Putting Providers At-Risk through Capitation or Shared Savings: How Strong are Incentives for Upcoding and Treatment Changes?

Background: Alternative payment models, including Accountable Care Organizations and fully capitated models, change incentives for treatment over fee-for-service models and are widely used in a variety of settings. The level of payment may affect the assignment to a payment category, but to date the upcoding literature has been motivated largely incorporating financial penalties for upcoding rather than by a theoretical model that incorporates the downstream effects of upcoding on service provision requirements.

Aims of the study: In this paper, we contribute to the literature on upcoding by developing a new theoretical model that is applicable to capitated, case-rate and shared savings payment systems. This model incorporates the downstream effects of upcoding on service provision requirements rather than just the avoidance of penalties. This difference is important especially for shared-savings models with quality benchmarks.

Methods: We test implications of our theoretical model on changes in severity determination and service use associated with changes in case-rate payments in a publicly-funded mental health care system. We model provider-assigned severity categories as a function of risk-adjusted capitated payments using conditional logit regressions and counts of service days per month using negative binomial models.

Results: We find that severity determination is only weakly associated with the payment rate, with relatively small upcoding effects, but that level of use shows a greater degree of association.

Discussion: These results are consistent with our theoretical predictions where the marginal utility of savings or profit is small, as would be expected from public sector agencies. Upcoding did seem to occur, but at very small levels and may have been mitigated after the county and providers had some experience with the new system. The association between the payment levels and the number of service days in a month, however, was significant in the first period, and potentially at a clinically important level. Limitations include data from a single county/multiple provider system and potential unmeasured confounding during the post-implementation period.

Implications for health care provision and use: Providers in our data were not at risk for inpatient services but decreases in use of outpatient services associated with rate decreases may lead to further increases in inpatient use and therefore expenditures over time.

Implications for health policies: Health program directors and policy makers need to be acutely aware of the interplay between provider payments and patient care and eventual health and mental health outcomes.

Implications for further research: Further research could examine the implications of the theoretical model of upcoding in other payment systems, estimate the power of the tiered-risk systems, and examine their influence on clinical outcomes.