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Bridging the rehabilitation data gap in Uganda: learning through the implementation of the WHO Routine Health Information System - Rehabilitation module

Hasan, M. Z.; Okello, G.; DE GROOTE, W.; Omaren, A.; Adair, T.; Bachani, A. M.

2025-02-14 public and global health
10.1101/2025.02.13.25322214 medRxiv
Show abstract

Ugandas Health Management Information System (HMIS) has historically lacked robust, standardized data on rehabilitation and assistive technology (AT) services, which has limited effective policy development and service planning. To address this gap, the Ministry of Health sought to integrate the WHO Routine Health Information System (RHIS) - Rehabilitation module into the national digital reporting platform (DHIS2). This mixed-methods explanatory case study adopted the Consolidated Framework for Implementation Research (CFIR) to examine the multi-level processes, determinants, and context influencing integration. The WHO RHIS-Rehabilitation module was integrated through stakeholder engagement, indicator consensus-building, customized tool development, and targeted capacity-building. Six core rehabilitation indicators were prioritized and launched in DHIS2 across 25 referral facilities. The process revealed persistent challenges, including infrastructural constraints, limited workforce capacity, and competing health sector priorities. Nonetheless, substantial improvements were observed in data standardization, stakeholder engagement, and foundational digital reporting capacity for rehabilitation services. Integrating the WHO RHIS-Rehabilitation module into Ugandas HMIS marks a significant advancement for rehabilitation information systems in resource-limited settings. Key lessons highlight the necessity of early policy alignment, ongoing capacity building, and continuous stakeholder support to sustain and expand rehabilitation data integration. This experience provides a practical pathway for strengthening rehabilitation data systems in comparable contexts.

Published in SSM - Health Systems · not in our set (fewer than 10 published preprints to learn from) · training set

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