Health Economics & Policy Research

Objective

To examine a 2018 rule change allowing pediatric providers to bill the child’s Medicaid ID for post-partum depression (PPD) screening of mothers conducted during well-child visits, and document its relationship with PPD treatment and infant hospitalizations.

Study setting and design

Screening rates during well-child visits are calculated at the zip code level and used in linear probability and Instrumental Variable (IV) models to examine increases in screening after the policy change and relate them to PPD treatment and infant hospitalizations.

Data sources and analytic sample

Individual-level Medicaid claims were used to compute PPD screening rates and measures of PPD treatment and infant hospitalization.

Principal findings

The policy was associated with increases in screening rates, although take up was uneven and overall screening rates remained low at 8.8%. There was little overall increase in treatment, although in zip codes in the top third of screening rates, higher screening was associated with 10.1% higher probability of maternal treatment. Zip codes with high fractions in poverty and/or minority had low screening rates, but screening was more likely to be associated with increases in treatment in these areas. There are no effects in the full sample of children, but among children above the poverty line, the observed increases in screening reduced the probability of infant hospitalization in the first six months by 7.7%.

Conclusions

The policy change had only limited success increasing screening, but increased screening could lead to more maternal PPD treatment and lower infant hospitalization rates if accompanied by expanded access to PPD treatment.

This paper examines how over-the-counter drug labels influence consumer perceptions of efficacy, distort decision-making, and shape equilibrium outcomes under counterfactual regulatory scenarios. It addresses a key identification challenge—the unobservability of perceived efficacy under different information structures—by conducting a randomized controlled trial and integrating its findings into a structural model. Using data from a control group and three treatment arms, I construct product-level measures of perceived efficacy beliefs based on pairwise product comparisons. Leveraging control group data supplemented with NielsenIQ data, I estimate a structural demand model that isolates the role of efficacy beliefs while accounting for heterogeneous preferences. I then incorporate updated beliefs to assess equilibrium effects under each information treatment. In equilibrium, the most effective intervention—emphasizing equivalent efficacy—increases substitution between biologically equivalent products by 26%, reduces consumer spending by 12%, but also introduces second-degree price discrimination driven by symptom-label preferences.

This case-control study evaluates the impact of a hospitalization on credit scores for Medicaid beneficiaries in Louisiana stratified by sex, race, and ethnicity.

Hospitalizations can impose financial hardships on families,1,2 contributing to lower credit scores3 and reducing access to credit.1 Non-Hispanic Black and Hispanic patients may struggle more with hospitalization costs due to lower wealth compared with non-Hispanic White patients.

We evaluated the impact of a hospitalization on credit scores for Medicaid beneficiaries in Louisiana, examining effects by sex, race, and ethnicity. Louisiana is a setting well-suited for this research given that it is a Medicaid expansion state, has relatively high levels of personal debt (which inform credit scores), and has a relatively diverse population.

The child mental health crisis has been described as the "defining public health crisis of our time." This article addresses three myths about the crisis: (i) the idea that the crisis is new; (ii) the belief that increases in youth suicide mainly reflect deterioration in children's underlying mental health; and (iii) the myth that investments in children have little impact on children's mental health. In fact, the crisis has existed for decades, youth suicides vary asynchronously with other mental health measures and are impacted by external factors such as firearms legislation, and investments can improve child mental health and prevent suicide.

This cohort study assesses the association of implementation and reversal of Supplemental Nutritional Assistance Program (SNAP) work requirements with SNAP enrollment.

We analyze the economic consequences of rising US health care prices. By increasing the cost of employer-sponsored health insurance, rising prices serve as a de facto payroll tax on labor. Using exposure to hospital mergers as an instrument, we estimate that a 1% increase in health care prices lowers payroll and employment at non-health-care employers by 0.4%. At the county level, a 1% increase in health care prices reduces labor income by 0.27%, increases flows into unemployment by 1%, and lowers federal income tax receipts by 0.4%. The disemployment effects of rising prices are concentrated among lower- and middle-income workers.

We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrolment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modelling reveals large “choice inconsistencies” such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of “approximate inertia” where enrolees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrolees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or “choice overload”. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.

Many mental health disorders start in adolescence and appropriate initial treatment may improve trajectories. But what is appropriate treatment? We use a large national database of insurance claims to examine the impact of initial mental health treatment on the outcomes of adolescent children over the next two years, where treatment is either consistent with FDA guidelines, consistent with looser guidelines published by professional societies (“grey-area” prescribing), or inconsistent with any guidelines (“red-flag” prescribing). We find that red-flag prescribing increases self-harm, use of emergency rooms, and health care costs, suggesting that treatment guidelines effectively scale up good treatment in practice.