Economic analysis of an internet-based depression prevention intervention

Area of Science:

• Digital Health Interventions
• Adolescent Mental Health
• Health Economics

Background:

• Adolescence presents a high risk for depression, yet care-seeking and treatment effectiveness are low in this demographic.
• The CATCH-IT (Competent Adolescent Coping with Health-related Troubles) program was developed as an internet-based depression prevention intervention for at-risk adolescents.

Purpose of the Study:

• To analyze the program costs of CATCH-IT, focusing on safety expenses within an Accountable Care Organization (ACO) framework.
• To evaluate the perceived value of the CATCH-IT internet program by comparing willingness-to-pay against development costs.

Main Methods:

• Cost analysis of CATCH-IT development and implementation for a 5,000-patient ACO, utilizing Medicare RBRVS data.
• Comparison of CATCH-IT costs against traditional cognitive behavioral therapy (CBT) and assessment of safety protocol cost-effectiveness.
• Evaluation of willingness-to-pay through post-study surveys to determine the program's perceived value and break-even point.

Main Results:

• Total development cost was $138,683.03 ($27.74 per patient), with implementation costs at $49,592.25 ($597.50 per patient).
• Safety costs constituted 35% of implementation costs. CATCH-IT implementation ($197.99 per participant for safety) was substantially cheaper than CBT ($1,632 per patient).
• Median willingness-to-pay was $40, with a break-even point at 3,468 individuals for development cost recovery.

Conclusions:

• Internet-based interventions like CATCH-IT are economically feasible within ACOs, offering a cost-effective alternative to current treatments.
• Despite the significant proportion of costs allocated to safety protocols, CATCH-IT demonstrates considerable cost savings compared to traditional interventions.
• Further research on the costs, outcomes, and safety of internet-based interventions is recommended for broader adoption and acceptance.