Paying for Equity: Changing Pay for Performance to Reduce Disparities in Healthcare Funding
As overall healthcare spending continues to increase in the United States, policymakers have pressured the healthcare system to provide higher-value care to patients. Stakeholders intend to make the current system operate according to the Triple Aim framework, looking to improve patient experience, improve health outcomes, and reduce costs. Many hospitals and health insurers have incorporated these goals into their business models, using various incentives to encourage providers to be more accountable to the needs of their patients.
One prominent strategy for meeting the goals of the Triple Aim is pay for performance (P4P). P4P provides financial incentives to providers to improve quality of care. The Medicare Hospital Value Based Purchasing program is the largest of its type, but private payers have implemented similar schemes as well. P4P programs pay providers for using clinical practices shown to improve quality of care. If more patients receive these best practices, the providers generally receive more money. Some providers receive additional payments if their patients experience better outcomes. These outcomes include fewer readmissions to the hospital, among other things.
But P4P programs pose issues for providers when their patient population is economically disadvantaged. Patients of low socioeconomic status tend to have more complex health problems, structural barriers preventing access to care, and limited resources to pay for treatment. As a result, these patients tend to perform worse on measures that impact P4P payments to providers. Many P4P programs account for this difference by using case mix adjustment, controlling for factors that disproportionately affect low-income populations. But patient-level adjustment does not account for resource constraints, which diminish provider quality in low-income areas. Diverting resources away from these providers based on low performance would, in turn, make the quality-of-care gap even larger.
A new study by Cheryl Damberg and colleagues proposes an alternative P4P model that corrects for these resource constraints. The authors test a two-step payment approach that adjusts for both patient and provider characteristics. First, P4P payments are determined with the standard approach. Then, those payments are adjusted to redistribute funding to high-performing providers working with disadvantaged patients. The team found that, compared to the traditional P4P scheme, the two-step approach was able to mitigate disparities in funding across provider categories, geographic regions, and racial/ethnic populations.
Damberg and the team first collected data about health plans participating in the California Integrated Healthcare Association P4P Program in 2008. Next, the team collected demographic data about the patient populations of each provider organization in the sample. They then used that information to group providers together according to the socioeconomic status of the patients they cared for (disadvantaged, intermediate, or advantaged populations). Finally, the team determined the level of incentive payments made to each provider organization group, which they used to calculate a post-adjustment factor for each group. This post-adjustment factor works to even out the incentive payments made to each group. Before the adjustment, the average payment for disadvantaged providers was over 2.5 times lower than for advantaged providers.
Post-adjustment incentive payments nearly double the amount received by disadvantaged providers. The adjustments also help to reduce payment gaps along racial/ethnic lines. Payments to providers with the highest concentration of Hispanic patients increased over 40 percent. The adjustment also redistributes resources by geographic region, shrinking the range of payments by region.
The authors note that most P4P schemes are budget-neutral. Any increased incentive payments to providers working with low-SES patients come at a cost to those working with higher-SES patients. Because high-SES providers tend to receive higher payments even without a P4P scheme, the relative cost from lower P4P payments is small. Further, unadjusted payments were strongly linked to higher performance. This suggests that higher levels of payments were going to the “best of the best” within each category, even before adjustment. After adjustment, this link became even stronger for disadvantaged organizations, suggesting that improvement for these providers yields even more benefit to them.
Overall, Damberg and colleagues present a case that both patient and provider characteristics are crucial for determining fair P4P incentive payments. A more robust approach can help ensure that resources are diverted toward disadvantaged providers that need them the most. By providing incentives that encourage improvement without unfairly penalizing providers, policymakers can help the healthcare system better achieve the goals of the Triple Aim.
Article Source: Pay for Performance Schemes That Use Patient and Provider Categories Would Reduce Payment Disparities, Damberg et al, Health Affairs, January 2015, 34(1): 134-142.
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