Optimizing Hybrid Care Models: A Framework for Integrating Mobile Health Vans with Remote Patient Monitoring (RPM) to Eliminate the Post-Discharge Readmission Divide

• Adaan Ahsun

  Covenant University

  Author

Hospital readmissions following discharge remain a persistent challenge in healthcare systems worldwide, with rates approaching 20-25% for conditions such as heart failure . Despite evidence-based transitional care interventions, a substantial "readmission divide" persists, disproportionately affecting underserved populations with limited access to technology and follow-up care. Remote Patient Monitoring (RPM) has demonstrated efficacy in reducing readmissions, with studies showing 57.8% reductions in hospitalization rates at 3 months post-intervention . However, the digital divide creates accessibility barriers for vulnerable populations lacking smartphones or digital literacy. This study addresses the research gap by proposing and validating a hybrid care framework integrating mobile health vans with RPM systems to bridge the post-discharge readmission divide. Using a design-based research methodology combining retrospective data analysis with prospective simulation, we evaluated a framework combining in-person mobile van visits with remote monitoring protocols. The integrated model achieved an 89.4% readmission prediction accuracy and demonstrated a 40% relative reduction in 30-day readmission rates compared to standard transitional care. The framework provides a replicable, scalable solution for healthcare systems seeking to eliminate disparities in post-discharge outcomes while addressing implementation barriers including the digital divide and system interoperability challenges.

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Copyright (c) 2026 Adaan Ahsun (Author)

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