Avoiding doubles in distributed nominative medical databases: optimization of the needleman and wunsch algorithm.
Difficulties in reconstituting patients' trajectory in the public health information systems are raised by errors in patients' identification processes. A crucial issue to achieve is avoiding doubles in distributed web databases. We explored Needleman and Wunsch (N&W) algorithm in order to optimize the properties of string matching. Five variants of the N&W algorithm were developed. The algorithms were implemented for a web Multi-Source Information System. This system was dedicated to tracking patients with End-Stage Renal Disease at both regional and national level. A simulated study database of 73,210 records was created. An insertion or suppression of each character of the original string was simulated. The rate of double entries was 2% given an acceptable distance set to 5 modifications. The search was sensitive and specific with an acceptable detection time. It detected up to 10% of modifications that is above the estimated error rate. A variant of the N&W algorithm designed as "cut-off heuristic", proved to be efficient for the search of double entries occurring in nominative distributed databases.
Le Mignot
Loïc
L
Université Paris-Descartes, Faculté de Médecine; Assistance Publique-Hôpitaux de Paris; Hôpital Necker, EA222, Service de Biostatistique et d'Informatique Médicale, Hôpital Necker, 149 rue de Sèvres, Paris, France.
Mugnier
Claude
C
Saïd
Mohamed Ben
MB
Jais
Jean-Philippe
JP
Richard
Jean-Baptiste
JB
Le Bihan-Benjamin
Christine
C
Taupin
Pierre
P
Landais
Paul
P
D000465:Algorithms; D003195:Computer Communication Networks; D016208:Databases, Factual; D006801:Humans