ArticleInternational journal of health policy and management2023
What Factors Explain Low Adoption of Digital Technologies for Health Financing in an Insurance Setting? Novel Evidence From a Quantitative Panel Study on IMIS in Tanzania.
Article in International journal of health policy and management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Factors Affecting the Successful Implementation of a Digital Intervention for Health Financing in a Low-Resource Setting at Scale: Semistructured Interview Study With Health Care Workers and Management Staff.Journal of medical Internet research · 2023Article
- Achieving universal health coverage in low- and middle-income countries through digital antimicrobial stewardship.Frontiers in digital health · 2023Article
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Authors and funding
7 authors.
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Abstract
backgroundDigital information management systems for health financing are implemented on the assumption thatdigitalization, among other things, enables strategic purchasing. However, little is known about the extent to which thesesystems are adopted as planned to achieve desired results. This study assesses the levels of, and the factors associated withthe adoption of the Insurance Management Information System (IMIS) by healthcare providers in Tanzania.
methodsCombining multiple data sources, we estimated IMIS adoption levels for 365 first-line health facilities in2017 by comparing IMIS claim data (verified claims) with the number of expected claims. We defined adoption as abinary outcome capturing underreporting (verified<expected) vs. not-underreporting, using four different approaches.We used descriptive statistics and analysis of variance (ANOVA) to examine adoption levels across facilities, districts,regions, and months. We used logistic regression to identify facility-specific factors (ie, explanatory variables) associatedwith different adoption levels.
resultsWe found a median (interquartile range [IQR]) difference of 77.8% (32.7-100) between expected and verifiedclaims, showing a consistent pattern of underreporting across districts, regions, and months. Levels of underreportingvaried across regions (ANOVA: F=7.24,
conclusionOur study shows that the adoption of IMIS in Tanzania may be sub-optimal and far from policy-makers'expectations, limiting its capacity to provide the necessary information to enhance strategic purchasing in the healthsector. Countries and agencies adopting digital interventions such as openIMIS to foster health financing reform areadvised to closely track their implementation efforts to make sure the data they rely on is accurate. Further, our studysuggests organizational and infrastructural barriers beyond the software itself hamper effective adoption.
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