How Medicare Advantage plans use data for supplemental benefits decision-making.

OBJECTIVES: Health care payers are increasingly experimenting with interventions to address social risk factors. With enactment of the 2018 Bipartisan Budget Act, Medicare Advantage (MA) plans have new opportunities to offer supplemental benefits that are not "primarily health-related." This article presents findings from interviews conducted with executives from MA plans regarding plan decision-making processes related to new social risk factor benefits. STUDY DESIGN: Semistructured qualitative interviews with MA plan leadership. METHODS: A total of 63 plan representatives from 29 unique MA plans were interviewed about the rationale for social risk-related interventions and how data are used to inform benefits expansion decisions. This paper combines qualitative interview data from 2 separate studies with similar target groups and interview guides. Interview transcripts were qualitatively analyzed to examine underlying themes. RESULTS: Three main themes emerged: (1) Plans use multiple data sources to determine how to target benefits; (2) evidence gaps hinder decision-making to expand or offer new supplemental benefits; and (3) in the absence of sufficient evidence, some plans have their own research and quality improvement processes to maximize effectiveness. CONCLUSIONS: Findings provide insights about opportunities and challenges that MA plans face in making decisions related to supplemental benefits designed to address members' social risk factors. Barriers include collecting, generating, and analyzing data critical to informing investments. Results highlight the need to ensure interoperability of new and existing data sources, foster shared learning opportunities, and narrow evidence gaps about specific social care interventions to inform the design and implementation of effective supplemental benefits.

The effects of state earned income tax credits on mental health and health behaviors: A quasi-experimental study.

The earned income tax credit (EITC) is the largest U.S. poverty alleviation program for families with children, and state EITC policies provide a modest supplement to the federal program. Yet there are few studies of the effects of state EITC policies on population health. We examined whether state EITC policies affect mental health and health behaviors. Participants were drawn from the 1995-2015 waves of the Panel Study of Income Dynamics, a diverse national cohort study (N = 10,567). We used a quasi-experimental difference-in-differences analysis to examine the effects of state EITC programs among eligible individuals, accounting for secular trends among similar individuals in non-EITC states. Outcomes included self-reported general health, psychological distress, alcohol use, and smoking. The mean size of state EITC refunds in our sample was $265 for eligible individuals. In the overall sample, state EITC programs were not associated with any health outcomes of interest. This finding was robust to alternative specifications, and similar in subgroup analyses by gender and marital status. This study suggests that state EITC programs, which tend to provide smaller refunds than the federal program, may not be large enough to have a positive impact on mental health and health behaviors. These findings may inform policymaking related to the generosity of state EITC programs, especially as states seek to address the socioeconomic consequences of the COVID-19 pandemic.

Short-term effects of the earned income tax credit on mental health and health behaviors.

Poverty has consistently been linked to poor mental health and risky health behaviors, yet few studies evaluate the effectiveness of programs and policies to address these outcomes by targeting poverty itself. We test the hypothesis that the earned income tax credit (EITC)-the largest U.S. poverty alleviation program-improves short-term mental health and health behaviors in the months immediately after income receipt. We conducted parallel analyses in two large longitudinal national data sets: the National Health Interview Survey (NHIS, 1997-2016, N = 379,603) and the Panel Study of Income Dynamics (PSID, 1985-2015, N = 29,808). Outcomes included self-rated health, psychological distress, tobacco use, and alcohol consumption. We employed difference-in-differences analysis, a quasi-experimental technique. We exploited seasonal variation in disbursement of the EITC, which is distributed as a tax refund every spring: we compared outcomes among EITC-eligible individuals interviewed immediately after refund receipt (Feb-Apr) with those interviewed in other months more distant from refund receipt (May-Jan), "differencing out" seasonal trends among non-eligible individuals. For most outcomes, we were unable to rule out the null hypothesis that there was no short-term effect of the EITC. Findings were cross-validated in both data sets. The exception was an increase in smoking in PSID, although this finding was not robust to sensitivity analyses. While we found no short-term "check effect" of the EITC on mental health and health behaviors, others have found long-term effects on these outcomes. This may be because recipients anticipate EITC receipt and smooth their income accordingly.