Unified modeling language for patient-centered telerehabilitation: A comprehensive framework integrating medical and biopsychosocial pathways

BACKGROUND

Effective telerehabilitation requires robust, standardized models to ensure comprehensive and continuous patient monitoring. However, existing rehabilitation models often lack integration, failing to cover the entire care continuum and its interdisciplinary aspects. This gap limits their applicability in real-world settings.

OBJECTIVE

This study introduces a semi-formal, Unified Modeling Language (UML)-based framework that provides a holistic, patient-centered representation of the rehabilitation pathway. The model is designed to bridge gaps in care coordination, aligning with recent scientific advances and healthcare policies emphasizing patient empowerment and interdisciplinary collaboration.

METHODS

Using a professional didactics approach, we conducted a literature review, field observations, and expert consultations (questionnaires, interviews) to map rehabilitation pathways across diverse conditions and settings. The model was iteratively refined based on expert feedback to ensure its accuracy and usability.

RESULTS

Our findings reveal significant fragmentation in rehabilitation pathways, driven by diverse clinical practices and discontinuities in care. To address this, the proposed UML-based model integrates medical, functional, psychosocial, and organizational data, ensuring a cohesive, capability-driven approach. The structured design enhances communication between stakeholders and improves interoperability across healthcare systems.

CONCLUSION

The proposed model provides a scalable foundation for digital telerehabilitation solutions, adaptable to various healthcare environments. By facilitating data integration and standardization, it supports better patient monitoring, decision-making, and personalized rehabilitation strategies. Future research will focus on refining the model to incorporate specialized rehabilitation fields and enhance interoperability with existing medical information systems.