Leveraging mHealth usage logs to inform health worker performance in a Resource-Limited setting: Case example of mUzima use for a chronic disease program in Western Kenya

Simon Savai, Jemimah Kamano, Lawrence Misoi, Peter Wakholi, Md Kamrul Hasan and Martin C Were

PLOS Digital Health, 2022, vol. 1, issue 9, 1-15

Abstract: Background: Health systems in low- and middle-income countries (LMICs) can be strengthened when quality information on health worker performance is readily available. With increasing adoption of mobile health (mHealth) technologies in LMICs, there is an opportunity to improve work-performance and supportive supervision of workers. The objective of this study was to evaluate usefulness of mHealth usage logs (paradata) to inform health worker performance. Methodology: This study was conducted at a chronic disease program in Kenya. It involved 23 health providers serving 89 facilities and 24 community-based groups. Study participants, who already used an mHealth application (mUzima) during clinical care, were consented and equipped with an enhanced version of the application that captured usage logs. Three months of log data were used to determine work performance metrics, including: (a) number of patients seen; (b) days worked; (c) work hours; and (d) length of patient encounters. Principal findings: Pearson correlation coefficient for days worked per participant as derived from logs as well as from records in the Electronic Medical Record system showed a strong positive correlation between the two data sources (r(11) = .92, p

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pdig00:0000096

DOI: 10.1371/journal.pdig.0000096

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