title: Impact of remuneration and organizational factors on completing preventive manoeuvres in primary care practices.
abstract: BACKGROUND
  Several jurisdictions attempting to reform primary care have focused on changes in physician remuneration. The goals of this study were to compare the delivery of preventive services by practices in four primary care funding models and to identify organizational factors associated with superior preventive care.
  
  
  METHODS
  In a cross-sectional study, we included 137 primary care practices in the province of Ontario (35 fee-for-service practices, 35 with salaried physicians [community health centres], 35 practices in the new capitation model [family health networks] and 32 practices in the established capitation model [health services organizations]). We surveyed 288 family physicians. We reviewed 4108 randomly selected patient charts and assigned prevention scores based on the proportion of eligible preventive manoeuvres delivered for each patient.
  
  
  RESULTS
  A total of 3284 patients were eligible for at least one of six preventive manoeuvres. After adjusting for patient profile and contextual factors, we found that, compared with prevention scores in practices in the new capitation model, scores were significantly lower in fee-for-service practices (β estimate for effect on prevention score = -6.3, 95% confidence interval [CI] -11.9 to -0.6) and practices in the established capitation model (β = -9.1, 95% CI -14.9 to -3.3) but not for those with salaried remuneration (β = -0.8, 95% CI -6.5 to 4.8). After accounting for physician characteristics and organizational structure, the type of funding model was no longer a statistically significant factor. Compared with reference practices, those with at least one female family physician (β = 8.0, 95% CI 4.2 to 11.8), a panel size of fewer than 1600 patients per full-time equivalent family physician (β = 6.8, 95% CI 3.1 to 10.6) and an electronic reminder system (β = 4.6, 95% CI 0.4 to 8.7) had superior prevention scores. The effect of these three factors was largely but not always consistent across the funding models; it was largely consistent across the preventive manoeuvres.
  
  
  CONCLUSIONS
  No funding model was clearly associated with superior preventive care. Factors related to physician characteristics and practice structure were stronger predictors of performance. Practices with one or more female physicians, a smaller patient load and an electronic reminder system had superior prevention scores. Our findings raise questions about reform initiatives aimed at increasing patient numbers, but they support the adoption of information technology.
authors.affiliation: Department of Family Medicine, University of Ottawa, C.T. Lamont Primary Health Care Research Centre, Ottawa, Ont. sdahrouge@bruyere.org
authors.forename: Simone
authors.initials: S
authors.lastname: Dahrouge
authors.forename: William E
authors.initials: WE
authors.lastname: Hogg
authors.forename: Grant
authors.initials: G
authors.lastname: Russell
authors.forename: Meltem
authors.initials: M
authors.lastname: Tuna
authors.forename: Robert
authors.initials: R
authors.lastname: Geneau
authors.forename: Laura K
authors.initials: LK
authors.lastname: Muldoon
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Kristjansson
authors.forename: John
authors.initials: J
authors.lastname: Fletcher
mesh_terms: D000704:Analysis of Variance; D002204:Capitation Fee / Q000458:organization & administration / Q000706:statistics & numerical data; D016009:Chi-Square Distribution; D003153:Community Health Services / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D018588:Fee-for-Service Plans / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D009864:Ontario; D010818:Practice Patterns, Physicians' / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D011314:Preventive Health Services / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D011320:Primary Health Care / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D060926:Remuneration; D012737:Sex Factors