Physician and hospital funding options in a public system with decreasing resources

Physician and hospital funding options in a public system with decreasing resources

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Article ID: iaor20032402
Country: Netherlands
Volume: 37
Issue: 1
Start Page Number: 45
End Page Number: 68
Publication Date: Mar 2003
Journal: Socio-Economic Planning Sciences
Authors: ,
Keywords: financial, programming: goal
Abstract:

Methods of physician and hospital reimbursement have been the subject of many debates over the years. Structuring a method of payment for physicians under a publicly funded system is particularly difficult when considered in relation to methods of hospital funding. In this paper, we present a mathematical model that simulates physician and hospital behaviour in a publicly funded health care system under a variety of funding scenarios. The model assumes both doctors and hospitals are constrained profit satisficers. Given this assumption, and a reduction in funding to the institution, the model searches for a resource allocation that will achieve target incomes for both decision-making groups through changes to case mix and/or reductions in the fixed or variable costs of production. Results indicate that when physicians are funded on a fee-for-service basis, the hospital funding method in place may have little impact on resource allocation following a budget reduction. When physicians are funded via salary, conflict between the two groups is reduced, but under-supply is more likely to occur. These results raise important questions regarding the type of hospital funding model that should be in place. Unlike earlier approaches, our model jointly simulates the behaviour of both hospitals and health care providers. By including both actors, it provides a mechanism for investigating the interaction between physicians and hospitals under a variety of funding scenarios. Given that hospital–physician systems respond to funding reductions by reducing the fixed costs of production or by decreasing the variable costs of production, the model can be used to identify a range of alternative case mix, case cost, and cost-sharing scenarios.

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