Which practice characteristics are associated with the quality of cardiovascular disease prevention in European primary care?
1 Department of General Practice and Health Services Research, University Hospital of Heidelberg, Voßstrasse 2, D-69115 Heidelberg, Germany
2 University of Manchester, Health Sciences – Primary Care Group, Williamson Building, |Manchester M13 9PL UK
3 Medical School University of Ljubljana, Department of Family medicine, Poljanski nasip 58, Ljubljana 1000, Slovenia
4 University of Heidelberg, Institute of Meedical Biometry and Informatics, Im Neuenheimer Feld 120, Heidelberg D-69120, Germany
5 Radboud University Nijmegen Medical Centre, Scientific Institute for Quality of Healthcare, P.O. Box 9101, Nijmegen 6500 HB The Netherlands
Implementation Science 2013, 8:27 doi:10.1186/1748-5908-8-27Published: 9 March 2013
Prevention of cardiovascular diseases (CVD) is a major health issue worldwide. Primary care plays an important role in cardiovascular risk management (CVRM). Guidelines and quality of care measures to assess CVRM in primary care practices are available. In this study, we assessed the relationship between structural and organisational practice characteristics and the quality of care provided in individuals at high risk for developing CVD in European primary care.
An observational study was conducted in 267 general practices from 9 European countries. Previously developed quality indicators were abstracted from medical records of randomly sampled patients to create a composite quality measure. Practice characteristics were collected by a practice questionnaire and face to face interviews. Data were aggregated using factor analysis to four practice scores representing structural and organisational practice features. A hierarchical multilevel analysis was performed to examine the impact of practice characteristics on quality of CVRM.
The final sample included 4223 individuals at high risk for developing CVD (28% female) with a mean age of 66.5 years (SD 9.1). Mean indicator achievement was 59.9% with a greater variation between practices than between countries. Predictors at the patient level (age, gender) had no influence on the outcome. At the practice level, the score ‘Preventive Services’ (13 items) was positively associated with clinical performance (r = 1.92; p = 0.0058). Sensitivity analyses resulted in a 5-item score (PrevServ_5) that was also positively associated with the outcome (r = 4.28; p < 0.0001).
There was a positive association between the quality of CVRM in individuals at high risk for developing CVD and the availability of preventive services related to risk assessment and lifestyle management supported by information technology.