title: Effect of prospective reimbursement on nursing home costs.
abstract: OBJECTIVE
  This study evaluates the effect of Maine's Medicaid nursing home prospective payment system on nursing home costs and access to care for public patients.
  
  
  METHODS
  The implementation of a facility-specific prospective payment system for nursing homes provided the opportunity for longitudinal study of the effect of that system. Data sources included audited Medicaid nursing home cost reports, quality-of-care data from state facility survey and licensure files, and facility case-mix information from random, stratified samples of homes and residents. Data were obtained for six years (1979-1985) covering the three-year period before and after implementation of the prospective payment system.
  
  
  METHODS
  This study used a pre-post, longitudinal analytical design in which interrupted, time-series regression models were estimated to test the effects of prospective payment and other factors, e.g., facility characteristics, nursing home market factors, facility case mix, and quality of care, on nursing home costs.
  
  
  RESULTS
  Prospective payment contributed to an estimated $3.03 decrease in total variable costs in the third year from what would have been expected under the previous retrospective cost-based payment system. Responsiveness to payment system efficiency incentives declined over the study period, however, indicating a growing problem in achieving further cost reductions. Some evidence suggested that cost reductions might have reduced access for public patients.
  
  
  CONCLUSIONS
  Study findings are consistent with the results of other studies that have demonstrated the effectiveness of prospective payment systems in restraining nursing home costs. Potential policy trade-offs among cost containment, access, and quality assurance deserve further consideration, particularly by researchers and policymakers designing the new generation of case mix-based and other nursing home payment systems.
authors: Edmund S. Muskie Institute of Public Affairs, University of Southern Maine, Portland 04103.
authors: A F
authors: AF
authors: Coburn
authors: R
authors: R
authors: Fortinsky
authors: C
authors: C
authors: McGuire
authors: T P
authors: TP
authors: McDonald
mesh_terms: D003363:Cost Control; D003362:Cost-Benefit Analysis; D003953:Diagnosis-Related Groups / Q000706:statistics & numerical data; D017048:Health Care Costs / Q000706:statistics & numerical data / Q000639:trends; D015276:Health Care Rationing / Q000191:economics / Q000706:statistics & numerical data; D006276:Health Facility Size / Q000706:statistics & numerical data; D006297:Health Services Accessibility / Q000191:economics*; D006302:Health Services Research; D006801:Humans; D008137:Longitudinal Studies; D008281:Maine; D008484:Medicaid / Q000592:standards*; D008485:Medical Audit / Q000706:statistics & numerical data; D009735:Nursing Homes / Q000145:classification / Q000191:economics*; D010067:Ownership / Q000706:statistics & numerical data; D011445:Prospective Payment System / Q000592:standards*; D011785:Quality Assurance, Health Care / Q000706:statistics & numerical data; D012044:Regression Analysis; D014481:United States; D016526:Workload / Q000706:statistics & numerical data