About this Journal


Article Abstract

Online ISSN: 1099-176X    Print ISSN: 1091-4358
The Journal of Mental Health Policy and Economics
Volume 23, Issue 3, 2020. Pages: 81-91
Published Online: 1 September 2020

Copyright © 2020 ICMPE.


 

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

 

Marisa Elena Domino,1 Edward C. Norton,2 Jangho Yoon,3 Gary S. Cuddeback,4 Joseph P. Morrissey1

1PhD, Konkuk University, Seoul, Korea
1Ph.D., Department of Health Policy and Management and Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
2Ph.D., Department of Health Management and Policy, Department of Economics, Population Studies Center, University of Michigan, Ann Arbor, MI, USA, and National Bureau of Economic Research, Cambridge, MA, USA
3Ph.D., Department of Preventive Medicine and Biostatistics, F. Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
4Ph.D., School of Social Work, Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

* Correspondence to: Marisa Elena Domino, Ph.D., Department of Health Policy and Management and Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, 135 Dauer Dr., Chapel Hill, NC 27599-7411, USA.
Tel.: +1-919-966 3891
E-mail: domino@unc.edu 

Source of Funding: This research was supported by grant funding from the John D. and Catherine T. MacArthur Foundation's Mental Health Policy Research Network and from the National Institute of Mental Health (MH63883 and MH065639).

Abstract
Alternative payment models, such as accountable care organizations, change incentives for treatment and may lead to upcoding. The upcoding literature is motivated largely by incorporating financial penalties for upcoding rather than by downstream effects on service provision requirements. This difference is important for shared-savings models with quality benchmarks. We develop a model of upcoding applicable to capitated, case-rate and shared savings payment systems. We test implications of our model on changes in severity determination and service use associated with changes in case-rate payments in a publicly funded mental health care system using conditional logit regressions and negative binomial models. We find 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, consistent with our theoretical predictions where the marginal utility of savings or profit is small, as would be expected from public sector agencies.


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.

Received 23 October 2019; accepted 17 June 2020

Copyright 2020 ICMPE