ArticlePLOS digital health2026
Adopting and validating a technology acceptance model-based paradigm to assess acceptance and satisfaction with electronic health information system by healthcare providers in resource-limited governmental and non-governmental hospitals.
Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
In resource-limited healthcare settings, adoption of electronic health information systems (EHIS) depends on provider acceptance and satisfaction. This study extended the Technology Acceptance Model (TAM) with Technology-Organization-Environment (TOE) factors to capture contextual influences in Palestinian hospitals. A cross-sectional survey of 220 healthcare professionals (December 2023-June 2024) assessed eight TOE constructs, including relative advantage, system quality, compatibility, complexity, top management support, IT support/training, and competitive pressure, alongside TAM beliefs (perceived usefulness, perceived ease of use) and behavioral intention. Partial least squares structural equation modeling (PLS-SEM) confirmed reliability and validity (indicator loadings 0.76-0.96; Cronbach's α 0.72-0.91; AVE 0.64-0.91; SRMR 0.075-0.079). The model explained 68% of variance in perceived usefulness, 57% in ease of use, and 74% in behavioral intention. Both ease of use (β = 0.43, p < 0.001) and usefulness (β = 0.39, p < 0.001) significantly predicted intention. System quality positively influenced usefulness (β = 0.30, p < 0.001) and ease of use (β = 0.23, p < 0.001). Competitive pressure was strongly associated with both constructs (PU: β = 0.23, p = 0.004; PEOU: β = 0.37, p < 0.001). Complexity showed no significant effect. Hierarchical regression confirmed TOE-TAM constructs explained 51-76% additional variance beyond demographics. The validated TAM-TOE instrument demonstrated robust psychometric properties and strong explanatory power for EHIS acceptance in resource-constrained contexts. Key levers for implementation include enhancing system quality, leveraging competitive pressure, aligning EHIS with workflows, and reinforcing organizational support. This tool provides evidence-based guidance to accelerate EHIS uptake, optimize clinical processes, and improve patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.