Abstract
IntroductionSub-Saharan Africa lags in adoption of mobile health (m-health) applications and in leveraging m-health for sustainable development goals. There is a need for a comprehensive investigation of determinants of hospitals’ adoption of m-health in Sub-Saharan Africa to inform policies, practices and investments.MethodsThis investigation used a logit regression model to analyze the determinants of m-health adoption in Kenyan hospitals applying the Technological, Organizational and Environmental (TOE) framework and the Diffusion of Innovation (DOI) theory. A representative sample of 211 executives of Level 4–6 hospitals in 24 counties provided primary data on Patient-Centered (PC) and Facility-Centered (FC) m-health applications.ResultsBoth PC and FC m-health adoption were predicted by competition for patients (PC p = 0.041, FC p = 0.021), IT human resource capacity (PC p = 0.048, FC p = 0.037), and hospital pursuit of market growth through technological leadership (PC p = 0.010, FC p = 0.020). Further determinants of PC m-health adoption included hospital access to slack financial resources (p = 0.006), acquisition strategy (p = 0.011), compatibility with the hospital systems (p = 0.015), trialability (p = 0.019), medical insurance company support (p = 0.025),patient pressure (p = 0.036), and perceived effect of global medical tourism (p = 0.039). FC m-health adoption was predicted by hospital size (p = 0.008), ICT infrastructure capacity (p = 0.041), and government support (p = 0.013).ConclusionA differentiated approach is required to scale up m-health adoption. PC m-health requires emphasis on establishing national and regional compatibility and interoperability, developing trialability processes and validation mechanisms, incentivizing patient competition and mobility, establishing innovative and cost-effective acquisition strategies, and ensuring integration of digital services within national insurance schemes and policies. These policies require support from patients and communities to drive demand and spur investment in adequate IT human resources to maintain reliability. Pilot PC m-health projects should prioritize hospitals with slack financial resources, while FC m-health should target large facility size. FC m-health applications are more complex and costly than PC, requiring government incentives to trigger hospital investments and national investment in ICT infrastructure. Investors and hospital managers should integrate m-health into market growth strategies for sustainable m-health scale-up in Kenya and beyond.
Highlights
OPEN ACCESSCitation: Ngongo BP, Ochola P, Ndegwa J, Katuse P (2019) The technological, organizational and environmental determinants of adoption of mobile health applications (m-health) by hospitals in Kenya
The total number of questionnaires that met the requirements for the study was 211 out of 241 (219 level 4 hospitals and 22 level 5 and 6 hospitals) distributed questionnaires across 24 counties.This represents 87.5% response rate which complies with recommendations by Fincham [31] that a response rate of 80% and above is needed for generalizability of results of surveys
Four questionnaires were discarded because they were filled by non-top executive staff and 3 questionnaires were discarded because the hospitals self-categorized as level 3 hospitals despite being registered as level 4 in the Kenya Ministry of Health database
Summary
Sub-Saharan Africa lags in adoption of mobile health (m-health) applications and in leveraging m-health for sustainable development goals. There is a need for a comprehensive investigation of determinants of hospitals’ adoption of m-health in Sub-Saharan Africa to inform policies, practices and investments. The sustainable development goals (SDG) acknowledge the transformational impact that digital health technologies such as mobile health (m-health) will have in a context of continued global population growth, inequitable access to health, increased healthcare costs, and the limited number of health care workers [1,2]. While m-health adoption by hospitals is expanding in high income countries, the adoption of m-health applications in Low- and Middle-Income Countries (LMICs) in general and in Sub-Saharan Africa, remains negligible with limited understanding of factors affecting this disparity [5]. Africa registers the highest rate of failure of m-health projects [4,7]
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