 95% confidence intervals (95% CI) estimated on real versus imputed 2012 data. The same model was then carried out for the whole imputed database. RESULTS: The ORs estimated on 36,695 observations by our multiple imputation method are comparable to the real 2012 data. On the 394,979 observations of the whole database, the ORs remain stable but the 95% CI tighten considerably. DISCUSSION: The model estimates computed on imputed data are similar to those calculated on real data. The main advantage of multiple imputation is to provide unbiased estimate of the ORs while maintaining their variances. Thus, our method will be used to increase the statistical power of future studies by including all 394,979 newborns.

@article{chazard_process_2015,
	title = {Process assessment by automated computation of healthcare quality indicators in hospital electronic health records: a systematic review of indicators},
	volume = {210},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {Process assessment by automated computation of healthcare quality indicators in hospital electronic health records},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2015_mie_automatedprocessindicatorcomputation.pdf},
	abstract = {The objective of the work is to extract healthcare process quality indicators from the literature, and to evaluate which of them could be automatically computed using routinely collected data from electronic health records (EHRs). A minimal set of data commonly available in EHRs is first defined. The initial bibliographic query enables to identify 8,744 papers, among which 126 papers describe 440 process indicators. 22.3\% of indicators can be automatically computed. The computation of the indicators mostly require diagnoses (99\%), drug prescriptions (59\%), medical procedures (48\%), administrative data (30\%), laboratory results (20\%), free-text reports with basic keyword research (19\%), linkage with the patient's previous stays (11\%) and dependence assessment (3\%). 77.7\% of indicators cannot be automatically computed, mostly because they require a linkage with outpatient data (61\%), structured data that are usually not available (43\%), unstructured data (26\%) or the trace of an information that was given to the patient (8\%).},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Chazard, Emmanuel and Babaousmail, Djaber and Schaffar, Aurélien and Ficheur, Grégoire and Beuscart, Régis},
	year = {2015},
	pmid = {25991279},
	pages = {867--871},
}

The objective of the work is to extract healthcare process quality indicators from the literature, and to evaluate which of them could be automatically computed using routinely collected data from electronic health records (EHRs). A minimal set of data commonly available in EHRs is first defined. The initial bibliographic query enables to identify 8,744 papers, among which 126 papers describe 440 process indicators. 22.3% of indicators can be automatically computed. The computation of the indicators mostly require diagnoses (99%), drug prescriptions (59%), medical procedures (48%), administrative data (30%), laboratory results (20%), free-text reports with basic keyword research (19%), linkage with the patient's previous stays (11%) and dependence assessment (3%). 77.7% of indicators cannot be automatically computed, mostly because they require a linkage with outpatient data (61%), structured data that are usually not available (43%), unstructured data (26%) or the trace of an information that was given to the patient (8%).

@article{ficheur_epihosp:_2015,
	title = {{EpiHosp}: {A} web-based visualization tool enabling the exploratory analysis of complications of implantable medical devices from a nationwide hospital database},
	volume = {210},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {{EpiHosp}},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2015_mie_epihosp.pdf},
	abstract = {Administrative data can be used for the surveillance of the outcomes of implantable medical devices (IMDs). The objective of this work is to build a web-based tool allowing for an exploratory analysis of time-dependent events that may occur after the implementation of an IMD. This tool should enable a pharmacoepidemiologist to explore on the fly the relationship between a given IMD and a potential outcome. This tool mine the French nationwide database of inpatient stays from 2008 to 2013. The data are preprocessed in order to optimize the queries. A web tool is developed in PHP, MySQL and Javascript. The user selects one or a group of IMD from a tree, and can filter the results using years and hospital names. Four result pages describe the selected inpatient stays: (1) temporal and demographic description, (2) a description of the geographical location of the hospital, (3) a description of the geographical place of residence of the patient and (4) a table showing the rehospitalization reasons by decreasing order of frequency. Then, the user can select one readmission reason and display dynamically the probability of readmission by mean of a Kaplan-Meier curve with confidence intervals. This tool enables to dynamically monitor the occurrence of time-dependent complications of IMD.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ficheur, Grégoire and Ferreira Careira, Lionel and Beuscart, Régis and Chazard, Emmanuel},
	year = {2015},
	pmid = {25991176},
	pages = {409--413},
}

Administrative data can be used for the surveillance of the outcomes of implantable medical devices (IMDs). The objective of this work is to build a web-based tool allowing for an exploratory analysis of time-dependent events that may occur after the implementation of an IMD. This tool should enable a pharmacoepidemiologist to explore on the fly the relationship between a given IMD and a potential outcome. This tool mine the French nationwide database of inpatient stays from 2008 to 2013. The data are preprocessed in order to optimize the queries. A web tool is developed in PHP, MySQL and Javascript. The user selects one or a group of IMD from a tree, and can filter the results using years and hospital names. Four result pages describe the selected inpatient stays: (1) temporal and demographic description, (2) a description of the geographical location of the hospital, (3) a description of the geographical place of residence of the patient and (4) a table showing the rehospitalization reasons by decreasing order of frequency. Then, the user can select one readmission reason and display dynamically the probability of readmission by mean of a Kaplan-Meier curve with confidence intervals. This tool enables to dynamically monitor the occurrence of time-dependent complications of IMD.

@article{baro_toward_2015,
	title = {Toward a {Literature}-{Driven} {Definition} of {Big} {Data} in {Healthcare}},
	volume = {2015},
	copyright = {All rights reserved},
	issn = {2314-6133},
	url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4468280/},
	doi = {10.1155/2015/639021},
	abstract = {Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.},
	urldate = {2016-08-09},
	journal = {BioMed Research International},
	author = {Baro, Emilie and Degoul, Samuel and Beuscart, Régis and Chazard, Emmanuel},
	year = {2015},
}

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.

@article{perichon_patients_2015,
	title = {Patients drug exchange forum corpus: toward drug safety signals detection},
	volume = {210},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {Patients drug exchange forum corpus},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Perichon, Renaud and Chazard, Emmanuel and Beuscart, Régis},
	year = {2015},
	pmid = {25991358},
	pages = {1023},
}

@article{ferret_evaluation_2015,
	title = {Evaluation of compliance with recommendations of prevention of thromboembolism in atrial fibrillation in the elderly, by data reuse of electronic health records},
	volume = {210},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2015_mie_preventionthromboembolismfa.pdf},
	abstract = {Under-prescription of anticoagulants in the elderly with atrial fibrillation (AF) has been described in several studies, showing that only 15 to 44\% of them receive anticoagulants. However, the European Society of Cardiology recommendations state that anticoagulants should be systematically prescribed. In case of refusal of the treatment by the patient, a platelet aggregation inhibitor should be prescribed in monotherapy or bitherapy according to the HAS-BLED bleeding risk score. In all the cases the patient should receive an antithrombotic treatment. In this work we observe the adequacy of prescription practices to the recommendations for AF in the elderly by data reuse on a monocentric observational retrospective cohort. Data of a 222 beds French community hospital were extracted for the year 2013. The patients aged over 75 years and presenting AF were selected. The HAS-BLED score was calculated and the consistency of the prescriptions with the recommendations of the European Society of Cardiology was verified. Then the compliance rate to the recommendations was calculated. The rules detected 433 patients with AF and aged over 75 years. From those patients, 45\% received an anticoagulant, 32.1\% received platelet aggregation inhibitors and 22.9\% did not receive any antithrombotic treatment. When a platelet aggregation inhibitor was prescribed the recommendation for bitherapy was not followed in 97\% of the cases. The compliance rate to the recommendations was 47.8\%. This work highlights a major problem of quality of the prescriptions in the hospital field and shows how data reuse can help describing this type of issues.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ferret, Laurie and Beuscart, Jean-Baptiste and Ficheur, Grégoire and Beuscart, Régis and Luyckx, Michel and Chazard, Emmanuel},
	year = {2015},
	pmid = {25991173},
	pages = {394--398},
}

Under-prescription of anticoagulants in the elderly with atrial fibrillation (AF) has been described in several studies, showing that only 15 to 44% of them receive anticoagulants. However, the European Society of Cardiology recommendations state that anticoagulants should be systematically prescribed. In case of refusal of the treatment by the patient, a platelet aggregation inhibitor should be prescribed in monotherapy or bitherapy according to the HAS-BLED bleeding risk score. In all the cases the patient should receive an antithrombotic treatment. In this work we observe the adequacy of prescription practices to the recommendations for AF in the elderly by data reuse on a monocentric observational retrospective cohort. Data of a 222 beds French community hospital were extracted for the year 2013. The patients aged over 75 years and presenting AF were selected. The HAS-BLED score was calculated and the consistency of the prescriptions with the recommendations of the European Society of Cardiology was verified. Then the compliance rate to the recommendations was calculated. The rules detected 433 patients with AF and aged over 75 years. From those patients, 45% received an anticoagulant, 32.1% received platelet aggregation inhibitors and 22.9% did not receive any antithrombotic treatment. When a platelet aggregation inhibitor was prescribed the recommendation for bitherapy was not followed in 97% of the cases. The compliance rate to the recommendations was 47.8%. This work highlights a major problem of quality of the prescriptions in the hospital field and shows how data reuse can help describing this type of issues.

@article{chazard_how_2015,
	title = {How much does hyperkalemia lengthen inpatient stays? {About} methodological issues in analyzing time-dependant events},
	volume = {210},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {How much does hyperkalemia lengthen inpatient stays?},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2015_mie_timedependentevents.pdf},
	abstract = {Adverse events may increase the hospital length of stay (LOS). As a consequence, computing the mean difference of LOS between two inpatient groups, with or without event, is a convenient way to evaluate their severity. Conversely, some adverse events are time-dependent: this leads to overestimate the consequences of the adverse event when statistical tests are performed. In this paper, we interest on hyperkalemia in the inpatient database of a community hospital (2\% of the inpatient stays). The cumulated risk of hyperkalemia appears to be a linear function of the LOS. We compute the LOS difference associated with hyperkalemia by using 17 statistical methods. The raw LOS difference is 8.8 days, but the simulation finds a difference of 2.3 days, while the regressions (with linear or log link, with or without pairing, with or without propensity score) find a difference of 4.4 to 4.6 days. The characteristics of the methods are discussed, but it is not possible to know which one is true. However the raw difference seems to overestimate the truth. This methodological bias is quite frequent and is a challenge in public health, as it participates in false knowledge discovery, which could lead decision makers to focus on wrong issues and make wrong decisions.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Chazard, Emmanuel and Dumesnil, Choé and Beuscart, Régis},
	year = {2015},
	pmid = {25991272},
	pages = {835--839},
}

Adverse events may increase the hospital length of stay (LOS). As a consequence, computing the mean difference of LOS between two inpatient groups, with or without event, is a convenient way to evaluate their severity. Conversely, some adverse events are time-dependent: this leads to overestimate the consequences of the adverse event when statistical tests are performed. In this paper, we interest on hyperkalemia in the inpatient database of a community hospital (2% of the inpatient stays). The cumulated risk of hyperkalemia appears to be a linear function of the LOS. We compute the LOS difference associated with hyperkalemia by using 17 statistical methods. The raw LOS difference is 8.8 days, but the simulation finds a difference of 2.3 days, while the regressions (with linear or log link, with or without pairing, with or without propensity score) find a difference of 4.4 to 4.6 days. The characteristics of the methods are discussed, but it is not possible to know which one is true. However the raw difference seems to overestimate the truth. This methodological bias is quite frequent and is a challenge in public health, as it participates in false knowledge discovery, which could lead decision makers to focus on wrong issues and make wrong decisions.

@article{djennaoui_improvement_2015,
	title = {Improvement of the quality of medical databases: data-mining-based prediction of diagnostic codes from previous patient codes},
	volume = {210},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {Improvement of the quality of medical databases},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2015_mie_dmbasedpredictionoficd10codes.pdf},
	abstract = {INTRODUCTION: Diagnoses and medical procedures collected under the French system of information are recorded in a nationwide database, the "PMSI national database", which is accessible for exploitation. Quality of the data in this database is directly related to the quality of coding, which can be of poor quality. Among the proposed methods for the exploitation of health databases, data mining techniques are particularly interesting. Our objective is to build sequential rules for missing diagnoses prediction by data mining of the PMSI national database.
METHOD: Our working sample was constructed from the national database for years 2007 to 2010. The information retained for rules construction were medical diagnoses and medical procedures. The rules were selected using a statistical filter, and selected rules were validated by case review based on medical letters, which enabled to estimate the improvement of diagnoses recoding.
RESULTS: The work sample was made of 59,170 inpatient stays. The predicted ICD codes were E11 (non-insulin-dependent diabetes mellitus), I48 (atrial fibrillation and flutter) and I50 (heart failure).We validated three sequential rules with a substantial improvement of positive predictive value: \{E11,I10,DZQM006\}=\>\{E11\} \{E11,I10,I48\}=\>\{E11\} \{I48,I69\}=\>\{I48\} Discussion. We were able to extract by data mining three simple, reliable and effective sequential rules, with a substantial improvement in diagnoses recoding. The results of our study indicate the opportunity to improve the data quality of the national database by data mining methods.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Djennaoui, Mehdi and Ficheur, Grégoire and Beuscart, Régis and Chazard, Emmanuel},
	year = {2015},
	pmid = {25991178},
	pages = {419--423},
}

INTRODUCTION: Diagnoses and medical procedures collected under the French system of information are recorded in a nationwide database, the "PMSI national database", which is accessible for exploitation. Quality of the data in this database is directly related to the quality of coding, which can be of poor quality. Among the proposed methods for the exploitation of health databases, data mining techniques are particularly interesting. Our objective is to build sequential rules for missing diagnoses prediction by data mining of the PMSI national database. METHOD: Our working sample was constructed from the national database for years 2007 to 2010. The information retained for rules construction were medical diagnoses and medical procedures. The rules were selected using a statistical filter, and selected rules were validated by case review based on medical letters, which enabled to estimate the improvement of diagnoses recoding. RESULTS: The work sample was made of 59,170 inpatient stays. The predicted ICD codes were E11 (non-insulin-dependent diabetes mellitus), I48 (atrial fibrillation and flutter) and I50 (heart failure).We validated three sequential rules with a substantial improvement of positive predictive value: \E11,I10,DZQM006\=>\E11\ \E11,I10,I48\=>\E11\ \I48,I69\=>\I48\ Discussion. We were able to extract by data mining three simple, reliable and effective sequential rules, with a substantial improvement in diagnoses recoding. The results of our study indicate the opportunity to improve the data quality of the national database by data mining methods.

@article{chazard_one_2015,
	title = {One {Million} {Electrocardiograms} of {Primary} {Care} {Patients}: {A} {Descriptive} {Analysis}},
	volume = {216},
	issn = {0926-9630},
	shorttitle = {One {Million} {Electrocardiograms} of {Primary} {Care} {Patients}},
	abstract = {In 722 cities of Minas Gerais (Brazil), primary care patients can have their ECGs remotely interpreted by cardiologists of the Telehealth Network of Minas Gerais (TNMG), a public telehealth service. As of December 2014, more than 1.9 million ECGs were interpreted. This study analyzed the database of all ECGs performed by the TNMG on primary care patients from 2009 to 2013 (n=1,101,993). Structured patient data and the results of automated ECG interpretation by the Glasgow Program are described. Mean patient age is 51 years old, 59\% of them are women. The average body mass index is 25.9 kg/m2, with an average increase of 0.15 kg/m2 per civil year. Those patients notably have hypertension (33.2\%), family history of coronary artery disease (14.5\%), smoking (6.9\%), diabetes (5.8\%), obesity (5.8\%) or Chagas Disease (3.0\%). Seventy percent of ECGs are normal. This percentage is higher in women (72.3\%) and decreases in average by 7.4 every 10 years of life. There are notably 12\% of possible myocardial infarction, 10\% of possible left ventricular hypertrophy and 8\% of possible supraventricular extra systole.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Chazard, Emmanuel and Marcolino, Milena Soriano and Dumesnil, Chloé and Caron, Alexandre and Palhares, Daniel Moore F. and Ficheur, Grégoire and Marino, Barbara C. A. and Alkmim, Maria Beatriz M. and Beuscart, Régis and Ribeiro, Antonio Luiz},
	year = {2015},
	pmid = {26262012},
	keywords = {Brazil, Data Mining, Databases, Factual, Electrocardiography, Electronic Health Records, Female, Heart Diseases, Humans, Male, Middle Aged, Prevalence, Primary Health Care, Remote Consultation, Risk Assessment},
	pages = {69--73},
}

In 722 cities of Minas Gerais (Brazil), primary care patients can have their ECGs remotely interpreted by cardiologists of the Telehealth Network of Minas Gerais (TNMG), a public telehealth service. As of December 2014, more than 1.9 million ECGs were interpreted. This study analyzed the database of all ECGs performed by the TNMG on primary care patients from 2009 to 2013 (n=1,101,993). Structured patient data and the results of automated ECG interpretation by the Glasgow Program are described. Mean patient age is 51 years old, 59% of them are women. The average body mass index is 25.9 kg/m2, with an average increase of 0.15 kg/m2 per civil year. Those patients notably have hypertension (33.2%), family history of coronary artery disease (14.5%), smoking (6.9%), diabetes (5.8%), obesity (5.8%) or Chagas Disease (3.0%). Seventy percent of ECGs are normal. This percentage is higher in women (72.3%) and decreases in average by 7.4 every 10 years of life. There are notably 12% of possible myocardial infarction, 10% of possible left ventricular hypertrophy and 8% of possible supraventricular extra systole.

@article{koutkias_adverse_2014,
	title = {From adverse drug event detection to prevention. {A} novel clinical decision support framework for medication safety},
	volume = {53},
	copyright = {All rights reserved},
	issn = {0026-1270},
	doi = {10.3414/ME14-01-0027},
	abstract = {BACKGROUND: Errors related to medication seriously affect patient safety and the quality of healthcare. It has been widely argued that various types of such errors may be prevented by introducing Clinical Decision Support Systems (CDSSs) at the point of care.
OBJECTIVES: Although significant research has been conducted in the field, still medication safety is a crucial issue, while few research outcomes are mature enough to be considered for use in actual clinical settings. In this paper, we present a clinical decision support framework targeting medication safety with major focus on adverse drug event (ADE) prevention.
METHODS: The novelty of the framework lies in its design that approaches the problem holistically, i.e., starting from knowledge discovery to provide reliable numbers about ADEs per hospital or medical unit to describe their consequences and probable causes, and next employing the acquired knowledge for decision support services development and deployment. Major design features of the framework's services are: a) their adaptation to the context of care (i.e. patient characteristics, place of care, and significance of ADEs), and b) their straightforward integration in the healthcare information technologies (IT) infrastructure thanks to the adoption of a service-oriented architecture (SOA) and relevant standards.
RESULTS: Our results illustrate the successful interoperability of the framework with two commercially available IT products, i.e., a Computerized Physician Order Entry (CPOE) and an Electronic Health Record (EHR) system, respectively, along with a Web prototype that is independent of existing healthcare IT products. The conducted clinical validation with domain experts and test cases illustrates that the impact of the framework is expected to be major, with respect to patient safety, and towards introducing the CDSS functionality in practical use.
CONCLUSIONS: This study illustrates an important potential for the applicability of the presented framework in delivering con- textualized decision support services at the point of care and for making a substantial contribution towards ADE prevention. Nonetheless, further research is required in order to quantitatively and thoroughly assess its impact in medication safety.},
	language = {eng},
	number = {6},
	journal = {Methods of Information in Medicine},
	author = {Koutkias, V. G. and McNair, P. and Kilintzis, V. and Skovhus Andersen, K. and Niès, J. and Sarfati, J.-C. and Ammenwerth, E. and Chazard, E. and Jensen, S. and Beuscart, R. and Maglaveras, N.},
	month = dec,
	year = {2014},
	pmid = {25377477},
	pages = {482--492},
}

BACKGROUND: Errors related to medication seriously affect patient safety and the quality of healthcare. It has been widely argued that various types of such errors may be prevented by introducing Clinical Decision Support Systems (CDSSs) at the point of care. OBJECTIVES: Although significant research has been conducted in the field, still medication safety is a crucial issue, while few research outcomes are mature enough to be considered for use in actual clinical settings. In this paper, we present a clinical decision support framework targeting medication safety with major focus on adverse drug event (ADE) prevention. METHODS: The novelty of the framework lies in its design that approaches the problem holistically, i.e., starting from knowledge discovery to provide reliable numbers about ADEs per hospital or medical unit to describe their consequences and probable causes, and next employing the acquired knowledge for decision support services development and deployment. Major design features of the framework's services are: a) their adaptation to the context of care (i.e. patient characteristics, place of care, and significance of ADEs), and b) their straightforward integration in the healthcare information technologies (IT) infrastructure thanks to the adoption of a service-oriented architecture (SOA) and relevant standards. RESULTS: Our results illustrate the successful interoperability of the framework with two commercially available IT products, i.e., a Computerized Physician Order Entry (CPOE) and an Electronic Health Record (EHR) system, respectively, along with a Web prototype that is independent of existing healthcare IT products. The conducted clinical validation with domain experts and test cases illustrates that the impact of the framework is expected to be major, with respect to patient safety, and towards introducing the CDSS functionality in practical use. CONCLUSIONS: This study illustrates an important potential for the applicability of the presented framework in delivering con- textualized decision support services at the point of care and for making a substantial contribution towards ADE prevention. Nonetheless, further research is required in order to quantitatively and thoroughly assess its impact in medication safety.

@article{chazard_proposal_2014,
	title = {Proposal and evaluation of {FASDIM}, a {Fast} {And} {Simple} {De}-{Identification} {Method} for unstructured free-text clinical records},
	volume = {83},
	copyright = {All rights reserved},
	issn = {1872-8243},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2014_ijmi_fasdim.pdf},
	doi = {10.1016/j.ijmedinf.2013.11.005},
	abstract = {PURPOSE: Medical free-text records enable to get rich information about the patients, but often need to be de-identified by removing the Protected Health Information (PHI), each time the identification of the patient is not mandatory. Pattern matching techniques require pre-defined dictionaries, and machine learning techniques require an extensive training set. Methods exist in French, but either bring weak results or are not freely available. The objective is to define and evaluate FASDIM, a Fast And Simple De-Identification Method for French medical free-text records.
METHODS: FASDIM consists in removing all the words that are not present in the authorized word list, and in removing all the numbers except those that match a list of protection patterns. The corresponding lists are incremented in the course of the iterations of the method. For the evaluation, the workload is estimated in the course of records de-identification. The efficiency of the de-identification is assessed by independent medical experts on 508 discharge letters that are randomly selected and de-identified by FASDIM. Finally, the letters are encoded after and before de-identification according to 3 terminologies (ATC, ICD10, CCAM) and the codes are compared.
RESULTS: The construction of the list of authorized words is progressive: 12h for the first 7000 letters, 16 additional hours for 20,000 additional letters. The Recall (proportion of removed Protected Health Information, PHI) is 98.1\%, the Precision (proportion of PHI within the removed token) is 79.6\% and the F-measure (harmonic mean) is 87.9\%. In average 30.6 terminology codes are encoded per letter, and 99.02\% of those codes are preserved despite the de-identification.
CONCLUSION: FASDIM gets good results in French and is freely available. It is easy to implement and does not require any predefined dictionary.},
	language = {eng},
	number = {4},
	journal = {International Journal of Medical Informatics},
	author = {Chazard, Emmanuel and Mouret, Capucine and Ficheur, Grégoire and Schaffar, Aurélien and Beuscart, Jean-Baptiste and Beuscart, Régis},
	month = apr,
	year = {2014},
	pmid = {24370391},
	keywords = {Anonymization, Confidentiality, De-identification, Free text, Natural language processing},
	pages = {303--312},
}

PURPOSE: Medical free-text records enable to get rich information about the patients, but often need to be de-identified by removing the Protected Health Information (PHI), each time the identification of the patient is not mandatory. Pattern matching techniques require pre-defined dictionaries, and machine learning techniques require an extensive training set. Methods exist in French, but either bring weak results or are not freely available. The objective is to define and evaluate FASDIM, a Fast And Simple De-Identification Method for French medical free-text records. METHODS: FASDIM consists in removing all the words that are not present in the authorized word list, and in removing all the numbers except those that match a list of protection patterns. The corresponding lists are incremented in the course of the iterations of the method. For the evaluation, the workload is estimated in the course of records de-identification. The efficiency of the de-identification is assessed by independent medical experts on 508 discharge letters that are randomly selected and de-identified by FASDIM. Finally, the letters are encoded after and before de-identification according to 3 terminologies (ATC, ICD10, CCAM) and the codes are compared. RESULTS: The construction of the list of authorized words is progressive: 12h for the first 7000 letters, 16 additional hours for 20,000 additional letters. The Recall (proportion of removed Protected Health Information, PHI) is 98.1%, the Precision (proportion of PHI within the removed token) is 79.6% and the F-measure (harmonic mean) is 87.9%. In average 30.6 terminology codes are encoded per letter, and 99.02% of those codes are preserved despite the de-identification. CONCLUSION: FASDIM gets good results in French and is freely available. It is easy to implement and does not require any predefined dictionary.

@article{schaffar_etude_2014,
	series = {Colloque {Adelf}-Émois : "{Système} d'information hospitalier et Épidémiologie"},
	title = {Étude de la faisabilité de l’implémentation d’indicateurs automatisés de la qualité des soins en {France}},
	volume = {62, Supplement 3},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762014000339},
	doi = {10.1016/j.respe.2014.01.033},
	urldate = {2014-04-15},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Schaffar, A. and Babaousmail, D. and Ficheur, G. and Beuscart, R. and Chazard, E.},
	month = mar,
	year = {2014},
	pages = {S81},
}

@article{chazard_exploitation_2014,
	series = {Colloque {Adelf}-Émois : "{Système} d'information hospitalier et Épidémiologie"},
	title = {Exploitation automatisée des données électrocardiographiques pour le codage : mise en place et évaluation},
	volume = {62, Supplement 3},
	issn = {0398-7620},
	shorttitle = {Exploitation automatisée des données électrocardiographiques pour le codage},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762014000170},
	doi = {10.1016/j.respe.2014.01.017},
	urldate = {2014-04-15},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Dumesnil, C. and Marcolino, M. S. and Caron, A. and Alkmim, M. B. and Pinho-Ribeiro, A. L.},
	month = mar,
	year = {2014},
	pages = {S76},
}

@article{dumesnil_comparer_2014,
	series = {Colloque {Adelf}-Émois : "{Système} d'information hospitalier et Épidémiologie"},
	title = {Comparer les durées de séjour selon qu’un événement indésirable temps-dépendant survient : évaluation et correction du risque de première espèce},
	volume = {62, Supplement 3},
	issn = {0398-7620},
	shorttitle = {Comparer les durées de séjour selon qu’un événement indésirable temps-dépendant survient},
	url = {http://www.sciencedirect.com/science/article/pii/S039876201400090X},
	doi = {10.1016/j.respe.2014.01.090},
	urldate = {2014-04-15},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Dumesnil, C. and Beuscart, R. and Chazard, E.},
	month = mar,
	year = {2014},
	pages = {S99},
}

@article{aernout_codage_2014,
	series = {Colloque {Adelf}-Émois : "{Système} d'information hospitalier et Épidémiologie"},
	title = {Codage automatisé à partir des comptes-rendus d’actes : construction et évaluation de règles de prédiction par une méthode mixte associant fouille de texte et validation experte},
	volume = {62, Supplement 3},
	issn = {0398-7620},
	shorttitle = {Codage automatisé à partir des comptes-rendus d’actes},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762014000704},
	doi = {10.1016/j.respe.2014.01.070},
	urldate = {2014-04-15},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Aernout, E. and Ficheur, G. and Djennaoui, M. and Chazard, E. and Beuscart, R.},
	month = mar,
	year = {2014},
	pages = {S93},
}

@techreport{chazard_livrable_2014,
	address = {Lille, France},
	title = {Livrable {D1}.1 : données médicales, confidentialité et secret médical. {Projet} {ANR} {Clinmine}},
	language = {FR},
	institution = {Agence Nationale de la Recherche},
	author = {Chazard, Emmanuel and Ficheur, Grégoire and Perichon, Renaud},
	month = feb,
	year = {2014},
}

@article{ficheur_adverse_2014,
	title = {Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases},
	volume = {14},
	copyright = {All rights reserved},
	issn = {1472-6947},
	shorttitle = {Adverse drug events with hyperkalaemia during inpatient stays},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2014_bmcmidm_adewithhyperkalemia.pdf},
	doi = {10.1186/1472-6947-14-83},
	abstract = {BACKGROUND: Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays.
METHODS: We used a set of complex detection rules to take account of the patient's clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules' analytical quality was evaluated for ADEs.
RESULTS: In terms of recall, 89.5\% of ADEs with hyperkalaemia "with or without an abnormal symptom" were automatically identified (including all three serious ADEs). In terms of precision, 63.7\% of the automatically identified ADEs with hyperkalaemia were true ADEs.
CONCLUSIONS: The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.},
	language = {eng},
	journal = {BMC medical informatics and decision making},
	author = {Ficheur, Grégoire and Chazard, Emmanuel and Beuscart, Jean-Baptiste and Merlin, Béatrice and Luyckx, Michel and Beuscart, Régis},
	year = {2014},
	pmid = {25212108},
	pmcid = {PMC4164763},
	pages = {83},
}

BACKGROUND: Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. METHODS: We used a set of complex detection rules to take account of the patient's clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules' analytical quality was evaluated for ADEs. RESULTS: In terms of recall, 89.5% of ADEs with hyperkalaemia "with or without an abnormal symptom" were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. CONCLUSIONS: The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.

@article{hackl_clinical_2013,
	title = {Clinical evaluation of the {ADE} scorecards as a decision support tool for adverse drug event analysis and medication safety management},
	volume = {76 Suppl 1},
	copyright = {All rights reserved},
	issn = {1365-2125},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2013_bjcp_clinicalevalofadescorecards.pdf},
	doi = {10.1111/bcp.12185},
	abstract = {AIMS: The prevention of adverse drug events (ADEs) demands co-ordination of different health care professionals. ADE scorecards are a novel approach to raise the team awareness regarding ADE risks and causes. It makes information on numbers and on possible causes of possible ADE cases available to the clinical team. The aim of the study was to investigate the usage and acceptance of ADE scorecards by healthcare professionals and their impact on rates of possible ADEs.
METHODS: ADE scorecards were introduced in three departments of a French hospital. A controlled time series analysis of ADE data was conducted to assess the impact of the ADE scorecards. In addition, qualitative interviews and a standardized survey with all participating staff members were performed.
RESULTS: Physicians, nurses and pharmacists found ADE scorecards effective to increase medication safety and recommended future usage. The time-series analysis did not show changes in rates of possible ADEs.
CONCLUSION: ADE scorecards appear to be useful to raise awareness of ADE-related issues among professionals. Although the evaluation did not show significant reductions of ADE rates, the participating physicians, nurses and pharmacists believed that the ADE scorecards could contribute to increased patient safety and to a reduction in ADE rates. Strategies need to be designed to integrate ADE scorecards better into the clinical routine and to increase the precision of ADE detection.},
	language = {eng},
	journal = {British journal of clinical pharmacology},
	author = {Hackl, Werner O and Ammenwerth, Elske and Marcilly, Romaric and Chazard, Emmanuel and Luyckx, Michel and Leurs, Pascale and Beuscart, Regis},
	month = sep,
	year = {2013},
	pmid = {24007454},
	keywords = {Medical Order Entry Systems, Patient Safety, evaluation studies, medication therapy management},
	pages = {78--90},
}

AIMS: The prevention of adverse drug events (ADEs) demands co-ordination of different health care professionals. ADE scorecards are a novel approach to raise the team awareness regarding ADE risks and causes. It makes information on numbers and on possible causes of possible ADE cases available to the clinical team. The aim of the study was to investigate the usage and acceptance of ADE scorecards by healthcare professionals and their impact on rates of possible ADEs. METHODS: ADE scorecards were introduced in three departments of a French hospital. A controlled time series analysis of ADE data was conducted to assess the impact of the ADE scorecards. In addition, qualitative interviews and a standardized survey with all participating staff members were performed. RESULTS: Physicians, nurses and pharmacists found ADE scorecards effective to increase medication safety and recommended future usage. The time-series analysis did not show changes in rates of possible ADEs. CONCLUSION: ADE scorecards appear to be useful to raise awareness of ADE-related issues among professionals. Although the evaluation did not show significant reductions of ADE rates, the participating physicians, nurses and pharmacists believed that the ADE scorecards could contribute to increased patient safety and to a reduction in ADE rates. Strategies need to be designed to integrate ADE scorecards better into the clinical routine and to increase the precision of ADE detection.

@inproceedings{contreras_tatouage_2013,
	title = {Tatouage {Robuste} et {Réversible} pour la {Traçabilité} de {Bases} de {Données} {Relationnelles} en {Santé}},
	url = {https://www.researchgate.net/publication/281804368_Tatouage_Robuste_et_Reversible_pour_la_Tracabilite_de_Bases_de_Donnees_Relationnelles_en_Sante},
	abstract = {Dans cet article, nous proposons un schéma de tatouage avec pour objectif la traçabilité des bases de données de santé. Celui-ci s'appuie sur une modulation de tatouage réversible et robuste...},
	urldate = {2016-10-02},
	booktitle = {{ResearchGate}},
	author = {Contreras, Javier FRANCO and Coatrieux, Gouenou and Cuppens, Frédéric and Cuppens-Boulahia, Nora and Chazard, Emmanuel and Roux, Christian},
	month = apr,
	year = {2013},
}

Dans cet article, nous proposons un schéma de tatouage avec pour objectif la traçabilité des bases de données de santé. Celui-ci s'appuie sur une modulation de tatouage réversible et robuste...

@article{ficheur_proposition_2013,
	title = {Proposition d’une méthode automatisée calculant la valeur moyenne d’un diagnostic associé significatif},
	volume = {61, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762013000485},
	doi = {10.1016/j.respe.2013.01.047},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Ficheur, G. and Genty, M. and Chazard, E. and Flament, C. and Beuscart, R.},
	month = mar,
	year = {2013},
	pages = {S18--S19},
}

@article{chazard__2013,
	title = {« {Planifadmission} », outil open-source d’aide à la planification des admissions programmées basé sur une prédiction statistique des durées de séjour},
	volume = {61, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762013000060},
	doi = {10.1016/j.respe.2013.01.005},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Miquel, P.-H. and Genty, M. and Beuscart, R.},
	month = mar,
	year = {2013},
	pages = {S5--S6},
}

@article{chazard_routine_2013,
	title = {Routine use of the "{ADE} scorecards", an application for automated {ADE} detection in a general hospital},
	volume = {192},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2013_medinfo_scorecards.pdf},
	abstract = {Retrospective detection of Adverse Drug Events (ADEs) is challenging, notably because ADEs result from complex interactions between many factors. Data mining techniques have recently emerged in the field of automated retrospective ADE detection. The "ADE Scorecards" are a research application based on data-mining that has been built in the framework of the PSIP European Project, and potentially enables automated ADE retrospective detection. The objective of this paper is to evaluate the use of the ADE Scorecards in a real-life healthcare situation. For that purpose, the ADE Scorecards have been implemented in a French general hospital and have been used by the physicians and pharmacists for three years (corresponding to 73,000 inpatient stays). According to the results, 2\% of the analyzed inpatient stays have a potential ADE with hyperkalemia, and 1\% of them have a potential ADE with vitamin K antagonist overdose. In practice, the application, which was first designed to be a standalone web-based application for the physicians, has been used as a part of a more global quality improvement approach led by the pharmacists.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Luyckx, Michel and Beuscart, Jean-Baptiste and Ferret, Laurie and Beuscart, Régis},
	year = {2013},
	pmid = {23920566},
	pages = {308--312},
}

Retrospective detection of Adverse Drug Events (ADEs) is challenging, notably because ADEs result from complex interactions between many factors. Data mining techniques have recently emerged in the field of automated retrospective ADE detection. The "ADE Scorecards" are a research application based on data-mining that has been built in the framework of the PSIP European Project, and potentially enables automated ADE retrospective detection. The objective of this paper is to evaluate the use of the ADE Scorecards in a real-life healthcare situation. For that purpose, the ADE Scorecards have been implemented in a French general hospital and have been used by the physicians and pharmacists for three years (corresponding to 73,000 inpatient stays). According to the results, 2% of the analyzed inpatient stays have a potential ADE with hyperkalemia, and 1% of them have a potential ADE with vitamin K antagonist overdose. In practice, the application, which was first designed to be a standalone web-based application for the physicians, has been used as a part of a more global quality improvement approach led by the pharmacists.

@article{ferret_evaluation_2013,
	title = {Evaluation of a computerized tool allowing retrospective detection of potential vitamin {K} antagonist overdoses in complex contexts},
	volume = {192},
	copyright = {All rights reserved},
	issn = {0926-9630},
	abstract = {Management of vitamin K antagonists (VKA) is difficult, and overdoses can have dramatic hemorrhagic consequences. These works form part of a European computerized medical data processing project, which aims to develop IT tools for describing adverse drug events (ADEs). Materials and methods A tool enabling retrospective research of potential ADE cases was developed, using complex ADE detection rules taking into account chronological parameters: the ADE scorecards. The rules were applied on 14,748 medical records from a community hospital. We evaluated the predictive positive value of the rules related to INR elevation by an expert review of the detected cases. The severity of the clinical consequences was evaluated. Results 49 cases were detected, among which 11 cases were ADEs. The predictive positive value of the rules is 22.44\%, mostly related to antibiotics and amiodarone introduction. The four cases of clinical damage related to a drug were properly designated by the rules. Discussion - Conclusion Our study shows the great potential of developing complex rules for the identification of adverse drug events in large medical databases.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Ferret, Laurie and Luyckx, Michel and Merlin, Béatrice and Ficheur, Grégoire and Chazard, Emmanuel and Beuscart, Régis},
	year = {2013},
	pmid = {23920616},
	pages = {553--556},
}

Management of vitamin K antagonists (VKA) is difficult, and overdoses can have dramatic hemorrhagic consequences. These works form part of a European computerized medical data processing project, which aims to develop IT tools for describing adverse drug events (ADEs). Materials and methods A tool enabling retrospective research of potential ADE cases was developed, using complex ADE detection rules taking into account chronological parameters: the ADE scorecards. The rules were applied on 14,748 medical records from a community hospital. We evaluated the predictive positive value of the rules related to INR elevation by an expert review of the detected cases. The severity of the clinical consequences was evaluated. Results 49 cases were detected, among which 11 cases were ADEs. The predictive positive value of the rules is 22.44%, mostly related to antibiotics and amiodarone introduction. The four cases of clinical damage related to a drug were properly designated by the rules. Discussion - Conclusion Our study shows the great potential of developing complex rules for the identification of adverse drug events in large medical databases.

@article{pruvost_value_2013,
	title = {The value of body weight measurement to assess dehydration in children},
	volume = {8},
	copyright = {All rights reserved},
	issn = {1932-6203},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2013_plosone_bodyweightdehydrationchildren.pdf},
	doi = {10.1371/journal.pone.0055063},
	abstract = {Dehydration secondary to gastroenteritis is one of the most common reasons for office visits and hospital admissions. The indicator most commonly used to estimate dehydration status is acute weight loss. Post-illness weight gain is considered as the gold-standard to determine the true level of dehydration and is widely used to estimate weight loss in research. To determine the value of post-illness weight gain as a gold standard for acute dehydration, we conducted a prospective cohort study in which 293 children, aged 1 month to 2 years, with acute diarrhea were followed for 7 days during a 3-year period. The main outcome measures were an accurate pre-illness weight (if available within 8 days before the diarrhea), post-illness weight, and theoretical weight (predicted from the child's individual growth chart). Post-illness weight was measured for 231 (79\%) and both theoretical and post-illness weights were obtained for 111 (39\%). Only 62 (21\%) had an accurate pre-illness weight. The correlation between post-illness and theoretical weight was excellent (0.978), but bootstrapped linear regression analysis showed that post-illness weight underestimated theoretical weight by 0.48 kg (95\% CI: 0.06-0.79, p{\textless}0.02). The mean difference in the fluid deficit calculated was 4.0\% of body weight (95\% CI: 3.2-4.7, p{\textless}0.0001). Theoretical weight overestimated accurate pre-illness weight by 0.21 kg (95\% CI: 0.08-0.34, p = 0.002). Post-illness weight underestimated pre-illness weight by 0.19 kg (95\% CI: 0.03-0.36, p = 0.02). The prevalence of 5\% dehydration according to post-illness weight (21\%) was significantly lower than the prevalence estimated by either theoretical weight (60\%) or clinical assessment (66\%, p{\textless}0.0001).These data suggest that post-illness weight is of little value as a gold standard to determine the true level of dehydration. The performance of dehydration signs or scales determined by using post-illness weight as a gold standard has to be reconsidered.},
	language = {eng},
	number = {1},
	journal = {PloS one},
	author = {Pruvost, Isabelle and Dubos, François and Chazard, Emmanuel and Hue, Valérie and Duhamel, Alain and Martinot, Alain},
	year = {2013},
	pmid = {23383058},
	keywords = {Body Weight, Child, Preschool, Dehydration, Female, Humans, Infant, Male, Reference Values, Weight Gain},
	pages = {e55063},
}

Dehydration secondary to gastroenteritis is one of the most common reasons for office visits and hospital admissions. The indicator most commonly used to estimate dehydration status is acute weight loss. Post-illness weight gain is considered as the gold-standard to determine the true level of dehydration and is widely used to estimate weight loss in research. To determine the value of post-illness weight gain as a gold standard for acute dehydration, we conducted a prospective cohort study in which 293 children, aged 1 month to 2 years, with acute diarrhea were followed for 7 days during a 3-year period. The main outcome measures were an accurate pre-illness weight (if available within 8 days before the diarrhea), post-illness weight, and theoretical weight (predicted from the child's individual growth chart). Post-illness weight was measured for 231 (79%) and both theoretical and post-illness weights were obtained for 111 (39%). Only 62 (21%) had an accurate pre-illness weight. The correlation between post-illness and theoretical weight was excellent (0.978), but bootstrapped linear regression analysis showed that post-illness weight underestimated theoretical weight by 0.48 kg (95% CI: 0.06-0.79, p\textless0.02). The mean difference in the fluid deficit calculated was 4.0% of body weight (95% CI: 3.2-4.7, p\textless0.0001). Theoretical weight overestimated accurate pre-illness weight by 0.21 kg (95% CI: 0.08-0.34, p = 0.002). Post-illness weight underestimated pre-illness weight by 0.19 kg (95% CI: 0.03-0.36, p = 0.02). The prevalence of 5% dehydration according to post-illness weight (21%) was significantly lower than the prevalence estimated by either theoretical weight (60%) or clinical assessment (66%, p\textless0.0001).These data suggest that post-illness weight is of little value as a gold standard to determine the true level of dehydration. The performance of dehydration signs or scales determined by using post-illness weight as a gold standard has to be reconsidered.

@book{venot_alain_medical_2013,
	address = {Paris, France},
	series = {Fundamentals and {Applications}},
	title = {Medical {Informatics}, e-{Health} - {Fundamentals} and {Applications}},
	isbn = {978-2-8178-0478-1},
	abstract = {Over the years, medical informatics has matured into a true scientific discipline. Fundamental and applied aspects are now taught in various fields of health, including medicine, dentistry, pharmacy, nursing and public health. ...},
	language = {En},
	urldate = {2014-03-07},
	publisher = {Springer},
	author = {{Venot, Alain} and {Burgun, Anita} and {Quantin, Catherine}},
	year = {2013},
	keywords = {Health Administration, Health Informatics, Medical Informatics, e-Health - Fundamentals and Applications},
}

Over the years, medical informatics has matured into a true scientific discipline. Fundamental and applied aspects are now taught in various fields of health, including medicine, dentistry, pharmacy, nursing and public health. ...

@book{venot_alain_informatique_2013,
	address = {Paris, France},
	series = {Fondements et applications},
	title = {Informatique {Médicale}, e-{Santé} – {Fondements} et applications},
	isbn = {978-2-8178-0338-8},
	abstract = {L’informatique médicale est devenue au fil des années une vraie discipline scientifique dont les bases et applications sont enseignées non seulement dans tous les domaines de santé (médecine, odontologie, pharmacie, maïeutique, ...},
	language = {Fr},
	urldate = {2014-03-07},
	publisher = {Springer},
	author = {{Venot, Alain} and {Burgun, Anita} and {Quantin, Catherine}},
	year = {2013},
	keywords = {Informatique médicale, e-Santé – Fondements et applications},
}

L’informatique médicale est devenue au fil des années une vraie discipline scientifique dont les bases et applications sont enseignées non seulement dans tous les domaines de santé (médecine, odontologie, pharmacie, maïeutique, ...

@article{ficheur_supervised_2013,
	title = {Supervised analysis of drug prescription sequences},
	volume = {192},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://ebooks.iospress.nl/publication/34005},
	abstract = {Hospitals have at their disposal large databases that may be considered for reuse. The objective of this work is to evaluate the impact of a drug on a specific laboratory result by analyzing these data. This analysis first involves building a record of temporal patterns, including medical context, of drug prescriptions. Changes in outcome due to these patterns of drug prescription are assessed using short phases of the inpatient stay compared to monotonous changes in the laboratory result. To illustrate this technique, we investigated potassium chloride supplementation and its impact on kalemia. This method enables us to assess the impact of a drug (in its frequent context of prescription) on a laboratory result. This kind of analysis could play a role in post-marketing studies.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Ficheur, Grégoire and Chazard, Emmanuel and Merlin, Béatrice and Ferret, Laurie and Luyckx, Michel and Beuscart, Régis},
	year = {2013},
	pmid = {23920563},
	pages = {293--297},
}

Hospitals have at their disposal large databases that may be considered for reuse. The objective of this work is to evaluate the impact of a drug on a specific laboratory result by analyzing these data. This analysis first involves building a record of temporal patterns, including medical context, of drug prescriptions. Changes in outcome due to these patterns of drug prescription are assessed using short phases of the inpatient stay compared to monotonous changes in the laboratory result. To illustrate this technique, we investigated potassium chloride supplementation and its impact on kalemia. This method enables us to assess the impact of a drug (in its frequent context of prescription) on a laboratory result. This kind of analysis could play a role in post-marketing studies.

@article{chazard_contextualisation_2012,
	title = {Contextualisation pour la détection et la prévention des effets indésirables médicamenteux},
	volume = {60, Supplement 2},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762012004841},
	doi = {10.1016/j.respe.2012.06.376},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Ficheur, G. and Bernonville, S. and Beuscart, J.-B. and Beuscart, R.},
	month = sep,
	year = {2012},
	pages = {S143--S144},
}

@article{ficheur_interoperabilite_2012,
	title = {Interopérabilité des bases de données médicales : proposition d’une méthode de mise en correspondance des bases de biologie optimisant leur exploitation},
	volume = {60, Supplement 1},
	issn = {0398-7620},
	shorttitle = {Interopérabilité des bases de données médicales},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762011005591},
	doi = {10.1016/j.respe.2011.12.114},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Ficheur, G. and Beuscart, J.-B. and Schaffar, A. and Chazard, E.},
	month = mar,
	year = {2012},
	keywords = {Biologie, CIM-10, Interopérabilité},
	pages = {S19},
}

@article{chazard_deidentification_2012,
	title = {Déidentification automatisée de courriers médicaux : la méthode {FASDIM}},
	volume = {60, Supplement 1},
	issn = {0398-7620},
	shorttitle = {Déidentification automatisée de courriers médicaux},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762011005578},
	doi = {10.1016/j.respe.2011.12.112},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Mouret-Kubiak, C. and Ficheur, G. and Beuscart, R.},
	month = mar,
	year = {2012},
	keywords = {Anonymisation, Confidentialité, Déidentification},
	pages = {S18},
}

@article{chazard_statistics-based_2012,
	title = {A statistics-based approach of contextualization for adverse drug events detection and prevention},
	volume = {180},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2012_mie_contextualization.pdf},
	abstract = {Several papers propose to take contexts into account for adverse drug events (ADE) detection and prevention, notably to decrease over-alerting of clinical decision support systems (CDSS). However, no statistical argument has been published till now. This works demonstrates, based on statistical analysis, that contextualization is necessary for ADE detection and prevention by 3 steps. A database of 115,447 inpatients stays from 6 hospitals, and 236 ADE detection rules are used. Step 1: the patients differ significantly between and within hospitals, regarding their medical background, their medication and several outcomes. Step 2: The estimated ADE rates vary between and within hospitals. Step 3: even when comparable conditions are present, the probability of ADE occurrence may differ between and within hospitals. Those 3 steps demonstrate that contextualization is necessary, and pave the way for a statistics-based method to contextualize ADE prevention (CDSS) and ADE detection tools.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Bernonville, Stéphanie and Ficheur, Grégoire and Beuscart, Régis},
	year = {2012},
	pmid = {22874295},
	keywords = {Adverse Drug Reaction Reporting Systems, Data Interpretation, Statistical, Data Mining, Decision Support Systems, Clinical, Drug Toxicity, Drug-Related Side Effects and Adverse Reactions, Electronic Health Records, France, Health Records, Personal, Humans, Prevalence, Sensitivity and Specificity},
	pages = {766--770},
}

Several papers propose to take contexts into account for adverse drug events (ADE) detection and prevention, notably to decrease over-alerting of clinical decision support systems (CDSS). However, no statistical argument has been published till now. This works demonstrates, based on statistical analysis, that contextualization is necessary for ADE detection and prevention by 3 steps. A database of 115,447 inpatients stays from 6 hospitals, and 236 ADE detection rules are used. Step 1: the patients differ significantly between and within hospitals, regarding their medical background, their medication and several outcomes. Step 2: The estimated ADE rates vary between and within hospitals. Step 3: even when comparable conditions are present, the probability of ADE occurrence may differ between and within hospitals. Those 3 steps demonstrate that contextualization is necessary, and pave the way for a statistics-based method to contextualize ADE prevention (CDSS) and ADE detection tools.

@article{franco_contreras_robust_2012,
	title = {Robust lossless watermarking based on circular interpretation of bijective transformations for the protection of medical databases},
	volume = {2012},
	copyright = {All rights reserved},
	issn = {1557-170X},
	doi = {10.1109/EMBC.2012.6347330},
	abstract = {In this paper, we adapt the image lossless watermarking modulation proposed by De Vleeschouwer et al., based on the circular interpretation of bijective modulations, to the protection of medical relational databases. Our scheme modulates the numerical attributes of the database. It is suited for either copyright protection, integrity control or traitor tracing, being robust to most common database attacks, such as the addition and removal of tuples and the modification of attributes' values. Conducted experiments on a medical database of inpatient hospital stay records illustrate the overall performance of our method and its suitability to the requirements of the medical domain.},
	language = {eng},
	journal = {Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference},
	author = {Franco Contreras, J and Coatrieux, G and Chazard, E and Cuppens, F and Cuppens-Boulahia, N and Roux, C},
	year = {2012},
	pmid = {23367265},
	keywords = {Algorithms, Computer Security, Electronic Health Records},
	pages = {5875--5878},
}

In this paper, we adapt the image lossless watermarking modulation proposed by De Vleeschouwer et al., based on the circular interpretation of bijective modulations, to the protection of medical relational databases. Our scheme modulates the numerical attributes of the database. It is suited for either copyright protection, integrity control or traitor tracing, being robust to most common database attacks, such as the addition and removal of tuples and the modification of attributes' values. Conducted experiments on a medical database of inpatient hospital stay records illustrate the overall performance of our method and its suitability to the requirements of the medical domain.

@article{chazard_data_2011,
	title = {Data mining to generate adverse drug events detection rules},
	volume = {15},
	copyright = {All rights reserved},
	issn = {1558-0032},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2011_ieeetitb_dataminingadedetectionrules.pdf},
	doi = {10.1109/TITB.2011.2165727},
	abstract = {Adverse drug events (ADEs) are a public health issue. Their detection usually relies on voluntary reporting or medical chart reviews. The objective of this paper is to automatically detect cases of ADEs by data mining. 115,447 complete past hospital stays are extracted from six French, Danish, and Bulgarian hospitals using a common data model including diagnoses, drug administrations, laboratory results, and free-text records. Different kinds of outcomes are traced, and supervised rule induction methods (decision trees and association rules) are used to discover ADE detection rules, with respect to time constraints. The rules are then filtered, validated, and reorganized by a committee of experts. The rules are described in a rule repository, and several statistics are automatically computed in every medical department, such as the confidence, relative risk, and median delay of outcome appearance. 236 validated ADE-detection rules are discovered; they enable to detect 27 different kinds of outcomes. The rules use a various number of conditions related to laboratory results, diseases, drug administration, and demographics. Some rules involve innovative conditions, such as drug discontinuations.},
	language = {eng},
	number = {6},
	journal = {IEEE transactions on information technology in biomedicine: a publication of the IEEE Engineering in Medicine and Biology Society},
	author = {Chazard, Emmanuel and Ficheur, Grégoire and Bernonville, Stéphanie and Luyckx, Michel and Beuscart, Régis},
	month = nov,
	year = {2011},
	pmid = {21859604},
	keywords = {Adverse Drug Reaction Reporting Systems, Adverse drug events (ADEs), Data Mining, Decision Support Systems, Clinical, Decision Trees, Drug Toxicity, Electronic Health Records, Humans, Medical diagnostic imaging, Medical information systems, Medical services, Patient Safety, Patient monitoring, Pharmaceutical Preparations, Software, adverse drug events detection rules, automatically detect cases, data model, data models, demographics, drug administrations, drug discontinuations, drugs, free-text recording, median delay, medical computing, patient diagnosis, public health, relative risk, rule repository, statistical analysis, supervised rule methods},
	pages = {823--830},
}

Adverse drug events (ADEs) are a public health issue. Their detection usually relies on voluntary reporting or medical chart reviews. The objective of this paper is to automatically detect cases of ADEs by data mining. 115,447 complete past hospital stays are extracted from six French, Danish, and Bulgarian hospitals using a common data model including diagnoses, drug administrations, laboratory results, and free-text records. Different kinds of outcomes are traced, and supervised rule induction methods (decision trees and association rules) are used to discover ADE detection rules, with respect to time constraints. The rules are then filtered, validated, and reorganized by a committee of experts. The rules are described in a rule repository, and several statistics are automatically computed in every medical department, such as the confidence, relative risk, and median delay of outcome appearance. 236 validated ADE-detection rules are discovered; they enable to detect 27 different kinds of outcomes. The rules use a various number of conditions related to laboratory results, diseases, drug administration, and demographics. Some rules involve innovative conditions, such as drug discontinuations.

@article{chazard__2011,
	title = {Les « {ADE} {Scorecards} », outil de détection et visualisation des effets indésirables médicamenteux},
	volume = {59, Supplement 2},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762011001623},
	doi = {10.1016/j.respe.2011.03.036},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Ficheur, G. and Baceanu, A. and Marcilly, R. and Beuscart, R.},
	month = jun,
	year = {2011},
	keywords = {Circuit du médicament, Data Mining, Effets indésirables liés aux médicaments, Sécurité du patient},
	pages = {S54},
}

@article{ficheur_codage_2011,
	title = {Codage automatisé : proposition d’une méthode utilisant une ontologie médicale construite par fouille de textes},
	volume = {59, Supplement 2},
	issn = {0398-7620},
	shorttitle = {Codage automatisé},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762011001520},
	doi = {10.1016/j.respe.2011.03.026},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Ficheur, G. and Chazard, E. and Messai, R. and Beuscart, R.},
	month = jun,
	year = {2011},
	keywords = {Codage automatisé, Fouille de données, Fouille de textes, Ontologie, Terminologie},
	pages = {S51},
}

@phdthesis{chazard_automated_2011,
	type = {These de doctorat},
	title = {Automated detection of adverse drug events by data mining of electronic health records},
	copyright = {Licence Etalab},
	url = {http://theses.fr/2011LIL2S009},
	abstract = {Les effets indésirables liés aux médicaments (EIM) sont des dommages liés au traitement médicamenteux plutôt qu’aux conditions sous-jacentes du patient. Ils mettent les patients en danger, et la plupart d’entre eux sont évitables. La détection des EIM repose habituellement sur les reports spontanés d’EIM et sur la revue de dossiers. L’objectif du présent travail est d’identifier automatiquement les cas d’EIM en utilisant des méthodes de Data Mining (fouille statistique de données). Le DataMining est un ensemble de méthodes statistiques particulièrement adaptées à la découverte de règles dans de grandes bases de données.Matériel Un modèle de données commun est tout d’abord défini, dans le but de décrire les données qui peuvent être extraites des dossiers patient électroniques. Plus de 90 000séjours hospitaliers complets sont extraits de 5 hôpitaux français et danois. Ces enregistrements incluent les diagnostics, les résultats de biologie, les médicaments administrés, des informations démographiques et administratives, et enfin du texte libre (courriers, comptes-rendus). Lorsque les médicaments ne peuvent être extraits d’un CPOE (système de prescription connectée), ils sont extraits des courriers pa rSemantic Mining (fouille de texte). De plus, la société Vidal fournit un ensemble exhaustif de RCP (Résumés des Caractéristiques du Produit).Méthode On tente de tracer dans les données tous les événements indésirables décrits dans les RCP. Puis en utilisant les méthodes de Data Mining, en particulier les arbres de décision et les règles d’association, on identifie les circonstances qui favorisent l’apparition d’EIM. Plusieurs règles de détection des EIM sont ainsi obtenues, elles sont ensuite filtrées et validées par un comité d’experts. Enfin, les règles sont décrites sous forme de fichiers XML et stockées dans une base. Elles sont exécutées afin de calculer certaines statistiques et de détecter les cas d’EIM.Résultats236 règles de détection des EIM sont ainsi découvertes. Elles permettent de détecter27 types d’événements indésirables différents. Plusieurs statistiques sont calculées automatiquement pour chaque règle dans chaque service, comme la confiance ou le risque relatif. Ces règles impliquent des conditions innovantes : par exemple certaines règles décrivent les conséquences de l’arrêt d’un médicament. De plus, deux outils Web sont développés et mis à la disposition des praticiens via Internet : les Scorecards permettent de présenter des informations statistiques e tépidémiologiques sur les EIM propres à chaque service, tandis que l’Expert Explorer permet aux médecins d’examiner en détail les cas probables d’EIM de leur service.Enfin, une évaluation préliminaire de l’impact clinique des EIM est menée, ainsi que l’évaluation de la précision de détection des EIM.},
	urldate = {2022-06-20},
	school = {Lille 2},
	author = {Chazard, Emmanuel},
	collaborator = {Beuscart, Régis},
	month = feb,
	year = {2011},
	keywords = {Arbres de décision, Arbres de décision -- Dissertation universitaire, Arbres de décision -- Dissertations académiques, Arbres de décision -- Thèses et écrits académiques, Data mining, Effets secondaires indésirables des médicaments -- Dissertation universitaire, Effets secondaires indésirables des médicaments -- Dissertations académiques, Exploration de données, Exploration de données -- Thèses et écrits académiques, Médicaments -- Effets secondaires, Médicaments -- Effets secondaires -- Thèses et écrits académiques, Préparations pharmaceutiques -- effets indésirables -- Dissertation universitaire, Préparations pharmaceutiques -- effets indésirables -- Dissertations académiques, Semantic mining, Système de prescription connectée},
}

Les effets indésirables liés aux médicaments (EIM) sont des dommages liés au traitement médicamenteux plutôt qu’aux conditions sous-jacentes du patient. Ils mettent les patients en danger, et la plupart d’entre eux sont évitables. La détection des EIM repose habituellement sur les reports spontanés d’EIM et sur la revue de dossiers. L’objectif du présent travail est d’identifier automatiquement les cas d’EIM en utilisant des méthodes de Data Mining (fouille statistique de données). Le DataMining est un ensemble de méthodes statistiques particulièrement adaptées à la découverte de règles dans de grandes bases de données.Matériel Un modèle de données commun est tout d’abord défini, dans le but de décrire les données qui peuvent être extraites des dossiers patient électroniques. Plus de 90 000séjours hospitaliers complets sont extraits de 5 hôpitaux français et danois. Ces enregistrements incluent les diagnostics, les résultats de biologie, les médicaments administrés, des informations démographiques et administratives, et enfin du texte libre (courriers, comptes-rendus). Lorsque les médicaments ne peuvent être extraits d’un CPOE (système de prescription connectée), ils sont extraits des courriers pa rSemantic Mining (fouille de texte). De plus, la société Vidal fournit un ensemble exhaustif de RCP (Résumés des Caractéristiques du Produit).Méthode On tente de tracer dans les données tous les événements indésirables décrits dans les RCP. Puis en utilisant les méthodes de Data Mining, en particulier les arbres de décision et les règles d’association, on identifie les circonstances qui favorisent l’apparition d’EIM. Plusieurs règles de détection des EIM sont ainsi obtenues, elles sont ensuite filtrées et validées par un comité d’experts. Enfin, les règles sont décrites sous forme de fichiers XML et stockées dans une base. Elles sont exécutées afin de calculer certaines statistiques et de détecter les cas d’EIM.Résultats236 règles de détection des EIM sont ainsi découvertes. Elles permettent de détecter27 types d’événements indésirables différents. Plusieurs statistiques sont calculées automatiquement pour chaque règle dans chaque service, comme la confiance ou le risque relatif. Ces règles impliquent des conditions innovantes : par exemple certaines règles décrivent les conséquences de l’arrêt d’un médicament. De plus, deux outils Web sont développés et mis à la disposition des praticiens via Internet : les Scorecards permettent de présenter des informations statistiques e tépidémiologiques sur les EIM propres à chaque service, tandis que l’Expert Explorer permet aux médecins d’examiner en détail les cas probables d’EIM de leur service.Enfin, une évaluation préliminaire de l’impact clinique des EIM est menée, ainsi que l’évaluation de la précision de détection des EIM.

@article{chazard_ade_2011,
	title = {The {ADE} scorecards: a tool for adverse drug event detection in electronic health records},
	volume = {166},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {The {ADE} scorecards},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2011_psip_scorecards.pdf},
	abstract = {Although several methods exist for Adverse Drug events (ADE) detection due to past hospitalizations, a tool that could display those ADEs to the physicians does not exist yet. This article presents the ADE Scorecards, a Web tool that enables to screen past hospitalizations extracted from Electronic Health Records (EHR), using a set of ADE detection rules, presently rules discovered by data mining. The tool enables the physicians to (1) get contextualized statistics about the ADEs that happen in their medical department, (2) see the rules that are useful in their department, i.e. the rules that could have enabled to prevent those ADEs and (3) review in detail the ADE cases, through a comprehensive interface displaying the diagnoses, procedures, lab results, administered drugs and anonymized records. The article shows a demonstration of the tool through a use case.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Băceanu, Adrian and Ferret, Laurie and Ficheur, Grégoire},
	year = {2011},
	pmid = {21685622},
	keywords = {Data Mining, Drug Toxicity, Humans, Information Systems, Internet, Medical Records Systems, Computerized},
	pages = {169--179},
}

Although several methods exist for Adverse Drug events (ADE) detection due to past hospitalizations, a tool that could display those ADEs to the physicians does not exist yet. This article presents the ADE Scorecards, a Web tool that enables to screen past hospitalizations extracted from Electronic Health Records (EHR), using a set of ADE detection rules, presently rules discovered by data mining. The tool enables the physicians to (1) get contextualized statistics about the ADEs that happen in their medical department, (2) see the rules that are useful in their department, i.e. the rules that could have enabled to prevent those ADEs and (3) review in detail the ADE cases, through a comprehensive interface displaying the diagnoses, procedures, lab results, administered drugs and anonymized records. The article shows a demonstration of the tool through a use case.

@article{coatrieux_lossless_2011,
	title = {Lossless watermarking of categorical attributes for verifying medical data base integrity},
	volume = {2011},
	copyright = {All rights reserved},
	issn = {1557-170X},
	doi = {10.1109/IEMBS.2011.6092021},
	abstract = {In this article, we propose a new lossless or reversible watermarking approach that allows the embedding of a message within categorical data of relational database. The reversibility property of our scheme is achieved by adapting the well known histogram shifting modulation. Based on this algorithm we derive a system for verifying the integrity of the database content, it means detecting addition, removal or modification of any t-uples or attributes. Such a content integrity check is independent of the manner the database is stored or structured. We illustrate the overall capability of our method and its constraints of deployment considering one medical database of inpatient hospital stay records. Especially, we reversibly watermark ICD-10 diagnostic codes.},
	language = {eng},
	journal = {Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference},
	author = {Coatrieux, G and Chazard, E and Beuscart, R and Roux, C},
	year = {2011},
	pmid = {22256244},
	keywords = {Algorithms, Computer Security, Humans, Medical Records Systems, Computerized},
	pages = {8195--8198},
}

In this article, we propose a new lossless or reversible watermarking approach that allows the embedding of a message within categorical data of relational database. The reversibility property of our scheme is achieved by adapting the well known histogram shifting modulation. Based on this algorithm we derive a system for verifying the integrity of the database content, it means detecting addition, removal or modification of any t-uples or attributes. Such a content integrity check is independent of the manner the database is stored or structured. We illustrate the overall capability of our method and its constraints of deployment considering one medical database of inpatient hospital stay records. Especially, we reversibly watermark ICD-10 diagnostic codes.

@article{marcilly_design_2011,
	title = {Design of {Adverse} {Drug} {Events}-{Scorecards}},
	volume = {164},
	copyright = {All rights reserved},
	issn = {0926-9630},
	abstract = {This paper presents the design of Adverse Drug Event-Scorecards. The scorecards described are innovative and novel, not having previously been reported in the literature. The Scorecards provide organizations (e.g. hospitals) with summary information about Adverse Drug Events (ADEs) using a Web-based platform. The data used in the Scorecards are routinely updated and report on ADEs detected through data mining processes. The development of the ADE Scorecards is ongoing and they are currently undergoing clinical testing.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Marcilly, Romaric and Chazard, Emmanuel and Beuscart-Zéphir, Marie-Catherine and Hackl, Werner and Băceanu, Adrian and Kushniruk, Andre and Borycki, Elizabeth M},
	year = {2011},
	pmid = {21335740},
	keywords = {Adverse Drug Reaction Reporting Systems, Data Mining, Internet, Quality Assurance, Health Care, Software Design, User-Computer Interface},
	pages = {377--381},
}

This paper presents the design of Adverse Drug Event-Scorecards. The scorecards described are innovative and novel, not having previously been reported in the literature. The Scorecards provide organizations (e.g. hospitals) with summary information about Adverse Drug Events (ADEs) using a Web-based platform. The data used in the Scorecards are routinely updated and report on ADEs detected through data mining processes. The development of the ADE Scorecards is ongoing and they are currently undergoing clinical testing.

@incollection{chazard_ade_2011-1,
	series = {Informatique et {Santé}},
	title = {Les «{ADE} {Scorecards}»: {Un} outil de détection par data mining des effets indésirables liés aux médicaments dans les dossiers médicaux (projet {PSIP})},
	copyright = {©2012 Springer-Verlag France S.A.R.L.},
	isbn = {978-2-8178-0284-8 978-2-8178-0285-5},
	shorttitle = {Les «{ADE} {Scorecards}»},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2011_jfim_adedetection_fr.pdf},
	abstract = {The automated detection of Adverse Drug Events (ADE) is an important issue in medical informatics. The objective of this work is to automatically detect ADEs and to present the results to physicians. 90,000 stays are extracted from the EHR of 5 French and Danish hospitals and loaded into a common repository, using a common data model. Then data mining procedures such as decision trees are used in order to get ADE detection rules that are filtered and validated by an expert committee. The procedure enables to produce 236 ADE detection rules that are able to detect 27 different kinds of outcomes. Contextualized statistics are computed for every rule in every medical department separately. The physicians of the medical departments are provided with that information by means of a web-based tool named “ADE Scorecards”. The tool is presented in the article through a use case and several screenshots. Based on a list of rules and a repository of stays, it allows for displaying the important rules, the related statistics, and the complete information about the suspicious cases. The knowledge is contextualized, i.e. it depends on the medical department. The tool is deployed in a French hospital and is currently being evaluated through a prospective impact assessment.},
	language = {fr},
	number = {1},
	urldate = {2016-01-24},
	booktitle = {Systèmes d’information pour l’amélioration de la qualité en santé},
	publisher = {Springer Paris},
	author = {Chazard, Emmanuel and Baceanu, Adrian and Ficheur, Grégoire and Marcilly, Romaric and Beuscart, Régis},
	editor = {Staccini, Pr Pascal M. and Harmel, Dr Ali and Darmoni, Pr Stéfan J. and Gouider, Pr Riadh},
	year = {2011},
	doi = {10.1007/978-2-8178-0285-5_16},
	keywords = {Adverse drug events, Biomedicine general, Computer Appl. in Administrative Data Processing, Data Mining, Database Management, Decision Trees, Electronic Health Records, Health Informatics, Information Systems and Communication Service, Management of Computing and Information Systems},
	pages = {177--188},
}

The automated detection of Adverse Drug Events (ADE) is an important issue in medical informatics. The objective of this work is to automatically detect ADEs and to present the results to physicians. 90,000 stays are extracted from the EHR of 5 French and Danish hospitals and loaded into a common repository, using a common data model. Then data mining procedures such as decision trees are used in order to get ADE detection rules that are filtered and validated by an expert committee. The procedure enables to produce 236 ADE detection rules that are able to detect 27 different kinds of outcomes. Contextualized statistics are computed for every rule in every medical department separately. The physicians of the medical departments are provided with that information by means of a web-based tool named “ADE Scorecards”. The tool is presented in the article through a use case and several screenshots. Based on a list of rules and a repository of stays, it allows for displaying the important rules, the related statistics, and the complete information about the suspicious cases. The knowledge is contextualized, i.e. it depends on the medical department. The tool is deployed in a French hospital and is currently being evaluated through a prospective impact assessment.

@article{ficheur_interoperability_2011,
	title = {Interoperability of medical databases: construction of mapping between hospitals laboratory results assisted by automated comparison of their distributions},
	volume = {2011},
	copyright = {All rights reserved},
	issn = {1942-597X},
	shorttitle = {Interoperability of medical databases},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2011_amia_interoperabilitymappinglaboratoryresults.pdf},
	abstract = {In hospital information systems, laboratory results are stored using specific terminologies which may differ between hospitals. The objective is to create a tool helping to build a mapping between a target terminology (reference dataset) and a new one. Using a training sample consisting of correct and incorrect correspondences between parameters of different hospitals, a match probability score is built. This model also enables to determine the theoretical conversion factor between two parameters. This method is evaluated on a test sample of a new hospital: For each reference parameter, best candidates are returned and sorted in decreasing order using the probability given by the model. The correct correspondent of 14 among 15 reference parameters are ranked in the top five among more than 70. All conversion factors are correct. A mapping webtool is built to present the essential information for best candidates. Using this tool, an expert has found all the correct pairs.},
	language = {eng},
	journal = {AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium},
	author = {Ficheur, Grégoire and Chazard, Emmanuel and Schaffar, Aurélien and Genty, Matthieu and Beuscart, Régis},
	year = {2011},
	pmid = {22195092},
	keywords = {Clinical Laboratory Information Systems, Databases, Factual, Hospital Information Systems, Laboratories, Hospital, Medical Record Linkage, Models, Statistical, Systems Integration, Vocabulary, Controlled},
	pages = {392--401},
}

In hospital information systems, laboratory results are stored using specific terminologies which may differ between hospitals. The objective is to create a tool helping to build a mapping between a target terminology (reference dataset) and a new one. Using a training sample consisting of correct and incorrect correspondences between parameters of different hospitals, a match probability score is built. This model also enables to determine the theoretical conversion factor between two parameters. This method is evaluated on a test sample of a new hospital: For each reference parameter, best candidates are returned and sorted in decreasing order using the probability given by the model. The correct correspondent of 14 among 15 reference parameters are ranked in the top five among more than 70. All conversion factors are correct. A mapping webtool is built to present the essential information for best candidates. Using this tool, an expert has found all the correct pairs.

@techreport{chazard_results_2010,
	title = {Results of data \& semantic mining. {PSIP} deliverable 2.3},
	institution = {European Research Council},
	author = {Chazard, Emmanuel and Preda, Cristian and Bernonille, Stéphanie and Băceanu, Adrian and Ficheur, Grégoire and Genty, Matthieu and Darmoni, Stefan and Sakji, Saoussen and Pereira, Suzanne and Tessier, Sophie and Saur, Francine and Serrot, Elisabeth and Kergourlay, Ivan and Beuscart, Regis and Cacciabue, Carlos},
	month = aug,
	year = {2010},
}

@techreport{andersen_final_2010,
	title = {Final set of {CDSS} modules. {PSIP} deliverable 5.2},
	institution = {European Research Council},
	author = {Andersen, Kenneth Skovhus and Koutkias, Vassilis and Frandsen, Jacob Roed and Jensen, Sanne and McNair, Peter and Baceanu, Adrian and Chazard, Emmanuel and Niès, Julie and Pereira, Suzanne},
	month = jul,
	year = {2010},
}

@article{chazard_detection_2010,
	title = {Détection et prévention des effets indésirables médicamenteux par fouille automatisée des dossiers patients électroniques},
	volume = {58, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762010000428},
	doi = {10.1016/j.respe.2010.02.013},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Chazard, E. and Salleron, J. and Génin, M. and Ficheur, G. and Duhamel, A.},
	month = apr,
	year = {2010},
	keywords = {Data-mining, Dossier patient électronique, Effets indésirables médicamenteux},
	pages = {S8},
}

@article{genty_reduction_2010,
	title = {Réduction du temps d’attente des patients et des médecins libéraux par mutualisation des patientèles en cabinet de groupe},
	volume = {58, Supplement 1},
	issn = {0398-7620},
	url = {http://www.sciencedirect.com/science/article/pii/S0398762010000829},
	doi = {10.1016/j.respe.2010.02.053},
	urldate = {2013-11-27},
	journal = {Revue d'Épidémiologie et de Santé Publique},
	author = {Genty, M. and Chazard, E. and Legrand, B. and Beuscart, R.},
	month = apr,
	year = {2010},
	keywords = {File d’attente, Médecine libérale, Simulation informatique},
	pages = {S21},
}

@article{beuscart_linnovation_2010,
	title = {De l’innovation au remboursement},
	volume = {31},
	issn = {1959-0318},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2010_irbm_innovationremboursement.pdf},
	doi = {10.1016/j.irbm.2009.11.004},
	abstract = {Résumé
Les dispositifs et procédés médicaux peuvent justifier un remboursement par l’Assurance Maladie, à condition qu’ils rendent le service attendu. À cette fin, le chemin est long de l’innovation au remboursement. L’industriel doit tout d’abord demander le marquage CE, après quoi le produit peut être commercialisé. L’Afssaps s’assure de la qualité du produit, du respect des standards et des normes et réalise des contrôles a posteriori, par exemple, de matériovigilance. Pour prétendre au remboursement, un dossier doit être présenté au ministère de la Santé et copie à la Haute Autorité de santé (HAS) pour la partie médicotechnique. Deux solutions s’offrent à l’industriel. Il peut demander la reconnaissance du dispositif dans le cadre d’un acte médical par la Commission d’évaluation des actes professionnels. L’acte impliquant le dispositif, s’il fait preuve de son efficacité, est inscrit sur la classification commune des actes médicaux. L’acte sera alors remboursé dans le cadre de la tarification à l’activité. L’autre possibilité est de demander l’évaluation par la Commission nationale d’évaluation des dispositifs médicaux et technologies de santé, autre instance de la HAS. Sur la base des données cliniques, cette commission délivre un avis sous forme d’une attestation de service attendu ou de service rendu permettant ultérieurement l’inscription sur la liste des produits et prestations remboursables. Ensuite le Comité économique des produits de santé, instance interministérielle, propose, après négociation, un prix ou un tarif pour le remboursement du dispositif ou du procédé. Cette démarche qui s’étale sur plusieurs années assure la qualité des produits et prestations remboursable, mais peut nuire, de par sa durée, à l’innovation technologique.

Medical devices and processes can be reimbursed by the health insurance system if they bring some added value for the patients. There is, however, a long way to go from innovation to reimbursement. The industry must obtain the CE mark in order to commercialize the product. The “Afssaps” verifies the product quality, the conformity to standards and norms, and follows its impact over time. To be reimbursed, the product application must be submitted to the “Haute Autorité de santé”, either by asking for its acceptation as a medical procedure by the “Commission d’évaluation des actes professionnels” (if approved it will be paid in relation to the subsequent activity) or by requesting the agreement of the “Commission nationale d’évaluation des dispositifs médicaux et technologies de santé”, which will be based on the expected/proved service, therefore authorizing its reimbursement as a medical device. The “Comité économique des produits de santé”, depending of the Health Ministry, after negociation, then gives a final approval and the corresponding price for reimbursement. This whole process can take several years, and guarantees the quality of products and prestations but may also have a negative impact on the innovations.},
	number = {1},
	urldate = {2013-11-27},
	journal = {IRBM},
	author = {Beuscart, R. and Chazard, E. and Souf, N.},
	month = feb,
	year = {2010},
	keywords = {Dispositif, Evaluation, Expected medical service, Medical device, Patient security, Service médical rendu, Sécurité du patient, Évaluation},
	pages = {26--29},
}

Résumé Les dispositifs et procédés médicaux peuvent justifier un remboursement par l’Assurance Maladie, à condition qu’ils rendent le service attendu. À cette fin, le chemin est long de l’innovation au remboursement. L’industriel doit tout d’abord demander le marquage CE, après quoi le produit peut être commercialisé. L’Afssaps s’assure de la qualité du produit, du respect des standards et des normes et réalise des contrôles a posteriori, par exemple, de matériovigilance. Pour prétendre au remboursement, un dossier doit être présenté au ministère de la Santé et copie à la Haute Autorité de santé (HAS) pour la partie médicotechnique. Deux solutions s’offrent à l’industriel. Il peut demander la reconnaissance du dispositif dans le cadre d’un acte médical par la Commission d’évaluation des actes professionnels. L’acte impliquant le dispositif, s’il fait preuve de son efficacité, est inscrit sur la classification commune des actes médicaux. L’acte sera alors remboursé dans le cadre de la tarification à l’activité. L’autre possibilité est de demander l’évaluation par la Commission nationale d’évaluation des dispositifs médicaux et technologies de santé, autre instance de la HAS. Sur la base des données cliniques, cette commission délivre un avis sous forme d’une attestation de service attendu ou de service rendu permettant ultérieurement l’inscription sur la liste des produits et prestations remboursables. Ensuite le Comité économique des produits de santé, instance interministérielle, propose, après négociation, un prix ou un tarif pour le remboursement du dispositif ou du procédé. Cette démarche qui s’étale sur plusieurs années assure la qualité des produits et prestations remboursable, mais peut nuire, de par sa durée, à l’innovation technologique. Medical devices and processes can be reimbursed by the health insurance system if they bring some added value for the patients. There is, however, a long way to go from innovation to reimbursement. The industry must obtain the CE mark in order to commercialize the product. The “Afssaps” verifies the product quality, the conformity to standards and norms, and follows its impact over time. To be reimbursed, the product application must be submitted to the “Haute Autorité de santé”, either by asking for its acceptation as a medical procedure by the “Commission d’évaluation des actes professionnels” (if approved it will be paid in relation to the subsequent activity) or by requesting the agreement of the “Commission nationale d’évaluation des dispositifs médicaux et technologies de santé”, which will be based on the expected/proved service, therefore authorizing its reimbursement as a medical device. The “Comité économique des produits de santé”, depending of the Health Ministry, after negociation, then gives a final approval and the corresponding price for reimbursement. This whole process can take several years, and guarantees the quality of products and prestations but may also have a negative impact on the innovations.

@article{koutkias_constructing_2010,
	title = {Constructing {Clinical} {Decision} {Support} {Systems} for {Adverse} {Drug} {Event} {Prevention}: {A} {Knowledge}-based {Approach}},
	volume = {2010},
	copyright = {All rights reserved},
	issn = {1942-597X},
	shorttitle = {Constructing {Clinical} {Decision} {Support} {Systems} for {Adverse} {Drug} {Event} {Prevention}},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2010_amia_constructingcdssforadeprevention.pdf},
	abstract = {A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.},
	language = {eng},
	journal = {AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium},
	author = {Koutkias, Vassilis and Kilintzis, Vassilis and Stalidis, George and Lazou, Katerina and Collyda, Chrysa and Chazard, Emmanuel and McNair, Peter and Beuscart, Regis and Maglaveras, Nicos},
	year = {2010},
	pmid = {21347009},
	pages = {402--406},
}

A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.

@article{merlin_can_2010,
	title = {Can {F}-{MTI} semantic-mined drug codes be used for adverse drug events detection when no {CPOE} is available?},
	volume = {160},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2010_medinfo_fmtimineddrugcodesadedetection.pdf},
	abstract = {BACKGROUND: Adverse Drug Events (ADEs) endanger the patients. Their detection and prevention is essential to improve the patients' safety. In the absence of computerized physician order entry (CPOE), discharge summaries are the only source of information about the drugs prescribed during a hospitalization. The French Multierminology Indexer (F-MTI) can help to extract drug-related information from those records.
METHODS: In first and second validation steps, the performance of the F-MTI tool is evaluated to extract ICD10 and ATC codes from free-text documents. In third step, potential ADE detection rules are used and the confidences of those rules are compared in several hospitals: using a CPOE vs. using semantic mining of free-text documents, diagnoses and lab results being available in both cases.
RESULTS: The F-MTI tool is able to extract ATC codes from documents. Moreover, the evaluation shows coherent and comparable results between the hospitals with CPOEs and the hospital with drugs information extracted from the reports for potential ADE detection.
CONCLUSION: semantic mining using F-MTI can help to identify previous cases of potential ADEs in absence of CPOE.},
	language = {eng},
	number = {Pt 2},
	journal = {Studies in health technology and informatics},
	author = {Merlin, Béatrice and Chazard, Emmanuel and Pereira, Suzanne and Serrot, Elisabeth and Sakji, Saoussen and Beuscart, Régis and Darmoni, Stefan},
	year = {2010},
	pmid = {20841839},
	keywords = {Adverse Drug Reaction Reporting Systems, Data Mining, Humans, International Classification of Diseases, Medical Order Entry Systems, Medication Errors, Pharmaceutical Preparations, Semantics, Software, Terminology as Topic},
	pages = {1025--1029},
}

BACKGROUND: Adverse Drug Events (ADEs) endanger the patients. Their detection and prevention is essential to improve the patients' safety. In the absence of computerized physician order entry (CPOE), discharge summaries are the only source of information about the drugs prescribed during a hospitalization. The French Multierminology Indexer (F-MTI) can help to extract drug-related information from those records. METHODS: In first and second validation steps, the performance of the F-MTI tool is evaluated to extract ICD10 and ATC codes from free-text documents. In third step, potential ADE detection rules are used and the confidences of those rules are compared in several hospitals: using a CPOE vs. using semantic mining of free-text documents, diagnoses and lab results being available in both cases. RESULTS: The F-MTI tool is able to extract ATC codes from documents. Moreover, the evaluation shows coherent and comparable results between the hospitals with CPOEs and the hospital with drugs information extracted from the reports for potential ADE detection. CONCLUSION: semantic mining using F-MTI can help to identify previous cases of potential ADEs in absence of CPOE.

@article{chazard_detection_2009,
	title = {Détection et prévention des effets indésirables liés aux médicaments par data-mining},
	volume = {30},
	issn = {1959-0318},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_irbm_dataminingeim_fr.pdf},
	doi = {10.1016/j.irbm.2009.05.008},
	abstract = {Résumé
Les effets indésirables liés aux médicaments causeraient 10 000 décès par an en France. Le plus souvent, la détection de ces effets repose sur les déclarations et l’écriture de règles d’alerte et de prévention est faite à dire d’expert lors de revues des dossiers. De plus, les spécificités des services ne sont pas prises en compte (patients, pratiques, connaissances). L’objectif du projet européen PSIP est d’utiliser le data-mining pour détecter ces effets et produire automatiquement les règles de contrôle, service par service. Sur 10 500 séjours danois et français, nous obtenons à ce jour 630 règles dont 75 sont validées. L’article présente un exemple d’arbre de décision et l’interprétation autour des précautions d’emploi des antivitamine K. L’exploitation des résultats ne s’entend qu’en contexte. Un procédé similaire pourrait être utilisé dans d’autres domaines.

Adverse drug events would be responsible from 10,000 death per year in France. Most often, detection relies on events declaration; alert and prevention rules are writen by experts thanks to cases reviews. Moreover, the medical departments’ specificities are not taken into account (patients, practices, knowledge). The objectives of the PSIP European project is to use data-mining to detect those events and automatically generate control rules, department by department. Using 10,500 French and Danish stays, we obtain till now 630 rules from which 75 have been validated. The article shows an example of a decision tree and its interpretation in the field of cautions taken during vitamin K antagonists’ use. Results’ exploitation cannot elude contextualization. A similar process may have many different uses.},
	number = {4},
	urldate = {2013-11-27},
	journal = {IRBM},
	author = {Chazard, E. and Preda, C. and Merlin, B. and Ficheur, G. and Beuscart, R.},
	month = sep,
	year = {2009},
	keywords = {Adverse drug events, Arbres de décision, Data-mining, Decision Trees, Effets indésirables des médicaments, Informatique médicale, Medical Informatics},
	pages = {192--196},
}

Résumé Les effets indésirables liés aux médicaments causeraient 10 000 décès par an en France. Le plus souvent, la détection de ces effets repose sur les déclarations et l’écriture de règles d’alerte et de prévention est faite à dire d’expert lors de revues des dossiers. De plus, les spécificités des services ne sont pas prises en compte (patients, pratiques, connaissances). L’objectif du projet européen PSIP est d’utiliser le data-mining pour détecter ces effets et produire automatiquement les règles de contrôle, service par service. Sur 10 500 séjours danois et français, nous obtenons à ce jour 630 règles dont 75 sont validées. L’article présente un exemple d’arbre de décision et l’interprétation autour des précautions d’emploi des antivitamine K. L’exploitation des résultats ne s’entend qu’en contexte. Un procédé similaire pourrait être utilisé dans d’autres domaines. Adverse drug events would be responsible from 10,000 death per year in France. Most often, detection relies on events declaration; alert and prevention rules are writen by experts thanks to cases reviews. Moreover, the medical departments’ specificities are not taken into account (patients, practices, knowledge). The objectives of the PSIP European project is to use data-mining to detect those events and automatically generate control rules, department by department. Using 10,500 French and Danish stays, we obtain till now 630 rules from which 75 have been validated. The article shows an example of a decision tree and its interpretation in the field of cautions taken during vitamin K antagonists’ use. Results’ exploitation cannot elude contextualization. A similar process may have many different uses.

@article{chazard_data-mining-based_2009,
	title = {Data-mining-based detection of adverse drug events},
	volume = {150},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_mie_dataminingade.pdf},
	abstract = {Every year adverse drug events (ADEs) are known to be responsible for 98,000 deaths in the USA. Classical methods rely on report statements, expert knowledge, and staff operated record review. One of our objectives, in the PSIP project framework, is to use data mining (e.g., decision trees) to electronically identify situations leading to risk of ADEs. 10,500 hospitalization records from Denmark and France were used. 500 rules were automatically obtained, which are currently being validated by experts. A decision support system to prevent ADEs is then to be developed. The article examines a decision tree and the rules in the field of vitamin K antagonists.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Preda, Cristian and Merlin, Béatrice and Ficheur, Grégoire and {PSIP consortium} and Beuscart, Régis},
	year = {2009},
	pmid = {19745372},
	keywords = {Anticoagulants, Databases, Factual, Decision Trees, Drug Toxicity, Information Storage and Retrieval, Medical Informatics, Vitamin K},
	pages = {552--556},
}

Every year adverse drug events (ADEs) are known to be responsible for 98,000 deaths in the USA. Classical methods rely on report statements, expert knowledge, and staff operated record review. One of our objectives, in the PSIP project framework, is to use data mining (e.g., decision trees) to electronically identify situations leading to risk of ADEs. 10,500 hospitalization records from Denmark and France were used. 500 rules were automatically obtained, which are currently being validated by experts. A decision support system to prevent ADEs is then to be developed. The article examines a decision tree and the rules in the field of vitamin K antagonists.

@article{leroy_toward_2009,
	title = {Toward automatic detection and prevention of adverse drug events},
	volume = {143},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_itch_towardautomaticdetection.pdf},
	abstract = {Adverse Drug Events (ADE) due to medication errors and human factors are a major public health issue. They endanger patient safety and cause considerable extra healthcare costs. The European project PSIP (Patient Safety through Intelligent Procedures in medication) aims to identify and prevent ADE. Data mining of the structured hospital data bases will give a list of observed ADE with frequencies and probabilities, thereby giving a better understanding of potential risks. The main objective of the project is to develop innovative knowledge based on the mining results and to deliver to professionals and patients, in the form of alerts and decision support functions, a contextualized knowledge fitting the local risk parameters.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Leroy, Nicolas and Chazard, Emmanuel and Beuscart, Régis and Beuscart-Zephir, Marie Catherine and {Psip Consortium}},
	year = {2009},
	pmid = {19380911},
	keywords = {Decision Support Systems, Clinical, Denmark, Drug Toxicity, France, Hospital Information Systems, Humans, Medical Audit},
	pages = {30--35},
}

Adverse Drug Events (ADE) due to medication errors and human factors are a major public health issue. They endanger patient safety and cause considerable extra healthcare costs. The European project PSIP (Patient Safety through Intelligent Procedures in medication) aims to identify and prevent ADE. Data mining of the structured hospital data bases will give a list of observed ADE with frequencies and probabilities, thereby giving a better understanding of potential risks. The main objective of the project is to develop innovative knowledge based on the mining results and to deliver to professionals and patients, in the form of alerts and decision support functions, a contextualized knowledge fitting the local risk parameters.