The effect of capitation on switching primary care physicians.
OBJECTIVE
To examine the relationship between patient case-mix, utilization, primary care physician (PCP) payment method, and the probability that patients switch their PCPs.


METHODS
Administrative enrollment and claims/encounter data for 1994-1995 from four physician organizations.


METHODS
We developed a conceptual model of patient switching behavior, which we used to guide the specification of multivariate logistic analyses focusing on interactions between patient case-mix, utilization, and PCP reimbursement methods.


METHODS
Claims data were aggregated to the encounter level; a switch was defined as a change in PCP since the previous encounter. The PCPs were reimbursed on either a capitated or fee-for-service (FFS) basis.


RESULTS
Patients with stable chronic conditions (Ambulatory Diagnostic Groups [ADG] 10) and capitated PCPs were 36 percent more likely to switch PCPs than similar patients with FFS PCPs, controlling for patient age and sex and physician fixed effects. When the number of previous encounters was included in the model this relationship was no longer significant. Instead high utilizers with capitated PCPs were significantly more likely to switch PCPs than were similar patients with FFS PCPs.


CONCLUSIONS
A patient's demographics and utilization are associated with the probability that the patient will switch PCPs. Capitated PCP payment was associated with higher rates of switching among high utilizers of health care resources. These findings raise concerns about the continuity and quality of care experienced by vulnerable patients in an era of changing financial incentives.
Sorbero
Melony E S
ME
University of Rochester School of Medicine and Dentistry, Department of Community and Preventive Medicine, NY 14642, USA.
Dick
Andrew W
AW
Zwanziger
Jack
J
Mukamel
Dana
D
Weyl
Nancy
N
D000328:Adult; D000704:Analysis of Variance; D002140:California; D002204:Capitation Fee; D003657:Decision Making; D005194:Family Practice / Q000191:economics* / Q000706:statistics & numerical data; D018588:Fee-for-Service Plans; D005260:Female; D006801:Humans; D007061:Idaho; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009518:New York; D009820:Ohio; D017060:Patient Satisfaction / Q000191:economics / Q000706:statistics & numerical data*; D020400:Provider-Sponsored Organizations / Q000191:economics* / Q000706:statistics & numerical data; D011785:Quality Assurance, Health Care; D013997:Time Factors