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.

BACKGROUND: Digital 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. METHODS: Combining 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

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.

BACKGROUND: Digital interventions for health financing, if implemented at scale, have the potential to improve health system performance by reducing transaction costs and improving data-driven decision-making. However, many interventions never reach sustainability, and evidence on success factors for scale is scarce. The Insurance Management Information System (IMIS) is a digital intervention for health financing, designed to manage an insurance scheme and already implemented on a national scale in Tanzania. A previous study found that the IMIS claim function was poorly adopted by health care workers (HCWs), questioning its potential to enable strategic purchasing and succeed at scale. OBJECTIVE: This study aimed to understand why the adoption of the IMIS claim function by HCWs remained low in Tanzania and to assess implications for use at scale. METHODS: We conducted 21 semistructured interviews with HCWs and management staff in 4 districts where IMIS was first implemented. We sampled respondents by using a maximum variation strategy. We used the framework method for data analysis, applying a combination of inductive and deductive coding to organize codes in a socioecological model. Finally, we related emerging themes to a framework for digital health interventions for scale. RESULTS: Respondents appreciated IMIS's intrinsic software characteristics and technical factors and acknowledged IMIS as a valuable tool to simplify claim management. Human factors, extrinsic ecosystem, and health care ecosystem were considered as barriers to widespread adoption. CONCLUSIONS: Digital interventions for health financing, such as IMIS, may have the potential for scale if careful consideration is given to the environment in which they are placed. Without a sustainable health financing environment, sufficient infrastructure, and human capacity, they cannot unfold their full potential to improve health financing functions and ultimately contribute to universal health coverage.