Missed opportunities for digital health data use in healthcare decision-making: A cross-sectional digital health landscape assessment in Homa Bay county, Kenya.

Abstract

The proliferation of digital health systems in Sub-Saharan Africa is driven by the need to improve healthcare access and decision-making. This digitisation has been marked by fragmented implementation, the absence of universal patient identifiers, inadequate system linkages, limited data sharing, and reliance on donor-driven funding. Consequently, the increase in digital health data generation is not matched by similar growth in data use for decision-making, patient-centric care, and research. This study aimed to describe the digital health landscape in Homa Bay County and highlight the strengths and limitations of using digital health data for healthcare decision-making. We used mixed methods. A cross-sectional survey was conducted between June 2022 and October 2023 in 112 healthcare facilities to identify available digital health systems and assess their adoption and utilisation. Thirty-three in-depth interviews were conducted with relevant digital health stakeholders to seek stakeholder perspectives. Our study identified ten different digital health systems, nine of which were in active use. 91% (102/112) of surveyed health facilities had Kenya Electronic Medical Record system deployed for HIV patient management. Eight additional digital systems were available alongside this HIV system, but deployment was fragmented. Challenges to digital systems usage included lack of interoperability, unreliable internet, system downtime, power outages, staff turnover, patient workload, and lack of universal patient identifiers. The study identified multiple systems in use, with the HIV care management system being the most prevalent. The primary challenge hindering effective digital data utilisation is network instability, alongside issues such as the lack of interoperability, disjointed data quality assurance processes, and non-standardised patient identifiers. Recommendations include establishing a routine care data governance framework, implementing universal unique patient identifiers, harmonised data quality practices, advocating for universally compatible digital systems, promoting interoperability, and evaluating the suitability of the existing digital health data for surveillance research and decision-making.