ArticleBMC health services research2024
Analyzing health service employees' intention to use e-health systems in southwest Ethiopia: using UTAUT-2 model.
Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Enhancing digital readiness and capability in healthcare: a systematic review of interventions, barriers, and facilitators.BMC health services research · 2025Pooled it
- Determinants of the Uptake and Frequency of Use of a Web Portal Digital Health Intervention in Patients With Type 2 Diabetes and/or Coronary Heart Disease: Secondary Analysis of a Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Intention to Use Digital Health Among COPD Patients in Europe: A Cluster Analysis.Healthcare (Basel, Switzerland) · 2026Article
- User acceptance of telerehabilitation in Germany: a structural equation modeling approach based on the UTAUT2 model.Frontiers in digital health · 2026Article
- Study on the "digital divide" in the continuous utilization of Internet medical services for older adults: Combination with PLS-SEM and fsQCA analysis approach.International journal for equity in health · 2025Article
- Intention to use a health information platform in supportive housing for people with disabilities: An application of the UTAUT model.PloS one · 2025Article
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2 authors.
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Abstract
backgroundE-health systems have the potential to improve healthcare delivery and access to medical services in resource-constrained settings. Despite its impact, the system exhibits a low level of consumer acceptance and intention to use it. This research paper aims to analyze the intention of health service employees to use e-health systems in southwest Ethiopia using the UTAUT-2 model.
methodInstitutional-based cross-sectional studies were conducted at four referral hospitals (two private and two public) to examine the acceptance of e-health among consumers. Employees who had previous experience with diagnostic information systems and the health logistic information system were given structured questionnaires based on the UTAUT-2 model. The data were analyzed using the PLS-SEM method to identify the key factors that influence the intention to use e-health systems. The data were analyzed using SPSS version 20 and SmartPLS 3 software.
resultOut of the 400 surveyed employees, 225 (56.25%) valid questionnaires were collected. The findings indicate that three factors-effort expectancy (β = 0.276, t = 3.015, p = 0.001), habit (β = 0.309, t = 3.754, p = 0), and performance expectancy (β = 0.179, t = 1.905, p = 0.028)-had a significant positive impact on employees' intention to use e-health systems. On the other hand, factors such as social influence, facilitating conditions, hedonic motivation, and price values did not appear as significant predictors of intention to use e-health. The study model was able to predict 63% of employees' intentions to use e-health systems.
conclusionEffort expectancy, habit, and performance expectancy were significant predictors of employees' intention to use e-health systems among health service employees in southwest Ethiopia. The study supports the ideas that ease of use, experience with information systems, and the role of the systems in improving job performance contribute to employees' intention to use e-health. Policymakers and healthcare organizations in the region can use these findings to develop strategies for successful implementation and adoption of e-health systems, ultimately improving healthcare services and outcomes for the population.
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