Integrating Behavioral Health into the Pediatric Medical Home for Low-Income Children: Impact on Utilization and Cost of Care

Background: Approximately 1 in 5 US children have a mental health (MH) disorder. Children with MH disorders, particularly those that are under-diagnosed or under-treated, have higher rates of avoidable utilization and health care costs. Despite the availability of evidence-based treatments for child MH conditions, there are many systemic barriers to receiving adequate MH care, especially for low-income and minority populations. As such, starting in mid-2016, three Boston-based community health centers (CHC) began implementing TEAM UP—a complete behavioral health integration model for low-income children.

Objective: To examine the impact of TEAM UP on (1) rates of health care utilization in children and (2) total cost of care for children.

Methods:

Data and sample: 2014-2018 Medicaid claims data for children ages 0-17 attributed to one of three intervention site CHCs (N=1948) or to one of six geographically proximal non-intervention site CHCs (N=4662).

Outcomes: Utilization outcomes included visits for primary care MH, outpatient MH, all-cause emergency department (ED), MH ED, asthma ED, inpatient admissions, and inpatient admissions with a primary diagnosis of a MH condition. Total cost of care included inpatient, outpatient, professional, and pharmacy costs based on HealthPartners Total Cost of Care methodology.

Analysis: The unit of analysis was the person-quarter. A propensity score-matched difference-in-differences framework was used to estimate the effect of the intervention on intervention-site patients, relative to a comparison group of similar non-intervention site patients. Propensity scores included baseline age, sex, race/ethnicity, clinical indicators (e.g. MH conditions, asthma), and median income in zip code. Utilization outcomes were estimated using generalized estimating equations (GEE) assuming a negative binomial distribution with log link. For cost, we used standard two-part generalized GEE models. For all models, outcome variable Y_iq was indexed to patient i in quarter q. Independent variables included a dummy for whether a patient was attributed to an intervention site, a dummy for the pre- (2014-2016q2) versus post-period (2017-2018q2), an interaction term between intervention status and post-period, quarter, number of eligible member months in quarter q for patient i, a vector of time-variant member-level covariates, and site fixed effects, with errors clustered at the site-level and using robust standard errors to account for repeated patient measures

Results:

Preliminary results suggest statistically significant declines in inpatient admissions where the primary diagnosis was MH (IRR=0.51, p=0.026), representing a 49% decline in admissions for TEAM UP patients relative to control group patients. Results further suggest a statistically significant reduction in ED visits with any diagnosis of asthma (IRR=0.718, p<0.001) and with a primary diagnosis of asthma (IRR=0.718, p=0.005) for TEAM UP patients relative to control group patients. ED visits for MH and primary care visits for MH remained statistically unchanged. Furthermore, we found that TEAM UP children with a MH diagnosis at baseline experienced marginally significant reductions in total costs compared to similar children in the control group (IRR=0.821/member/quarter, p=0.053).

Conclusions: Early results suggest that the TEAM UP behavioral health integration model has the potential to reduce avoidable utilization in children and reduce total costs for children with a mental health diagnosis.