Evaluation of syndromic algorithms for detecting patients with potentially transmissible infectious diseases based on computerised emergency-department data

BMC Medical Informatics and Decision Making

Research Article

Stefan Darmoni¹  Anne-Laure Millet²  Véronique Potinet-Pagliaroli³  Marie-Hélène Metzger⁴  Solweig Gerbier-Colomban⁵  Christophe Riou⁶  Jacqueline Grando⁷  Quentin Gicquel⁸ 

[1] CISMeF, LITIS EA 4108 - Université de Rouen, F-76031, Rouen cedex, France;Hospices Civils de Lyon, Direction Système d’Information et Informatique, F-69500, Bron, France;Hospices Civils de Lyon, Hôpital de la Croix-Rousse, Service des urgences, F-69317, Lyon, France;Hospices Civils de Lyon, Hôpital de la Croix-Rousse, Unité d’hygiène et d’épidémiologie, F-69317, Lyon, France;Université de Lyon, F-69000, Lyon; Université Lyon 1; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622, Villeurbanne, France;Hospices Civils de Lyon, Hôpital de la Croix-Rousse, Unité d’hygiène et d’épidémiologie, F-69317, Lyon, France;Université de Lyon, F-69000, Lyon; Université Lyon 1; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622, Villeurbanne, France;Service d’Hygiène, Épidémiologie et Prévention, Hôpital de la Croix-Rousse, 103, Grande-Rue de la Croix-Rousse, F-69317, Lyon Cedex 04, France;Hospices Civils de Lyon, Pôle Information Médicale Evaluation Recherche, F-69424, Lyon, France;Hospices Civils de Lyon, Hôpital de la Croix-Rousse, Service des urgences, F-69317, Lyon, France;Hospices Civils de Lyon, Service d’hygiène et d’épidémiologie, F-69565, Saint-Genis-Laval, France;Université de Lyon, F-69000, Lyon; Université Lyon 1; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622, Villeurbanne, France;

关键词: Emergency service;    Hospital;    Syndromic surveillance;    Detection algorithm;    Infection control;    Sensitivity and specificity;    Population surveillance;   

DOI  :  10.1186/1472-6947-13-101

 received in 2012-12-17, accepted in 2013-08-30,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundThe objective of this study was to ascertain the performance of syndromic algorithms for the early detection of patients in healthcare facilities who have potentially transmissible infectious diseases, using computerised emergency department (ED) data.MethodsA retrospective cohort in an 810-bed University of Lyon hospital in France was analysed. Adults who were admitted to the ED and hospitalised between June 1, 2007, and March 31, 2010 were included (N=10895). Different algorithms were built to detect patients with infectious respiratory, cutaneous or gastrointestinal syndromes. The performance parameters of these algorithms were assessed with regard to the capacity of our infection-control team to investigate the detected cases.ResultsFor respiratory syndromes, the sensitivity of the detection algorithms was 82.70%, and the specificity was 82.37%. For cutaneous syndromes, the sensitivity of the detection algorithms was 78.08%, and the specificity was 95.93%. For gastrointestinal syndromes, the sensitivity of the detection algorithms was 79.41%, and the specificity was 81.97%.ConclusionsThis assessment permitted us to detect patients with potentially transmissible infectious diseases, while striking a reasonable balance between true positives and false positives, for both respiratory and cutaneous syndromes. The algorithms for gastrointestinal syndromes were not specific enough for routine use, because they generated a large number of false positives relative to the number of infected patients. Detection of patients with potentially transmissible infectious diseases will enable us to take precautions to prevent transmission as soon as these patients come in contact with healthcare facilities.

【 授权许可】

CC BY   
© Gerbier-Colomban et al.; licensee BioMed Central Ltd. 2013