Experiences of Maryland Primary Care Practices in Addressing Social Needs Through a Novel Value-Based Payment

To understand perceived successes and challenges of the HEART payment, and opportunities for similar value-based payment mechanisms aiming to address health-related social needs.

This study analyzes perceptions of primary care practices participating in the Maryland Primary Care Program (MDPCP) on the HEART payment, a value-based payment designed to support patients' social and medical needs. After a year of payment implementation, we gathered feedback through participant surveys and focus groups.

From February to March 2023, we administered a survey with 112 responses and held seven focus groups to collect primary data. For quantitative survey data, we summarized descriptive statistics and performed regression analyses to determine predictors of perceived value of the HEART payment. For qualitative focus group data, we coded and analyzed data to understand key themes on success factors and barriers to HEART payment implementation.

The HEART payment was rated as high value for 61.3% of survey respondents. In bivariate regression analysis, the level of funds received and affiliation with a Care Transformation Organization (CTO) were associated with perceived value of the HEART payment; however, these associations were not significant in multivariate models. In focus groups, we found that the biggest perceived success of HEART was its unique ability to enable direct support for patients' health-related social needs, with practices using the payment to provide patients with resources such as transportation, medically necessary home remediations, and support for loneliness. Perceived challenges included the need for more precise patient eligibility targeting and administrative burdens.

The HEART payment is a promising new payment model that enables primary care practices to directly address patients' social needs. Future value-based payment models that incorporate social risk adjustments in provider payments may consider alternate methods to identify patients with a high burden of health-related social needs. This may include adjusting data points used to identify beneficiaries or allowing providers to directly identify patients.