Electronic Medical Records Adoption and Patient Health Outcome Metrics in International Rescue Committee Facilities at Kakuma Refugee Camp, Kenya

Abstract

This study was conducted in Kakuma Refugee Camp, Kenya, where the adoption of Electronic Medical Records (EMRs) in humanitarian healthcare settings is increasingly recognized as a strategic intervention for improving clinical quality, operational efficiency, and system accountability. However, implementation in resource-limited environments like Kakuma remains challenged by infrastructural constraints, limited digital capacity, and workforce turnover. This study assessed the influence of EMR adoption on four core operational domains—drug inventory tracking, quality of patient care quality, data security, and report generation—and their impact on patient recovery outcomes within International Rescue Committee (IRC) health facilities. Anchored in the Diffusion of Innovations (DOI) Theory,

the Technology-Organization-Environment (TOE) Framework, and Donabedian’s Quality-of- Care Model, the study employed a quantitative explanatory research design, using structured

questionnaires administered to 53 healthcare workers. Multiple linear regression was used to determine the predictive effect of each EMR functionality on self-reported clinical outcomes, including treatment adherence, diagnostic turnaround time, and overall recovery. Findings revealed that all four EMR functionalities had a statistically significant and positive impact on patient recovery outcomes. Patient care quality was the strongest predictor (β = 0.881, p = 0.000), followed by drug tracking efficiency (β = 0.640, p = 0.000), data security (β = 0.625, p = 0.017), and report generation (β = 0.539, p = 0.001). The model explained 62.1% of the variance in recovery outcomes (R2 = 0.621), indicating a robust model fit. These results underscore that EMRs are most effective when fully integrated into clinical, pharmaceutical, administrative, and reporting workflows. Chapter Five concludes that while all functionalities

contribute significantly, their collective value is maximized through alignment with day-to- day practices, policy support, and user-centered system design. The study contributes to theory

by extending digital health adoption frameworks to fragile healthcare environments and to practice by identifying functionality-specific priorities for EMR implementation. Methodologically, it demonstrates the utility of frontline perception data in evaluating digital system performance where objective health indicators are limited. Policy recommendations include role-specific training, participatory system refinement, and public–private partnerships to ensure scalable and sustainable EMR deployment. Future research should incorporate objective clinical metrics, longitudinal designs, and a broader scope of system functionalities. Qualitative studies are also encouraged to explore user experiences and support EMR alignment with operational realities in complex humanitarian contexts.