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Assessing factors militating against the acceptance and successful implementation of a cloud based health center from the healthcare professionals' perspective: a survey of hospitals in Benue state, northcentral Nigeria.
BMC Medical Informatics and Decision Making 2019 Februrary 20
BACKGROUND: Cloud based health platforms (CBHP) have tremendous capacity to meet patient's health needs. The benefits inherent in CBHP position it to be relevant for efficient healthcare delivery. Nonetheless, studies have shown that the adoption of new technologies is sometimes a challenge especially in developing nations. This study, therefore, aim to examine, identify and evaluate the factors affecting healthcare professionals' intention to accept the cloud-based health center (CBHC) in developing countries. The research study focuses on hospitals in North-central of Nigeria.
METHODS: Using questionnaire adopted from related studies, a cross-sectional study was carried out of 300 healthcare professionals selected from medical health institutions in Benue State Nigeria. The study adopted the Unified Theory of Acceptance and use of Technology Extended (UTAUT2). Data analysis was carried out using SPSS (V20.0) and LISREL (V9.30) generally employed in Structural Equation Modeling to examine components and path model. The Socio technical design method was used to develop the CBHC.
RESULTS: Findings portrays performance expectancy, cloud based health knowledge, IT infrastructure and social influence to have significant effects on the intentions of healthcare professionals to accept and use the CBHC. These findings, agrees with prior related studies.
CONCLUSIONS: Our findings impacts the body of knowledge in that it identifies important areas the studies can be useful, especially, to managers and healthcare policy makers in the planning/implementation of health cloud. Research findings from the theoretical acceptance model identifies the factors and barriers towards sustainable cloud based health center solutions to meet the healthcare needs of people in remote communities.
METHODS: Using questionnaire adopted from related studies, a cross-sectional study was carried out of 300 healthcare professionals selected from medical health institutions in Benue State Nigeria. The study adopted the Unified Theory of Acceptance and use of Technology Extended (UTAUT2). Data analysis was carried out using SPSS (V20.0) and LISREL (V9.30) generally employed in Structural Equation Modeling to examine components and path model. The Socio technical design method was used to develop the CBHC.
RESULTS: Findings portrays performance expectancy, cloud based health knowledge, IT infrastructure and social influence to have significant effects on the intentions of healthcare professionals to accept and use the CBHC. These findings, agrees with prior related studies.
CONCLUSIONS: Our findings impacts the body of knowledge in that it identifies important areas the studies can be useful, especially, to managers and healthcare policy makers in the planning/implementation of health cloud. Research findings from the theoretical acceptance model identifies the factors and barriers towards sustainable cloud based health center solutions to meet the healthcare needs of people in remote communities.
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