Pioneering MDD Treatment Modeling for Optimal Care Pathways

MDD treatment modeling demonstrates that sequenced interventions for major depressive disorder consistently deliver superior quality-adjusted life years and net monetary benefits compared with no active treatment. All examined pathways outperformed inaction, with an SSRI-first sequence followed by SNRI, augmented SNRI, and SNRI plus antipsychotic offering the strongest balance of clinical gains and incremental costs.

Patient-Level Simulations Reflect Real-World Complexity

A discrete event simulation framework captures individual patient heterogeneity, competing risks, and continuous time rather than relying on average-patient Markov assumptions. Continuous input from patients, clinicians, employers, and payers shaped every element of the open-source MDD treatment modeling platform, which was built in transparent R code to allow full inspection and adaptation by any user.

Five-Year Cost-Effectiveness of Treatment Sequences

Base-case results over five years showed SSRI monotherapy as the lowest-cost option yet produced fewer quality-adjusted life years than switching or psychotherapy-augmented pathways. The switching sequence yielded an ICER of approximately $28,000 per QALY, while the psychotherapy-intensive route exceeded conventional thresholds because twice-weekly sessions drove costs beyond the modest QALY gains. Sensitivity analyses confirmed that health-state utilities, initial response rates, and late relapse probabilities exerted the strongest influence on outcomes.

Strategic Tool for Mental Health Reimbursement Decisions

This flexible MDD treatment modeling platform equips health economics teams to test emerging therapies, incorporate new real-world evidence on treatment resistance, and evaluate full patient journeys. Greater transparency in modeling can lead to more nuanced coverage policies that better reflect the heterogeneous experiences of insured populations living with MDD.