When we think of value based purchasing, our thoughts typically focus on quality level, incentives and penalties.
Annals of Internal Medicine recently released an ahead of print article discussing pay for performance and Medicare's poor ability to adjust the patient population appropriately. The impact of poor risk adjustment creates barriers to access to care to such a degree that providers choose to eliminate sicker patients from their practice.
The reason for this problem: providers who treated the sicker patients were not appropriately rated for the quality and outcomes achieved. Due to an inadequate risk adjustment process, these providers were rated as providing poorer quality care.
The findings indicate pay for performance models need to control for as many patient characteristics as possible that could impact the results of care. This is required to more fairly judge the level of care provided. The societal impact of inadequate risk adjustment is sicker patients not receiving needed care.
When you enter into a contract focused on quality of care, take time to discuss the risk adjustment process. You want your care fairly rated. Based on this study, you also want to think of the future impact in your community. The unhealthy individuals living in your community need access to care.
Below you will find a quick view of the abstract.
The Value-Based Payment Modifier: Program Outcomes and Implications for Disparities
Eric T. Roberts, PhD; Alan M. Zaslavsky, PhD; J. Michael McWilliams, MD, PhD
When risk adjustment is inadequate and incentives are weak, pay-for-performance programs, such as the Value-Based Payment Modifier (Value Modifier [VM]) implemented by the Centers for Medicare & Medicaid Services, may contribute to health care disparities without improving performance on average.
To estimate the association between VM exposure and performance on quality and spending measures and to assess the effects of adjusting for additional patient characteristics on performance differences between practices serving higher-risk and those serving lower-risk patients.
Exploiting the phase-in of the VM on the basis of practice size, regression discontinuity analysis and 2014 Medicare claims were used to estimate differences in practice performance associated with exposure of practices with 100 or more clinicians to full VM incentives (bonuses and penalties) and exposure of practices with 10 or more clinicians to partial incentives (bonuses only). Analyses were repeated with 2015 claims to estimate performance differences associated with a second year of exposure above the threshold of 100 or more clinicians. Performance differences were assessed between practices serving higher- and those serving lower-risk patients after standard Medicare adjustments versus adjustment for additional patient characteristics.
Random 20% sample of beneficiaries.
Hospitalization for ambulatory care–sensitive conditions, all-cause 30-day readmissions, Medicare spending, and mortality.
No statistically significant discontinuities were found at the threshold of 10 or more or 100 or more clinicians in the relationship between practice size and performance on quality or spending measures in either year. Adjustment for additional patient characteristics narrowed performance differences by 9.2% to 67.9% between practices in the highest and those in the lowest quartile of Medicaid patients and Hierarchical Condition Category scores.
Observational design and administrative data.
The VM was not associated with differences in performance on program measures. Performance differences between practices serving higher- and those serving lower-risk patients were affected considerably by additional adjustments, suggesting a potential for Medicare's pay-for-performance programs to exacerbate health care disparities.