title: Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
abstract: BACKGROUND
  General practice based registration networks (GPRNs) provide information on population health derived from electronic health records (EHR). Morbidity estimates from different GPRNs reveal considerable, unexplained differences. Previous research showed that population characteristics could not explain this variation. In this study we investigate the influence of practice characteristics on the variation in incidence and prevalence figures between general practices and between GPRNs.
  
  
  METHODS
  We analyzed the influence of eight practice characteristics, such as type of practice, percentage female general practitioners, and employment of a practice nurse, on the variation in morbidity estimates of twelve diseases between six Dutch GPRNs. We used multilevel logistic regression analysis and expressed the variation between practices and GPRNs in median odds ratios (MOR). Furthermore, we analyzed the influence of type of EHR software package and province within one large national GPRN.
  
  
  RESULTS
  Hardly any practice characteristic showed an effect on morbidity estimates. Adjusting for the practice characteristics did also not alter the variation between practices or between GPRNs, as MORs remained stable. The EHR software package 'Medicom' and the province 'Groningen' showed significant effects on the prevalence figures of several diseases, but this hardly diminished the variation between practices.
  
  
  CONCLUSIONS
  Practice characteristics do not explain the differences in morbidity estimates between GPRNs.
authors.forename: C
authors.initials: C
authors.lastname: van den Dungen
authors.forename: N
authors.initials: N
authors.lastname: Hoeymans
authors.forename: M
authors.initials: M
authors.lastname: van den Akker
authors.forename: M C J
authors.initials: MC
authors.lastname: Biermans
authors.forename: K
authors.initials: K
authors.lastname: van Boven
authors.forename: J H K
authors.initials: JH
authors.lastname: Joosten
authors.forename: R A
authors.initials: RA
authors.lastname: Verheij
authors.forename: M W M
authors.initials: MW
authors.lastname: de Waal
authors.forename: F G
authors.initials: FG
authors.lastname: Schellevis
authors.forename: J A M
authors.initials: JA
authors.lastname: van Oers
mesh_terms: D057179:Advanced Practice Nursing / Q000706:statistics & numerical data; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005194:Family Practice / Q000706:statistics & numerical data*; D005260:Female; D058006:General Practice / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D009017:Morbidity; D055361:Multilevel Analysis; D009426:Netherlands / Q000453:epidemiology; D010822:Physicians, Women / Q000706:statistics & numerical data; D015995:Prevalence; D012042:Registries / Q000706:statistics & numerical data*