title: [Evaluation of medical information systems as a mean of identification of incident cases of colorectal cancer].
abstract: BACKGROUND
  Cancer registries are a reliable source of data to estimate national cancer incidence rates, but they are not always available in all regions. This study assessed the value of medical information systems (PMSI) to identify incident cases of colorectal cancer
  
  
  METHODS
  Two algorithms were elaborated to identify these incident cases in the PMSI database. The first algorithm was based on diagnosis and medical procedure codes and the second algorithm was based exclusively on diagnoses and the absence of diagnoses over the last five years. The results obtained for two departments were compared with those derived from two cancer registries, constituting the reference data. We then elaborated two multivariate logistic regression models to correct the national number of incident cases estimated by the algorithm adopted after evaluation of the results.
  
  
  RESULTS
  The first algorithm provided results that were very close to those derived from the regional registries (646 vs 645 cases) with a good sensitivity and positive predictive value of 75%. The second algorithm overestimated the incidence by about 50% with a positive predictive value of 60% and was therefore not adopted for the national estimation. By applying the first algorithm to the national PMSI MCO database (medicine, surgery, obstetrics), and after modelling, the estimated incidence differed by only 2.34% compared to that observed by all 14 registries. The national estimation of cancer incidence was 39,122 [37,020; 41,224] cases for 2005, which is consistent with the figure published by the Francim national registry network (37,413).
  
  
  CONCLUSIONS
  This study demonstrates the value of PMSI data for estimation of national incidence rates for certain cancers in the absence of cancer registries. However, raw data must be corrected and can be achieved by the method proposed here.
authors.forename: Catherine
authors.initials: C
authors.lastname: Quantin
authors.forename: Eric
authors.initials: E
authors.lastname: Benzenine
authors.forename: Mathieu
authors.initials: M
authors.lastname: Hägi
authors.forename: Bertrand
authors.initials: B
authors.lastname: Auverlot
authors.forename: Michal
authors.initials: M
authors.lastname: Abrahamowicz
authors.forename: Jonathan
authors.initials: J
authors.lastname: Cottenet
authors.forename: Evelyne
authors.initials: E
authors.lastname: Fournier
authors.forename: Christine
authors.initials: C
authors.lastname: Binquet
authors.forename: Delphine
authors.initials: D
authors.lastname: Compain
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Monnet
authors.forename: Anne-Manie
authors.initials: AM
authors.lastname: Bouvier
authors.forename: Arlette
authors.initials: A
authors.lastname: Danzon
mesh_terms: D000465:Algorithms; D015179:Colorectal Neoplasms / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D007256:Information Systems; D012042:Registries