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1. Remote Monitoring of Cardiac Implantable Devices: Ontology Driven Classification of the Alerts

Author

Rosier, Arnaud, Mabo, Philippe, Temal, Lynda, van Hille, Pascal, Dameron, Olivier, Deléger, Louise, Grouin, Cyril, Zweigenbaum, Pierre, Jacques, Julie, Chazard, Emmanuel, Laporte, Laure, Henry, Christine, Burgun, Anita, CIC-IT Rennes, Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de cardiologie et maladies vasculaires [Rennes] = Cardiac, Thoracic, and Vascular Surgery [Rennes], CHU Pontchaillou [Rennes], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Dynamics, Logics and Inference for biological Systems and Sequences (Dyliss), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris Saclay (COmUE)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Université Paris-Sud - Paris 11 (UP11), Alicante [Seclin], Université de Lille, Droit et Santé, Sorin Group [Clamart], Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Centre de Recherche des Cordeliers (CRC (UMR_S 872)), Université Paris Descartes - Paris 5 (UPD5)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche des Cordeliers (CRC), Université Paris Diderot - Paris 7 (UPD7)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de cardiologie et maladies vasculaires, Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-CHU Pontchaillou [Rennes], Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec, Université Paris-Sud - Paris 11 (UP11)-Université Paris-Saclay-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7)-École pratique des hautes études (EPHE)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Hôpital Pontchaillou-CHU Pontchaillou [Rennes], Laboratoire Traitement du Signal et de l'Image ( LTSI ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Dynamics, Logics and Inference for biological Systems and Sequences ( Dyliss ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -GESTION DES DONNÉES ET DE LA CONNAISSANCE ( IRISA-D7 ), Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), CentraleSupélec-Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Télécom Bretagne-Institut National des Sciences Appliquées ( INSA ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -École normale supérieure - Rennes ( ENS Rennes ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bretagne Sud ( UBS ) -CentraleSupélec-Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Télécom Bretagne-Institut National des Sciences Appliquées ( INSA ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -École normale supérieure - Rennes ( ENS Rennes ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bretagne Sud ( UBS ) -Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Télécom Bretagne-Institut National des Sciences Appliquées ( INSA ) -École normale supérieure - Rennes ( ENS Rennes ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bretagne Sud ( UBS ), Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur ( LIMSI ), Université Paris-Sud - Paris 11 ( UP11 ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Medical Information and Archives (CHU Lille, Université de Lille Nord de France), Hôpital Européen Georges Pompidou [APHP] ( HEGP ), Centre de Recherche des Cordeliers ( CRC (UMR_S 872) ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Centre de Recherche des Cordeliers ( CRC ), and Université Paris Diderot - Paris 7 ( UPD7 ) -École pratique des hautes études ( EPHE ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM )

Subjects
Pacemaker, Artificial, Reproducibility of Results, Pilot Projects, Decision Support Systems, Clinical, Sensitivity and Specificity, Telemedicine, Defibrillators, Implantable, Biological Ontologies, Clinical Alarms, Therapy, Computer-Assisted, Atrial Fibrillation, Electrocardiography, Ambulatory, Electronic Health Records, Humans, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Diagnosis, Computer-Assisted, [ SDV.IB ] Life Sciences [q-bio]/Bioengineering, Natural Language Processing
Abstract

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

Published
2016

2. Lossless watermarking of categorical attributes for verifying medical data base integrity

Author

Gouenou Coatrieux, C. Roux, Régis Beuscart, Emmanuel Chazard, Télécom Bretagne (devenu IMT Atlantique), Ex-Bibliothèque, Département Image et Traitement Information (ITI), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Laboratoire de Traitement de l'Information Medicale (LaTIM), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Mines-Télécom [Paris] (IMT), Department of Medical Information and Archives, and Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)

Subjects
Lossless compression, 021110 strategic, defence & security studies, Information retrieval, Medical Records Systems, Computerized, Property (programming), Relational database, Computer science, 0211 other engineering and technologies, Watermark, 02 engineering and technology, Watermarking, computer.software_genre, Histogram, Data integrity, 0202 electrical engineering, electronic engineering, information engineering, Humans, 020201 artificial intelligence & image processing, Data mining, Digital watermarking, computer, Categorical variable, Algorithms, Computer Security
Abstract

International audience; 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.

Published
2011

3. Impact of previous REnal TRansplantation on the mid-term renal Outcome after CARdiac surgery: the RETROCAR trial.

Author

Beurton A, Fajardie A, Rubin S, Belnou P, Aguerreche C, Pernot M, Mion S, Imbault J, and Ouattara A

Subjects
Humans, Postoperative Complications epidemiology, Renal Dialysis adverse effects, Retrospective Studies, Risk Factors, Acute Kidney Injury epidemiology, Cardiac Surgical Procedures adverse effects, Kidney Transplantation adverse effects
Abstract

Background: Acute kidney injury (AKI) is one of the most common complications after cardiac surgery with cardiopulmonary bypass (CPB). Renal transplant recipients (RTRs) have a higher risk of cardiac surgery-associated AKI (CSA-AKI). A relationship has been strongly suggested between AKI and poor long-term graft survival. The main objective was to evaluate the impact of on-pump cardiac surgery on the 1-year renal allograft survival rate., Methods: The study population consisted of 37 RTRs and 56 non-RTRs who underwent cardiac surgery between 1 January 2010 and 31 December 2019. They were matched according to age, sex, preoperative glomerular function, diabetes and type of surgery. The primary composite outcome was renal survival, defined as patient survival without the requirement for permanent dialysis or new kidney transplantation at 1 year after surgery., Results: The renal survival rate was significantly lower in the RTR group than in the non-RTR group [81% versus 96%; odds ratio 0.16 (95% confidence interval 0.03-0.82), P = .03]. The proportion of patients who returned to permanent dialysis was higher in the RTR group than in the non-RTR group (12% versus 0%; P = .02). The proportion of patients with severe AKI was also higher in the RTR group. At 1 year after surgery, serum creatinine level, glomerular filtration rate and all-cause mortality rates were comparable between both groups., Conclusion: Patients with a functional renal allograft have a low 1-year renal allograft survival rate after cardiac surgery with CPB. In addition, these patients have significant risks of AKI and acute kidney disease after open-heart surgery., (© The Author(s) 2022. Published by Oxford University Press on behalf of the ERA.)

Published
2023
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4. Risk Factors of Midterm Mortality After Aortic Valve Replacement for Severe Calcified Tricuspid Aortic Valve Stenosis: A retrospective analysis of Perioperative Events Assessment in Adult Cardiac surgery (PESSAC) Registry.

Author

Beurton A, Ferté T, Mion S, Besnard T, Jecker O, Remy A, Labrousse L, and Ouattara A

Subjects
Adult, Aortic Valve diagnostic imaging, Aortic Valve surgery, Humans, Male, Registries, Retrospective Studies, Risk Assessment, Risk Factors, Treatment Outcome, Aortic Valve Stenosis diagnostic imaging, Aortic Valve Stenosis surgery, Cardiac Surgical Procedures adverse effects, Heart Valve Prosthesis Implantation
Abstract

Objective: The European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) initially developed for predicting early postoperative mortality of all types of cardiac surgery, is less able to predict, more specifically, long-term outcomes after aortic valve replacement (AVR). The study authors here evaluated the risk factors for three-year mortality after isolated aortic valve replacement (AVR) for severe calcified tricuspid aortic valve stenosis and compared them with EuroSCORE II to predict long-term outcomes., Design: A retrospective study., Setting: A university teaching hospital., Participants: This study included 1,101 adults who underwent isolated AVR for severe calcified tricuspid aortic valve stenosis between September 2010 to June 2015., Interventions: None., Measurements and Main Results: The primary endpoint was that of three-year all-cause mortality after AVR. By three years, 168 patients (15.3%) had died. Risk factors for all-cause mortality were: male gender (odds ratio [OR] = 1.78; 95% confidence interval [CI] = 1.21-2.62; p < 0.01), peripheral arterial disease (OR = 1.77; 95% CI = 1.08-2.92; p = 0.03), age (OR = 1.06 per year increase; 95% CI =1.04-1.09; p < 0.01), pulmonary artery systolic pressure (OR = 1.02 per mmHg increase; 95% CI = 1.01-1.03; p < 0.01), platelet count (OR = 1.003 per G/L increase; 95% CI = 1.000-1.005; p = 0.04), and valve area (OR = 0.97 per cm²/m² increase; 95% CI= 0.95-0.99; p < 0.01). The area under the receiver operating characteristic curves were 0.67 (95% CI = 0.60-0.75) and 0.60 (95% CI = 0.56-0.65) for the authors' logistic regression model and EuroSCORE II, respectively (p = 0.11)., Conclusions: The study authors identified six independent risk factors for three-year mortality after isolated AVR. The logistic regression model had relatively modest predictive performance for three-year mortality., Competing Interests: Conflict of Interest None., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Published
2021
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5. Inappropriate anticholinergic drugs prescriptions in older patients: analysing a hospital database.

Author

Ferret L, Ficheur G, Delaviez E, Luyckx M, Quenton S, Beuscart R, Chazard E, and Beuscart JB

Subjects
Aged, Aged, 80 and over, Cohort Studies, Constipation chemically induced, Constipation epidemiology, Databases, Factual statistics & numerical data, Drug Utilization statistics & numerical data, Female, France epidemiology, Hospitals, General statistics & numerical data, Humans, Inappropriate Prescribing statistics & numerical data, Male, Retrospective Studies, Cholinergic Antagonists adverse effects, Databases, Factual trends, Drug Utilization trends, Hospitals, General trends, Inappropriate Prescribing trends
Abstract

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

Published
2018
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6. Impact of acute geriatric care in elderly patients according to the Screening Tool of Older Persons' Prescriptions/Screening Tool to Alert doctors to Right Treatment criteria in northern France.

Author

Frély A, Chazard E, Pansu A, Beuscart JB, and Puisieux F

Subjects
Aged, Aged, 80 and over, Female, France, Hospitalization, Humans, Male, Polypharmacy, Prospective Studies, Geriatrics, Inappropriate Prescribing prevention & control, Inappropriate Prescribing statistics & numerical data
Abstract

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

Published
2016
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7. The ADE scorecards: a tool for adverse drug event detection in electronic health records.

Author

Chazard E, Băceanu A, Ferret L, and Ficheur G

Subjects
Humans, Information Systems organization & administration, Data Mining methods, Drug-Related Side Effects and Adverse Reactions prevention & control, Internet, Medical Records Systems, Computerized organization & administration
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.

Published
2011

8. Interoperability of medical databases: construction of mapping between hospitals laboratory results assisted by automated comparison of their distributions.

Author

Ficheur G, Chazard E, Schaffar A, Genty M, and Beuscart R

Subjects
Databases, Factual, Laboratories, Hospital, Models, Statistical, Systems Integration, Clinical Laboratory Information Systems, Hospital Information Systems organization & administration, Medical Record Linkage, Vocabulary, Controlled
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.

Published
2011

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