Publications plus anciennes

@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_les_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{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_les_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.

@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.

@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{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{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{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{chazard_detection_2009-1,
	title = {Detection of adverse drug events detection: data aggregation and data mining},
	volume = {148},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {Detection of adverse drug events detection},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_psip_decisiontrees.pdf},
	abstract = {Adverse drug events (ADEs) are a public health issue. The objective of this work is to data-mine electronic health records in order to automatically identify ADEs and generate alert rules to prevent those ADEs. The first step of data-mining is to transform native and complex data into a set of binary variables that can be used as causes and effects. The second step is to identify cause-to-effect relationships using statistical methods. After mining 10,500 hospitalizations from Denmark and France, we automatically obtain 250 rules, 75 have been validated till now. The article details the data aggregation and an example of decision tree that allows finding several rules in the field of vitamin K antagonists.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Ficheur, Grégoire and Merlin, Béatrice and Genin, Michael and Preda, Cristian and {PSIP consortium} and Beuscart, Régis},
	year = {2009},
	pmid = {19745237},
	keywords = {Data Collection, Data Mining, Denmark, Drug Toxicity, France, Humans, Medical Records Systems, Computerized},
	pages = {75--84},
}

Adverse drug events (ADEs) are a public health issue. The objective of this work is to data-mine electronic health records in order to automatically identify ADEs and generate alert rules to prevent those ADEs. The first step of data-mining is to transform native and complex data into a set of binary variables that can be used as causes and effects. The second step is to identify cause-to-effect relationships using statistical methods. After mining 10,500 hospitalizations from Denmark and France, we automatically obtain 250 rules, 75 have been validated till now. The article details the data aggregation and an example of decision tree that allows finding several rules in the field of vitamin K antagonists.

@article{baceanu_expert_2009,
	title = {The expert explorer: a tool for hospital data visualization and adverse drug event rules validation},
	volume = {148},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {The expert explorer},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_psip_expertexplorer.pdf},
	abstract = {An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Băceanu, Adrian and Atasiei, Ionuţ and Chazard, Emmanuel and Leroy, Nicolas and {PSIP Consortium}},
	year = {2009},
	pmid = {19745238},
	keywords = {Data Mining, Drug Toxicity, Hospital Information Systems, Humans, Internet, Reproducibility of Results, Software Design},
	pages = {85--94},
}

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

@article{chazard_adverse_2009,
	title = {Adverse drug events prevention rules: multi-site evaluation of rules from various sources},
	volume = {148},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {Adverse drug events prevention rules},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_psip_rulesrepository.pdf},
	abstract = {Adverse drug events are a public health issue (98,000 deaths in the USA every year). Some computerized physician order entry (CPOEs) coupled with clinical decision support systems (CDSS) allow to prevent ADEs thanks to decision rules. Those rules can come from many sources: academic knowledge, record reviews, and data mining. Whatever their origin, the rules may induce too numerous alerts of poor accuracy when identically applied in different places. In this work we formalized rules from various sources in XML and enforced their execution on several medical departments to evaluate their local confidence. The article details the process and shows examples of evaluated rules from various sources. Several needs are enlightened to improve confidences: segmentation, contextualization, and evaluation of the rules over time.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Ficheur, Grégoire and Merlin, Béatrice and Serrot, Elisabeth and {PSIP Consortium} and Beuscart, Régis},
	year = {2009},
	pmid = {19745240},
	keywords = {Data Mining, Decision Making, Decision Support Systems, Clinical, Drug Toxicity, Guidelines as Topic, Humans, Medical Order Entry Systems, Safety Management, Systems Integration},
	pages = {102--111},
}

Adverse drug events are a public health issue (98,000 deaths in the USA every year). Some computerized physician order entry (CPOEs) coupled with clinical decision support systems (CDSS) allow to prevent ADEs thanks to decision rules. Those rules can come from many sources: academic knowledge, record reviews, and data mining. Whatever their origin, the rules may induce too numerous alerts of poor accuracy when identically applied in different places. In this work we formalized rules from various sources in XML and enforced their execution on several medical departments to evaluate their local confidence. The article details the process and shows examples of evaluated rules from various sources. Several needs are enlightened to improve confidences: segmentation, contextualization, and evaluation of the rules over time.

@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.

@article{chazard_detection_2009-2,
	title = {Detection of adverse drug events: proposal of a data model},
	volume = {148},
	copyright = {All rights reserved},
	issn = {0926-9630},
	shorttitle = {Detection of adverse drug events},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2009_psip_datamodel.pdf},
	abstract = {Our main objective is to detect adverse drug events (ADEs) in former hospital stays. As ADEs are rare, that supposes to screen thousands of electronic health records (EHRs). For that purpose, we need to define a data model that has two main objectives: (1) being able to describe hospital stays from various hospitals (2) being tuned so as to prepare the data mining process: as ADEs are not flagged in the datasets, the data model must be optimized for ADE detection. The article presents the phases of the design and the data model that results from this work. It is compatible with many hospitals. It deals with diagnoses, drug prescriptions, lab results and administrative information. It allows for data mining and ADE detection in EHRs.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Merlin, Béatrice and Ficheur, Grégoire and Sarfati, Jean-Charles and {PSIP Consortium} and Beuscart, Régis},
	year = {2009},
	pmid = {19745236},
	keywords = {Data Mining, Decision Support Techniques, Drug Toxicity, Electronic Health Records, Humans},
	pages = {63--74},
}

Our main objective is to detect adverse drug events (ADEs) in former hospital stays. As ADEs are rare, that supposes to screen thousands of electronic health records (EHRs). For that purpose, we need to define a data model that has two main objectives: (1) being able to describe hospital stays from various hospitals (2) being tuned so as to prepare the data mining process: as ADEs are not flagged in the datasets, the data model must be optimized for ADE detection. The article presents the phases of the design and the data model that results from this work. It is compatible with many hospitals. It deals with diagnoses, drug prescriptions, lab results and administrative information. It allows for data mining and ADE detection in EHRs.

@techreport{chazard_first_2008,
	title = {First results of data mining. {PSIP} deliverable 2.1.},
	institution = {European Research Council},
	author = {Chazard, Emmanuel and Preda, Cristian and Beuscart, Regis and Băceanu, Adrian and Niculescu, C},
	month = aug,
	year = {2008},
}

@techreport{bernard_structures_2008,
	title = {Structures and {Data} {Models} of the {Data} repositories available in the {PSIP} project. {PSIP} deliverable 1},
	institution = {European Research Council},
	author = {Bernard, Olivier and Koncar, M and Sarfati, Jean-Charles and Chazard, Emmanuel and Niès, Julie},
	month = apr,
	year = {2008},
}

@article{grenier_p107_2008,
	title = {P107 Évaluation rétrospective de 20 ans d’activité d’une unité de diabétologie centrée sur une éducation thérapeutique du patient – Étude préliminaire},
	volume = {34, Supplement 3},
	issn = {1262-3636},
	url = {http://www.sciencedirect.com/science/article/pii/S1262363608730192},
	doi = {10.1016/S1262-3636(08)73019-2},
	abstract = {Objectif
Cette unité a été créée en 1983 et fonctionne en ambulatoire. Son activité est centrée sur le suivi à long terme des patients avec une large place à l’éducation thérapeutique associée au suivi curatif et au bilan d’évolutivité. Cette étude a pour objectif d’évaluer l’impact de cette structure sur l’équilibre et l’apparition des complications chez les patients. Nous avons analysé de façon rétrospective le contenu d’une base de données renseignée à chaque passage d’un patient (consultation, hôpital de jour, hôpital de semaine).
Résultats
Les résultats retrouvent une augmentation du nombre de consultation. Le nombre de patients distincts pris en charge par an augmente. La file active (3 780 patients) est composée de 80,2 \% de diabétiques de type 2 et 14,3 \% de type 1, les 5,5 \% restant correspondant au diabète gestationnel ou secondaire. Avec le temps, les diabétiques sont adressés plus tôt dans leur maladie avec une HbA1C et une glycémie à jeun plus basse. L’analyse des résultats de l’HbA1C montre chez les diabétiques de type 1, une forte décroissance les 2 000 premiers jours et chez les diabétiques de type 2 dans les 500 premiers jours, puis on assiste à une discrète décroissance dans les 2 types de diabète à long terme. La fréquence des complications est la suivante ( \% type 1/ \% type 2) : rétinopathie (40,85/16,78), rénales (45,32/41,51), clairance de la créatinine inférieure à 60 ml/mn (20,4/23,3), neuropathie (20,33/23,5), trouble trophique (23,88/22,51), dyslipidémie (17,53/34,28), cardiaque (2,23/8,86), AVC (0,9/1,81), HTA (11,75/29,24).
Conclusion
Notre unité propose à l’analyse un suivi plus proche des recommandations de l’HAS que celui constaté dans l’étude ENTRED en 2001 et ce depuis 1989. Cette étude conclut que l’évaluation reste la clé pour déterminer l’impact de l’éducation thérapeutique sur la santé des patients et qu’une étude prospective est souhaitable. Il semble qu’à partir de ce modèle, une généralisation de ce suivi et cette évaluation est à envisager pour toutes les maladies chroniques.},
	urldate = {2013-11-27},
	journal = {Diabetes \& Metabolism},
	author = {Grenier, J.L. and d’Escrivan, N. and Vincent, D. and Chazard, E. and Lepeut, M.},
	month = mar,
	year = {2008},
	pages = {H74},
}

Objectif Cette unité a été créée en 1983 et fonctionne en ambulatoire. Son activité est centrée sur le suivi à long terme des patients avec une large place à l’éducation thérapeutique associée au suivi curatif et au bilan d’évolutivité. Cette étude a pour objectif d’évaluer l’impact de cette structure sur l’équilibre et l’apparition des complications chez les patients. Nous avons analysé de façon rétrospective le contenu d’une base de données renseignée à chaque passage d’un patient (consultation, hôpital de jour, hôpital de semaine). Résultats Les résultats retrouvent une augmentation du nombre de consultation. Le nombre de patients distincts pris en charge par an augmente. La file active (3 780 patients) est composée de 80,2 % de diabétiques de type 2 et 14,3 % de type 1, les 5,5 % restant correspondant au diabète gestationnel ou secondaire. Avec le temps, les diabétiques sont adressés plus tôt dans leur maladie avec une HbA1C et une glycémie à jeun plus basse. L’analyse des résultats de l’HbA1C montre chez les diabétiques de type 1, une forte décroissance les 2 000 premiers jours et chez les diabétiques de type 2 dans les 500 premiers jours, puis on assiste à une discrète décroissance dans les 2 types de diabète à long terme. La fréquence des complications est la suivante ( % type 1/ % type 2) : rétinopathie (40,85/16,78), rénales (45,32/41,51), clairance de la créatinine inférieure à 60 ml/mn (20,4/23,3), neuropathie (20,33/23,5), trouble trophique (23,88/22,51), dyslipidémie (17,53/34,28), cardiaque (2,23/8,86), AVC (0,9/1,81), HTA (11,75/29,24). Conclusion Notre unité propose à l’analyse un suivi plus proche des recommandations de l’HAS que celui constaté dans l’étude ENTRED en 2001 et ce depuis 1989. Cette étude conclut que l’évaluation reste la clé pour déterminer l’impact de l’éducation thérapeutique sur la santé des patients et qu’une étude prospective est souhaitable. Il semble qu’à partir de ce modèle, une généralisation de ce suivi et cette évaluation est à envisager pour toutes les maladies chroniques.

@phdthesis{chazard_emmanuel_data_2008,
	address = {Paris, France},
	type = {Mémoire de {Master} 2},
	title = {Data {Mining} et prévention des effets indésirables liés aux médicaments},
	url = {http://www.chazard.org/emmanuel/pdf_articles/thesis_master_2008_m2msr_chazard.pdf},
	abstract = {Les effets indésirables liés aux médicaments entraîneraient 10 000 décès par an en France. Leur prévention à l’hôpital repose sur les systèmes de prescription connectés (CPOE) couplés à des systèmes d’aide à la décision (CDSS). Les règles d’alertes de CDSS sont écrites à dire d’expert et génèreraient des alertes trop fréquentes et peu adaptées donc mal suivies. Le projet PSIP (Patient Safety through Intelligent Procedures in medication) propose entre autres de générer ces règles d’après la fouille automatisée des données (data mining), afin de constituer des règles d’alertes basées sur les erreurs passées du service. Ces règles seront ensuite validées par une revue experte de dossiers. Ce mémoire évoque les premières phases : conception du modèle de données, analyses statistique (31 arbres de décision) et premiers résultats (223 règles).},
	language = {Fr},
	school = {Université Paris Sud, Paris XI},
	author = {{Chazard, Emmanuel}},
	year = {2008},
}

Les effets indésirables liés aux médicaments entraîneraient 10 000 décès par an en France. Leur prévention à l’hôpital repose sur les systèmes de prescription connectés (CPOE) couplés à des systèmes d’aide à la décision (CDSS). Les règles d’alertes de CDSS sont écrites à dire d’expert et génèreraient des alertes trop fréquentes et peu adaptées donc mal suivies. Le projet PSIP (Patient Safety through Intelligent Procedures in medication) propose entre autres de générer ces règles d’après la fouille automatisée des données (data mining), afin de constituer des règles d’alertes basées sur les erreurs passées du service. Ces règles seront ensuite validées par une revue experte de dossiers. Ce mémoire évoque les premières phases : conception du modèle de données, analyses statistique (31 arbres de décision) et premiers résultats (223 règles).

@article{chazard_graphical_2007,
	title = {Graphical representation of the comprehensive patient flow through the hospital},
	copyright = {All rights reserved},
	issn = {1942-597X},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2007_amia_comprehensivepatientflow.pdf},
	abstract = {Representing the patient flow through the hospital is quite a difficult task, considering the amount of data to be taken into account. In this article, some usual visual representations are first shown, then new charts are proposed. Several real examples are given. Those charts have been implemented in a web-based query interface, using PHP5 and generating SVG outputs on the fly, without any a priori knowledge. These charts allow for representing a large amount of data on the same graph: the occupancy of each medical department, their linking and transfers, allowing to display the whole care sequence. SVG, an XML-based free vector graphics format, allows rich end-user interaction. Practical applications: length of stay reducing, cost reducing, cost breakdown, further statistical study, administrative authorizations.},
	language = {eng},
	journal = {AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium},
	author = {Chazard, Emmanuel and Beuscart, Régis},
	year = {2007},
	pmid = {18693808},
	keywords = {Computer Graphics, Hospital Administration, Hospitalization, Humans, Patient Transfer, Programming Languages},
	pages = {110--114},
}

Representing the patient flow through the hospital is quite a difficult task, considering the amount of data to be taken into account. In this article, some usual visual representations are first shown, then new charts are proposed. Several real examples are given. Those charts have been implemented in a web-based query interface, using PHP5 and generating SVG outputs on the fly, without any a priori knowledge. These charts allow for representing a large amount of data on the same graph: the occupancy of each medical department, their linking and transfers, allowing to display the whole care sequence. SVG, an XML-based free vector graphics format, allows rich end-user interaction. Practical applications: length of stay reducing, cost reducing, cost breakdown, further statistical study, administrative authorizations.

@article{puech_dicomworks_2007,
	title = {{DicomWorks} {Teleradiology}: secure transmission of medical images over the internet at low cost},
	volume = {2007},
	copyright = {All rights reserved},
	issn = {1557-170X},
	shorttitle = {{DicomWorks} {Teleradiology}},
	doi = {10.1109/IEMBS.2007.4353899},
	abstract = {We developed a completely secured teleradiology solution tailored for e-mail teleradiology applications at low-cost. Data processing consists in creating a couple of files with an encrypted and compressed image archive and a 128 bits decoding key file. No proprietary file format or encryption scheme is used. Files are exchanged using the e-mail (SMTP and POP) protocols, but FTP or sFTP can be used for better performances. Software includes original features such as real-time interactive JPEG compression, instant archive preview or secured data cleanup when a user logs off. We believe that this flexible, integrated and easy to use solution is a robust alternative to more complex architectures for simple image transmissions or occasional circumstances.},
	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 = {Puech, Philippe and Chazard, Emmanuel and Lemaitre, Laurent and Beuscart, Regis},
	year = {2007},
	pmid = {18003565},
	keywords = {Biomedical imaging, Costs, Costs and Cost Analysis, Couplings, Decoding, Diagnostic Imaging, DicomWorks teleradiology, Image coding, Internet, POP protocol, Protocols, SMTP protocol, Telemedicine, Teleradiology, compressed image archive, cryptography, data communication, data processing, decoding key file, electronic mail, encrypted image archive, instant archive preview, low cost e-mail teleradiology applications, medical administrative data processing, radiology, realtime interactive JPEG compression, secure medical image transmission, secured data cleanup, secured teleradiology solution, storage capacity 128 bit},
	pages = {6706--6709},
}

We developed a completely secured teleradiology solution tailored for e-mail teleradiology applications at low-cost. Data processing consists in creating a couple of files with an encrypted and compressed image archive and a 128 bits decoding key file. No proprietary file format or encryption scheme is used. Files are exchanged using the e-mail (SMTP and POP) protocols, but FTP or sFTP can be used for better performances. Software includes original features such as real-time interactive JPEG compression, instant archive preview or secured data cleanup when a user logs off. We believe that this flexible, integrated and easy to use solution is a robust alternative to more complex architectures for simple image transmissions or occasional circumstances.

@article{chazard_using_2006,
	title = {Using {Treemaps} to represent medical data},
	volume = {124},
	copyright = {All rights reserved},
	issn = {0926-9630},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2006_mie_treemaps.pdf},
	abstract = {Confronted with the inadequacy of traditional charts, we tested the contribution of Treemaps to the representation of medical data. Treemap charts allow description of large hierarchical collections of quantitative data, on a synthetic way. Treemaps were implemented using PHP5, and were tested in the field of DRG-mining and other medical informations. From now on, this implementation is used in an interactive web-based request tool, and could be used to design interactive piloting tools.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Chazard, Emmanuel and Puech, Philippe and Gregoire, Marc and Beuscart, Régis},
	year = {2006},
	pmid = {17108571},
	keywords = {Computer Graphics, France, Medical Informatics, Software},
	pages = {522--527},
}

Confronted with the inadequacy of traditional charts, we tested the contribution of Treemaps to the representation of medical data. Treemap charts allow description of large hierarchical collections of quantitative data, on a synthetic way. Treemaps were implemented using PHP5, and were tested in the field of DRG-mining and other medical informations. From now on, this implementation is used in an interactive web-based request tool, and could be used to design interactive piloting tools.

@phdthesis{deseine_etude_2006,
	address = {Lille ; 1969-2017, France},
	type = {Thèse d'exercice},
	title = {Etude rétrospective de 17 ans d'activité du {Centre} d'éducation pour le traitement du diabète et des maladies de la nutrition du {CHG} de {Roubaix}: traitement de base de données, analyse, indicateurs d'utilité},
	shorttitle = {Etude rétrospective de 17 ans d'activité du {Centre} d'éducation pour le traitement du diabète et des maladies de la nutrition du {CHG} de {Roubaix}},
	abstract = {Le CETRADIMN (Centre d’Education pour le Traitement du Diabète et des Maladies de la Nutrition), rattaché au CHG de Roubaix, propose une prise en charge ambulatoire complète des patients diabétiques, en complément avec la médecine de ville. Le CETRADIMN dispose d’une base de données épidémiologique renseignée depuis 1988, conçue dans un système de gestion de base de données orienté objet. Ce travail s’articule autour de trois axes : 1-réaliser une extraction et un nettoyage de la base de données existante afin de permettre une exploitation rétrospective et participer à la migration des anciennes données vers le nouveau système d’information ; exposer les outils de récupération d’une base ; discuter des moyens permettant de garantir la cohérence et l’intégrité des données 2-porter un regard rétrospectif statique et dynamique sur l’activité, les patients, les pratiques et le réseau de médecins correspondants du CETRADIMN, plus particulièrement dans le domaine de la prise en charge des patients diabétiques ; exposer les spécificités du recrutement du CETRADIMN 3-proposer et tester in situ des indicateurs d'utilité, à l’aide de méthodes statistiques de régressions, d’analyses harmoniques et d’analyses de données longitudinales. Nous proposons et testons un indicateur de formation des médecins correspondants, un indicateur d'application des recommandations de suivi de la HAS et, après une modélisation des profils individuels et moyens d'évolution de l'HbA1c, un indicateur de contrôle glycémique à long terme.},
	language = {français},
	school = {Université du droit et de la santé},
	author = {Deseine, Anne-Sophie and Chazard, Emmanuel and Legrand, Bertrand},
	collaborator = {Grenier, Jean-Louis},
	year = {2006},
	keywords = {Diabète -- Dissertation universitaire, Diabétiques -- Thèses et écrits académiques, Maladies de la nutrition -- Thèses et écrits académiques, Maladies métaboliques et nutritionnelles -- Dissertation universitaire, Éducation des patients -- Thèses et écrits académiques, Éducation du patient comme sujet -- Dissertation universitaire},
}

Le CETRADIMN (Centre d’Education pour le Traitement du Diabète et des Maladies de la Nutrition), rattaché au CHG de Roubaix, propose une prise en charge ambulatoire complète des patients diabétiques, en complément avec la médecine de ville. Le CETRADIMN dispose d’une base de données épidémiologique renseignée depuis 1988, conçue dans un système de gestion de base de données orienté objet. Ce travail s’articule autour de trois axes : 1-réaliser une extraction et un nettoyage de la base de données existante afin de permettre une exploitation rétrospective et participer à la migration des anciennes données vers le nouveau système d’information ; exposer les outils de récupération d’une base ; discuter des moyens permettant de garantir la cohérence et l’intégrité des données 2-porter un regard rétrospectif statique et dynamique sur l’activité, les patients, les pratiques et le réseau de médecins correspondants du CETRADIMN, plus particulièrement dans le domaine de la prise en charge des patients diabétiques ; exposer les spécificités du recrutement du CETRADIMN 3-proposer et tester in situ des indicateurs d'utilité, à l’aide de méthodes statistiques de régressions, d’analyses harmoniques et d’analyses de données longitudinales. Nous proposons et testons un indicateur de formation des médecins correspondants, un indicateur d'application des recommandations de suivi de la HAS et, après une modélisation des profils individuels et moyens d'évolution de l'HbA1c, un indicateur de contrôle glycémique à long terme.

@phdthesis{chazard_emmanuel_les_2006,
	address = {Lille, France},
	type = {Mémoire de {Master} 2},
	title = {Les représentations graphiques, support de la décision de gestion hospitalière},
	url = {http://www.chazard.org/emmanuel/pdf_articles/thesis_master_2006_m2mess_chazard.pdf},
	abstract = {Les outils graphiques sont abondamment utilisés dans la gestion des établissements hospitaliers. La complexité et l’abondance des données pose deux problèmes : 
1- les fautes méthodologiques sont fréquentes lors du choix du graphique 
2- les graphiques traditionnels ne suffisent plus à synthétiser ces données 
 Le présent mémoire prend le prétexte de 8 cas pratiques de gestion hospitalière pour montrer quelles erreurs méthodologiques ne pas commettre lors du choix du graphique, montrer comment outrepasser les limites des tableurs, et enfin proposer des graphiques innovants. Certaines de ces créations originales, programmées pour l’occasion, auront un débouché industriel.},
	language = {Fr},
	school = {Université des Sciences et Technologies, Lille 1},
	author = {{Chazard, Emmanuel}},
	year = {2006},
}

Les outils graphiques sont abondamment utilisés dans la gestion des établissements hospitaliers. La complexité et l’abondance des données pose deux problèmes : 1- les fautes méthodologiques sont fréquentes lors du choix du graphique 2- les graphiques traditionnels ne suffisent plus à synthétiser ces données Le présent mémoire prend le prétexte de 8 cas pratiques de gestion hospitalière pour montrer quelles erreurs méthodologiques ne pas commettre lors du choix du graphique, montrer comment outrepasser les limites des tableurs, et enfin proposer des graphiques innovants. Certaines de ces créations originales, programmées pour l’occasion, auront un débouché industriel.

@phdthesis{chazard_emmanuel_dind_2005,
	address = {Lille, France},
	type = {Mémoire de {Master} 2},
	title = {{DIND} {PMSI} : {Dind} {Is} {Not} {Datim} - {Système} de détection d’atypies dans les fichiers de {RSS}},
	url = {http://www.chazard.org/emmanuel/pdf_articles/thesis_master_2005_m2iirs_chazard.pdf},
	language = {Fr},
	school = {Université du Droit et de la Santé, Lille 2},
	author = {{Chazard, Emmanuel}},
	year = {2005},
}