title: [Completeness assessment of the Breton registry of congenital abnormalities: A checking tool based on hospital discharge data].
abstract: BACKGROUND
  Exhaustiveness is required for registries. In the Breton registry of congenital abnormalities, cases are recorded at the source. We use hospital discharge data in order to verify the completeness of the registry. In this paper, we present a computerized tool for completeness assessment applied to the Breton registry.
  
  
  METHODS
  All the medical information departments were solicited once a year, asking for infant medical stays for newborns alive at one year old and for mother's stays if not. Files were transmitted by secure messaging and data were processed on a secure server. An identity-matching algorithm was applied and a similarity score calculated. When the record was not linked automatically or manually, the medical record had to be consulted. The exhaustiveness rate was assessed using the capture recapture method and the proportion of cases matched manually was used to assess the identity matching algorithm.
  
  
  RESULTS
  The computerized tool bas been used in common practice since June 2012 by the registry investigators. The results presented concerned the years 2011 and 2012. There were 470 potential cases identified from the hospital discharge data in 2011 and 538 in 2012, 35 new cases were detected in 2011 (32 children born alive and 3 stillborn), and 33 in 2012 (children born alive). There were respectively 85 and 137 false-positive cases. The theorical exhaustiveness rate reached 91% for both years. The rate of exact matching amounted to 68%; 6% of the potential cases were linked manually.
  
  
  CONCLUSIONS
  Hospital discharge databases contribute to the quality of the registry even though reports are made at the source. The implemented tool facilitates the investigator's work. In the future, use of the national identifying number, when allowed, should facilitate linkage between registry data and hospital discharge data.
authors.affiliation: Département d'information médicale, CHU de Rennes, 35033 Rennes, France; Inserm LTSI UMR 1099, équipe projet données massives en santé, faculté de médecine, université de Rennes 1, 35064 Rennes cedex, France. Electronic address: christine.riou@chu-rennes.fr.
authors.forename: C
authors.initials: C
authors.lastname: Riou
authors.affiliation: Registre des malformations congénitales de Bretagne, CHU de Rennes, Rennes, France.
authors.forename: F
authors.initials: F
authors.lastname: Rouget
authors.affiliation: Département d'information médicale, CHU de Rennes, 35033 Rennes, France.
authors.forename: J-P
authors.initials: JP
authors.lastname: Sinteff
authors.affiliation: Registre des malformations congénitales de Bretagne, CHU de Rennes, Rennes, France.
authors.forename: P
authors.initials: P
authors.lastname: Pladys
authors.affiliation: Inserm LTSI UMR 1099, équipe projet données massives en santé, faculté de médecine, université de Rennes 1, 35064 Rennes cedex, France; Centre d'investigation clinique, CHU de Rennes, 35033 Rennes, France.
authors.forename: M
authors.initials: M
authors.lastname: Cuggia
mesh_terms: D000013:Congenital Abnormalities / Q000453:epidemiology*; D003625:Data Collection; D016208:Databases, Factual; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008499:Medical Records; D010351:Patient Discharge; D012042:Registries
keywords: Congenital abnormalities; Hospital discharge database; Informatique médicale; Malformations congénitales; Medical informatics application; PMSI; Rapprochement d’identités; Record linkage; Registre; Registry