Paying healthcare providers: an agency-theoretic approach to chronic disease management
Open Access
- Author:
- Mata, Aurore-Laetitia
- Graduate Program:
- Industrial Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- None
- Committee Members:
- Dr Nembhard, Thesis Advisor/Co-Advisor
Harriet Black Nembhard, Thesis Advisor/Co-Advisor - Keywords:
- chronic disease
healthcare financing
principal-agent - Abstract:
- The overall quality of healthcare delivered to Americans is suboptimal. The increasing prevalence of chronic disease exacerbates these problems representing a significant challenge for the healthcare system. Moreover there is a misalignment between healthcare provider‘s compensation and high quality care. The use of financial incentives varies according to whether providers receive their base compensation by fee-for-service, capitation or mixed payment. The purpose of this study is to develop a theoretical model to design an optimal payment system, linking base compensation and pay-for-performance to motivate provider‘s effort across the multiple tasks involved in successful chronic disease management. Drawing from agency theory, we propose a simple multitasking model of provider choice of patient chronic care under different base compensation schemes. Specifically, a healthcare provider (agent) treats a patient and is reimbursed by the principal (the purchaser). High quality treatment increases patient‘s benefits, measured as controlled blood pressure for hypertensive care for example (downstream outcome). The purchaser also observes the provider‘s adherence to certain clinical processes, for example the frequency of monitoring tests or the provision of smoking cessation advice (intermediate outcomes). The question is to design the optimal pay-for-performance system, given the base compensation scheme, provider‘s characteristics and performance measurement systems. This model is used to test the effects of alternative base payment mechanisms, provider‘s altruism and risk orientation, as well as the number and reliability of performance measures on the total welfare, measured as the sum of expected utility of the purchaser and the physician. Simulation analysis yields estimates of total welfare, patient‘s benefit, total spending, parameters of the payment system, provider‘s wage and percentage of provider‘s wage coming from pay-for-performance (i.e., size of incentives). The model further strengthens conventional arguments for mixed payment systems. Results show that the estimation of the purchaser‘s reward from increased quality should be made carefully to prevent overpayment. Moreover provider‘s altruism improves outcomes even though it may generate excessive spending on patient care. The more risk averse the provider is, the more important is the role played by pay-for-performance incentives. Therefore the incentive effects will vary substantially across providers. What is more, determining the number of performance measures and their reliability is a crucial decision for designing pay-for-performance programs. Finally, we identify perspectives for future research.