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Modeling ROI in Chronic Disease Management, A Simulation-Based Framework Integrating Patient Adherence and Policy Timing

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  • Jinho Cha
  • Eunchan D. Cha
  • Emily Yoo
  • Hyoshin Song

Abstract

Background: Chronic diseases impose a sustained burden on healthcare systems through progressive deterioration and long-term costs. Although adherence-enhancing interventions are widely promoted, their return on investment (ROI) remains uncertain, particularly under heterogeneous patient behavior and socioeconomic variation. Methods: We developed a simulation-based framework integrating disease progression, time-varying adherence, and policy timing. Cumulative healthcare costs were modeled over a 10-year horizon using continuous-time stochastic formulations calibrated with Medical Expenditure Panel Survey (MEPS) data stratified by income. ROI was estimated across adherence gains (delta) and policy costs (gamma). Results: Early and adaptive interventions yielded the highest ROI by sustaining adherence and slowing progression. ROI exceeded 20 percent when delta >= 0.20 and gamma

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  • Jinho Cha & Eunchan D. Cha & Emily Yoo & Hyoshin Song, 2025. "Modeling ROI in Chronic Disease Management, A Simulation-Based Framework Integrating Patient Adherence and Policy Timing," Papers 2510.06379, arXiv.org.
    • Handle: RePEc:arx:papers:2510.06379
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    File URL: http://arxiv.org/pdf/2510.06379
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