Harnessing Big Data to Improve Children’s Mental Health Treatment

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 special issue of the Journal of Human Resources showcases an emerging literature on the economics of child mental health. Until recently, the severe stigma associated with mental health issues meant that few people felt comfortable talking about them or realized how very prevalent they are (Bharadwaj, Pai, and Suziedelyte 2017). Arguably, this changed with the COVID-19 pandemic, which precipitated widespread discussions of a child and youth mental health crisis (United States Public Health Service, Office of the Surgeon General 2021).

Background and Objectives: Children with asthma who have depressed caregivers are known to be less adherent to medication regimes. However, it is less clear how adherence responds to a caregiver’s new diagnosis of severe depression or whether there is a similar relationship with other serious caregiver diagnoses. The hypothesis is that adherence worsens both with new diagnoses of depression and possibly with new diagnoses of other serious conditions. Methods: This study follows a cohort of 341,444 continuously insured children with asthma before and after a caregiver’s new diagnosis of severe depression or another serious health condition. The effect of a new depression diagnosis on a child’s medication adherence is compared to the effect of new diagnoses of other common caregiver chronic conditions including diabetes, cancer, congestive heart failure, coronary artery disease, and chronic obstructive pulmonary disease. Results: Results show that children’s medication adherence declines following a caregiver’s new diagnosis of severe depression, but that it also declines following a caregiver’s new diagnosis of diabetes. There is no association with new diagnoses of the other caregiver chronic conditions examined. Conclusions: Children whose caregivers have a new diagnosis of depression or diabetes may be at increased risk of deterioration in their medication adherence. These caregivers may benefit from additional support and follow-up. The relationship between caregivers’ health and children’s medication adherence is complex and deserves further study.