A controlled trial of the effect of a prepaid group practice on use of services

N Engl J Med. 1984 Jun 7;310(23):1505-10. doi: 10.1056/NEJM198406073102305.

Abstract

Does a prepaid group practice deliver less care than the fee-for-service system when both serve comparable populations with comparable benefits? To answer this question, we randomly assigned a group of 1580 persons to receive care free of charge from either a fee-for-service physician of their choice (431 persons) or the Group Health Cooperative of Puget Sound (1149 persons). In addition, 733 prior enrollees of the Cooperative were studied as a control group. The rate of hospital admissions in both groups at the Cooperative was about 40 per cent less than in the fee-for-service group (P less than 0.01), although ambulatory-visit rates were similar. The calculated expenditure rate for all services was about 25 per cent less in the two Cooperative groups (P less than 0.01 for the experimental group, P less than 0.05 for the control group). The number of preventive visits was higher in the prepaid groups, but this difference does not explain the reduced hospitalization. The similarity of use between the two prepaid groups suggests that the mix of health risks at the Cooperative was similar to that in the fee-for-service system. The lower rate of use that we observed, along with comparable reductions found in non-controlled studies by others, suggests that the style of medicine at prepaid group practices is markedly less "hospital-intensive" and, consequently, less expensive.

Publication types

  • Clinical Trial
  • Comparative Study
  • Randomized Controlled Trial
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Fees, Medical
  • Group Practice, Prepaid / statistics & numerical data
  • Health Maintenance Organizations / economics
  • Health Maintenance Organizations / statistics & numerical data*
  • Hospitalization
  • Humans
  • Insurance, Health / statistics & numerical data
  • Office Visits
  • Preventive Health Services / statistics & numerical data
  • Random Allocation
  • Research Design
  • Statistics as Topic
  • Washington