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Constructing a Digital Bridge: A Systematic Review Assessing Electronic Medical Record and Telehealth Implementation
Caleigh S Roach1, Ann Pham2, Jacob J Shawwa1
1Department of Neurological Surgery, University of Miami, Miami, Florida, USA; Miller School of Medicine, University of Miami, Miami, Florida, USA.
Background:
Neurosurgical care in Uganda faces significant challenges due to workforce shortages, infrastructure limitations, and a lack of digital health tools. Implementing electronic medical records (EMRs) and telehealth could improve neurosurgical outcomes, but adoption remains low. This systematic review examines barriers and facilitators to EMR and telehealth implementation in Ugandan neurosurgery to identify opportunities for improvement.
Methods:
A systematic review was conducted following Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020 guidelines across PubMed, Google Scholar, and Scopus to identify studies published from 2007 to 2024 evaluating EMR and telehealth adoption in Uganda. Thematic analysis categorized barriers and facilitators into 10 distinct themes. Statistical analysis for frequency and correlation with technologies were performed using χ2 analysis and Pearson residual tests, with statistical significance set at P < 0.1.
Results:
Key barriers include technological infrastructure inefficiencies (24%), systemic and operational limitations (16%), and technical competency and training deficits (13%). Similarly, the primary facilitators include infrastructure reliability (22%), training and education investment (13%), and community engagement (13%). Notably, telehealth adoption was more significantly impacted by human resource limitations (P < 0.05), whereas EMR implementation was hindered by systemic inefficiencies (P < 0.05).
Conclusions:
Addressing Uganda's digital health gaps requires cost-effective and scalable strategies, including mobile-based EMRs, teleconsultation frameworks, and structured workforce training. Future research should focus on developing implementation models tailored to low-resource settings, ensuring feasibility and sustainability. This study aims to contribute to the growing discourse on digital solutions for resource-limited healthcare, with a particular emphasis on innovation in global neurosurgical care.
