TOWARDS MORE APPROPRIATE CARE: Using financial incentives in contract design

SUMMARY It is often argued that health care providers (e.g. hospitals, physicians, etc.) are imperfect agents of the patient: over-supplying (or in certain situations under-supplying) health care services when facing a financial advantage to do so.[1] Hence, changing the incentives in provider payment contracts may lead to more appropriate provision of health care. This belief was the motivation for the design of several innovative reimbursement arrangements, such as Medicare’s Hospital Readmission Reduction Program or Maryland’s All-Payer program, created under Affordable Care Act (ACA), and the creation of Accountable Care Organizations.[2] However, the results of these initiatives have been mixed, leading experts to conclude that reaching optimal contract design is more tedious than originally believed.[3] Therefore, it is important to understand what drives providers and under what conditions they respond to financial incentives. Although health care providers’ response to financial stimulus has been empirically shown in an abundance of cases [1, 4], its magnitude is far from uniform and, in certain cases, researchers found no measurable response at all ([5-8]). There is a shortage of comprehensive analyses on exactly what drives providers’ behavior, which hampers the realization of optimal payment designs. In the present dissertation, I attempt to illustrate how providers respond to incentives in various environments and provide recommendations on the optimal payment design in order to obtain high quality and affordable care. My research utilizes examples of policy-reforms and payment design discontinuities in Dutch health care as ‘natural experiments’ that allow me to quantify responses to sudden shifts in the incentive structure. My work focuses primarily on medical specialist care (secondary care) and utilizes claim-level administrative data from Dutch health insurers for the years 2006 to 2018. Overall, my results show that providers with guaranteed budgets, that were independent of production volumes, achieved higher productivity growths and lower growths in treatment intensity, than those with volume-driven arrangements, demonstrating that providers were able to improve efficiency when incentivized to do so using guaranteed budgets (in Chapters 2-3). However, when going deeper and evaluating health care organizations’ response to financial incentives using discontinuities in reimbursement schedules (in Chapters 4-5) I found that the response was not uniform among all providers: small, profit-oriented organizations, especially those in financial distress, were more likely to maximize revenues by strategically discharging patients when a higher tariff was reached. In addition, I demonstrate that the same organization (i.e. rehabilitation centers) showed no response to the discontinuity in an outpatient setting, while strong response is observed in an inpatient setting. A possible interpretation could be the higher potential financial gains from utilizing strategic discharge behavior. Overall, these findings imply that moving away from volume-based production arrangement towards guaranteed payments (e.g. global budgets) could present the right incentives for containing costs and improving efficiency. Global budget mechanisms, however, are not new. These arrangements have been frequently used since the first wave of health care reforms after World War II. [9]. Lessons learnt from these, as well as more recent experiments, such as Maryland’s All-Payer program and pilot programs such as Bernhoven Hospital in the Netherlands, must be considered when designing hospital contracts. Most importantly, the mechanism should appropriately reward gains in market share in order to continue to encourage competition between providers and to circumvent the build-up of waiting lists, while quality and continuity of care must be guaranteed, and policy-makers should ensure that the mechanism is in line with other reimbursement arrangements (e.g. DRG- systems, risk-adjustment mechanisms).