title: [Comparing results of methicillin-resistant Staphylococcus aureus (MRSA) surveillance using the French DRG-based information system (PMSI)].
abstract: BACKGROUND
  The surveillance of methicillin-resistant Staphylococcus aureus (MRSA) is a national priority. The rate of MRSA infections is one of six indicators tracked by the Department of Health. Since 2002, the French institute for public health surveillance (InVS) has monitored MRSA infections to estimate incidence density. Today, the use of the French administrative database (PMSI) could facilitate this surveillance. The aim of this study was to compare MRSA incidence density computed at a national level using PMSI databases with the results from the InVS taken as the reference.
  
  
  METHODS
  PMSI databases for the years 2006 to 2009 were used. The reference results were those published by the InVS from 2006 to 2009. MRSA density defined as the number of MRSA infections recorded per year over 1000 hospital stays was computed. It was then compared with the MRSA incidence density measured by InVS. The time course of MRSA incidence in the PMSI records was modeled using a Poisson regression.
  
  
  RESULTS
  The incidence density measured by the InVS was higher than the MRSA density computed using the PMSI, but this difference appeared to decrease over time. The PMSI density/InVS MRSA incidence density ratio was 0.8% in 2006 and about 9.2% in 2009. We observed inverted trends with a growing trend in MRSA density identified by the PMSI. Furthermore, the year of study was significantly associated with incidence density (P=0.01).
  
  
  CONCLUSIONS
  Using PMSI data as an additional source of information in the hospital MRSA surveillance process makes it possible to detect and analyze patient repeats at the regional and national levels with linkage facilities. Estimation of incidence density for hospitals not participating to this surveillance system will be the next step.
authors.affiliation: Service de biostatistique et d'informatique médicale, CHU de Dijon, CHRU, 21000 Dijon, France.
authors.forename: G
authors.initials: G
authors.lastname: Nuemi
authors.forename: K
authors.initials: K
authors.lastname: Astruc
authors.forename: S
authors.initials: S
authors.lastname: Aho
authors.forename: C
authors.initials: C
authors.lastname: Quantin
mesh_terms: D016000:Cluster Analysis; D003428:Cross Infection / Q000453:epidemiology; D016208:Databases, Factual / Q000592:standards / Q000706:statistics & numerical data*; D003953:Diagnosis-Related Groups / Q000706:statistics & numerical data*; D005602:France / Q000453:epidemiology; D006761:Hospitals / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D007902:Length of Stay / Q000706:statistics & numerical data; D016347:Medical Records Systems, Computerized / Q000592:standards / Q000706:statistics & numerical data*; D055624:Methicillin-Resistant Staphylococcus aureus; D011159:Population Surveillance / Q000379:methods*; D013203:Staphylococcal Infections / Q000191:economics / Q000453:epidemiology*
keywords: Cross infection; Diagnosis related groups (DRG); Hospital information systems; Infection croisée; Methicillin-resistant Staphylococcus aureus (MRSA); Population surveillance; Programme de médicalisation du système d’information (PMSI); Regression analysis; Régression; Staphylococcus aureus résistant à la méticilline (SARM); Surveillance