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Identification and prioritisation of requirements of a clinical decision support system for gait-related diseases in resource limited settings
Author(s)
Burger, Radford
Date Issued
2025
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
Gait-related disorders, such as multiple sclerosis (MS), Parkinson's disease (PD), cerebral palsy (CP), arthritis, symptoms of stroke, and injury, can drastically impact a person’s quality of life. Unfortunately, patients and medical practitioners in resource-limited settings often have limited access to costly specialised treatment and medical equipment required to effectively treat these conditions. Clinical decision support systems (CDSS) can overcome some of these challenges by providing healthcare workers with access to decision-making tools that facilitate diagnosis and treatment. The implementation and adoption of CDSS in resource-limited settings (RLS) have not been fully realised despite all its potential benefits. Failure to perform proper requirements analysis has been identified as a contributing factor. This study addresses some of these challenges through systematic reviews to identify and prioritise the requirements necessary for a CDSS tailored to the specific needs of RLS. The objectives formulated to achieve this are (1) Identify the requirements for a CDSS for gait related diseases in RLS; (2) perform a comparative analysis of requirements prioritisation (RP) techniques for CDSS for gait-related diseases in RLS; (3) apply a selected RP process for CDSS for gait-related diseases in RLS; (4) evaluate the quality attributes of the prioritised requirements for CDSS for gait-related diseases in RLS. Design science research methodology (DSR) was chosen as a research strategy to guide the execution of the study. The first phase involved analysis of existing literature and document reviews to identify requirements for the development of CDSS that focus on gait-related diseases in RLS. Literature analysis was used in phase 2 to select a preliminary set of RP techniques that suit the scope of requirements for CDSS for gait-related diseases in RLS. The third phase determined the criteria for a comparative analysis of the set of selected prioritisation techniques to help with selecting the best-suited one to the identified requirements. To ensure practical relevance and feasibility, researchers, practitioners, and academics in the fields of gait analysis, physiology, biomechanics, physiotherapy or neuro- mechanics were approached to review the requirements and apply the selected prioritisation technique. In phase four, software development experts evaluated the quality and accuracy of the prioritised requirements, based on criteria derived from the Wiegers’ Quality Model and Pohl’s Quality Model. In the final phase, the findings from the evaluation phase were analysed to derive conclusions and provide actionable insights. Individual requirements received average ratings of between 4 (good) and 5 (excellent). The average rating for the requirements set was 5 (excellent) on all the specified quality attributes. This study successfully identified and prioritised the requirements for a CDSS tailored to gait related diseases in RLS. User-centric, technical, and context-specific needs were effectively captured through a comprehensive literature review and engagement with experts. The MoSCoW prioritisation technique proved to be a practical and efficient method for requirement prioritisation in low-resource environments. The findings of this study can be a valuable guide for software developers and healthcare managers on aspects that require the most emphasis during the development of a CDSS in RLS.
Additional information
Thesis (Master of Information and Communication Technology)--Cape Peninsula University of Technology, 2025
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