Identification and Prioritization of Requirements for a Home‐Based Tele‐Rehabilitation Information System for Cerebral Palsy Patients: A Delphi Study

ABSTRACT Background and Aims The delivery of consistent and comprehensive rehabilitation care for Cerebral Palsy (CP) patients, particularly in limited‐resource settings, faces significant structural, geographical, and economic barriers. The aim of the current study was to identify and finalize, through expert consensus, the functional and non‐functional requirements of a home‐based telerehabilitation information system for CP patients in the context of Iran, a setting with similar challenges to other low‐ and middle‐income countries (LMICs). Methods A two‐round Delphi methodology was employed with a multidisciplinary panel of experts to obtain a consensus regarding the requirements of a home‐based telerehabilitation system. Based on a prior qualitative study and a scoping review, a comprehensive set of requirements was developed. Requirements with a mean score of ≥ 3.75 on a 5‐point Likert scale or ≥ 80% agreement were included in the final framework. The ≥ 3.75 mean score was selected to represent a high consensus level, ensuring the average rating was clearly above the midpoint and toward the “Very Important” category (score of 5). Results A total of 142 requirements were identified and classified into 11 functional subsystems, comprising 121 functional and 21 non‐functional requirements. The subsystems with the highest number of endorsed requirements were Remote Exercise Therapy ( n = 22), Remote Education ( n = 21), and Remote Counseling ( n = 13). The most highly‐rated non‐functional requirements focused on Usability (e.g., simple interface), Compatibility (e.g., multi‐device support), and Adaptability (e.g., future feature addition). Conclusion This study establishes a validated, context‐sensitive framework for the development of a home‐based telerehabilitation system for CP patients in Iran. By incorporating expert consensus across clinical and technical domains, the findings offer a strong foundation for future system design and implementation. The approach highlights the importance of tailoring digital health solutions to local needs and healthcare infrastructures, providing a model for similar LMIC settings.