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Patient complexity and GPs' income under mixed remuneration
1The Research Unit of Health Economics, University of Southern Denmark, Odense, Denmark. krolsen@health.sdu.dk
General practitioners (GPs) in Denmark face challenges in serving complex patient populations. A mixed remuneration system does not fully compensate GPs for treating patients with higher needs, impacting their income and utility.
Area of Science:
- Health economics
- Primary care policy
Background:
- Recruitment of general practitioners (GPs) to underserved areas in Denmark is challenging.
- The current mixed remuneration scheme (combining per capita and fee-for-service payments) is under scrutiny for its adequacy in compensating GPs for treating high-need patients.
Purpose of the Study:
- To assess the impact of patient heterogeneity on GP list size, income, and total utility within a mixed remuneration system.
- To evaluate the effectiveness of the current payment model in addressing the needs of complex patient populations.
Main Methods:
- Adaptation of the Iversen (2004) model as a theoretical framework.
- Empirical analysis using data from 1039 Danish solo general practice solo practitioners.
- Statistical analysis of the relationship between patient complexity, list size, and income.
Main Results:
- Theoretical model indicates higher patient complexity leads to lower list size, with ambiguous effects on income but a negative impact on total utility (income and leisure).
- Empirical data confirms that patient complexity significantly reduces both list size and income for GPs.
- The mixed remuneration system does not fully compensate practices for the increased demands of more complex patient panels.
Conclusions:
- The current mixed remuneration system is insufficient to ensure equitable compensation for GPs serving complex patient populations.
- Differentiated per capita payments could be a viable strategy to promote fair and consistent income distribution among GPs.
- Policy interventions may be needed to adequately support GPs working with high-need patients.
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