The cost of implementing and sustaining an evidence-based, behavioral-health electronic screening system in probation departments.

Overview

abstract

BACKGROUND: Roughly 50%-75% of youths who have had contact with the juvenile justice system have a mental-health disorder. In 2019, a northeastern state required probation departments to implement an evidence-based behavioral health (BH) screen. e-Connect is a digital clinical decisional support system designed to identify suicide thoughts and behaviors and related BH risk and triage youths based on BH need, then facilitate linkage to care. OBJECTIVE: To identify the resources and estimate the costs required to implement and sustain e-Connect from probation-department and policymaker perspectives. METHODS: Prospective micro-costing analysis conducted concurrently with a rigorous evaluation of e-Connect. Data were collected for 622 youths ages 10-18 via administrative records, study instruments, and semi-structured interviews. Resources/costs were categorized as "fixed", "time-dependent", or "variable". Mean annual costs (per-county and per-screen, by county) were calculated for two intervention phases, "implementation" and "sustainment". All costs are in 2019 USD. RESULTS: The policymaker-relevant, annualized, mean, per-county start-up and sustainment costs were $18,704 (SD = $14,320) and $13,374 (SD = $13,317), respectively. The per-screen sustainment cost was $115 (SD = $113) across counties, with variation attributed to a combination of a county's behavioral-health needs, and differences in the types of resources utilized as part of their post-screening clinical response. CONCLUSION: The results of this analysis will inform the decisions of probation departments and their stakeholders, who are interested in implementing an evidence-based behavioral-health screen for youths on probation. Site-level figures will provide important details regarding the resources/costs associated with various implementation and management strategies. Cross-site, per-person averages will provide crucial inputs into budget impact models and cost-effectiveness analyses.