Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?

BMC Family Practice

Research Article

C van den Dungen¹  JAM van Oers²  M van den Akker³  JHK Joosten⁴  MCJ Biermans⁵  K van Boven⁶  MWM de Waal⁷  FG Schellevis⁸  N Hoeymans⁹  RA Verheij^1,10 

[1] Department Tranzo, Faculty of Social and Behavioural Sciences, Tilburg University, 5000 LE, Tilburg, The Netherlands;Department Tranzo, Faculty of Social and Behavioural Sciences, Tilburg University, 5000 LE, Tilburg, The Netherlands;National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands;Department of Family Medicine, School for Public Health and Primary Care (Caphri), Maastricht University, Maastricht, The Netherlands;Department of General Practice, KU Leuven, Leuven, Belgium;Department of General Practice and Elderly Care Medicine, The Academic Network of General Practitioners of the VU University, VU University Medical Centre, Amsterdam, The Netherlands;Department of Primary and Community Care, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands;Department of Primary and Community Care, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands;General Practitioner, Franeker, The Netherlands;Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands;Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands;Department of General Practice & Elderly Care Medicine/EMGO Institute for health and care research, VU University Medical Centre, Amsterdam, The Netherlands;National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands;Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands;

关键词: Family practice;    Incidence;    Electronic medical records;    Practice characteristics;    Population health;    Prevalence;   

DOI  :  10.1186/s12875-014-0176-7

 received in 2014-05-06, accepted in 2014-10-10,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundGeneral 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.MethodsWe 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.ResultsHardly 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.ConclusionPractice characteristics do not explain the differences in morbidity estimates between GPRNs.

【 授权许可】

CC BY   
© van den Dungen et al.; licensee BioMed Central Ltd. 2014