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.