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

作者：Mercy Chepkirui, Stephanie Dellicour, Rosemary Musuva, Isdorah Odero, Benson Omondi, Benard Omondi, Eric Onyango, Hellen C. Barsosio, Lilian Otiso, Gordon Okomo, Maina Michael Waweru, Maia Lesosky, Tara Tancred, Yussif Alhassan, Simon Kariuki, Feiko O. ter Kuile, Miriam Taegtmeyer · 发表于：PLOS Digital Health · 年份：2025 · DOI：10.1371/journal.pdig.0000870 · 被引用次数：7 · 研究领域：Electronic Health Records Systems、Mobile Health and mHealth Applications、Data-Driven Disease Surveillance

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, ...