Fee-for-benefit: a strategy to improve the quality of health care and control costs through reimbursement incentives.
OBJECTIVE
The purpose of this study was to determine whether reimbursement in direct proportion to expected therapeutic benefit is capable of improving the utilization and cost of health care.


BACKGROUND
The benefit associated with a particular medical or surgical treatment varies widely from patient to patient. Nevertheless, payment to the provider of the treatment is essentially invariant under the current fee-for-service system. Under an alternative fee-for-benefit strategy, empiric data are used to construct a multivariate model to predict the expected benefit to an individual patient from a particular health care service on the basis of conventional clinical descriptors. The payers and the providers of the service then openly negotiate an explicit economic relation between expected benefit and monetary payment such that payment is directly proportional to benefit.


METHODS
Computer simulations were performed to determine the potential impact of this fee-for-benefit strategy with respect to medical versus surgical treatment of coronary artery disease.


RESULTS
Compared with conventional fee-for-service, fee-for-benefit resulted in a 12% improvement in patient benefit (quality-adjusted survival), a 22% reduction in provider payments and a 55% increase in cost/benefit (the ratio of benefit to payment).


CONCLUSIONS
The incentives embodied in a fee-for-benefit strategy can be an effective mechanism for encouraging more appropriate health care utilization while simultaneously controlling health care costs.
Diamond
G A
GA
Division of Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA 90048.
Denton
T A
TA
Matloff
J M
JM
D000206:Actuarial Analysis; D003198:Computer Simulation; D001026:Coronary Artery Bypass / Q000191:economics* / Q000401:mortality; D003327:Coronary Disease / Q000191:economics* / Q000401:mortality / Q000601:surgery; D003363:Cost Control; D003362:Cost-Benefit Analysis; D005251:Fees, Medical / Q000706:statistics & numerical data; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D008017:Life Expectancy; D017059:Models, Econometric; D017063:Outcome Assessment, Health Care / Q000191:economics*; D011446:Prospective Studies; D012052:Reimbursement, Incentive; D016019:Survival Analysis; D014481:United States; D026712:Value of Life