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Dynamics of Health Technology Diffusion in the Integrated Care System (DHTDICS): A Development and Validation Study in China

BACKGROUND: Limited diffusion of health technology has greatly halted the improvement of resource integration and healthcare outcomes. The importance of understanding the dynamics of health technology diffusion is increasingly highlighted. However, the dynamic mechanism of health technology diffusio...

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Detalles Bibliográficos
Autores principales: Deng, Qingwen, Lu, Junhong, Zeng, Zhichao, Zheng, Yuhang, Liu, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850575/
https://www.ncbi.nlm.nih.gov/pubmed/33536802
http://dx.doi.org/10.2147/RMHP.S293144
Descripción
Sumario:BACKGROUND: Limited diffusion of health technology has greatly halted the improvement of resource integration and healthcare outcomes. The importance of understanding the dynamics of health technology diffusion is increasingly highlighted. However, the dynamic mechanism of health technology diffusion in the context of the integrated care system (ICS) remained largely unknown. PURPOSE: To develop and validate the scale on Dynamics of Health Technology Diffusion in Integrated Care System (DHTDICS) for providing an instrument to investigate the health technology diffusion in the ICS in China, by taking the Des-gamma-Carboxy Prothrombin (DCP) test as an example. METHODS: Based on previous classical theories such as the theory of planned behavior (TPB), technology acceptance model (TAM), and technology-organization-environment framework (TOE), the scale with 34 items was initially developed. It was tested in a cross-sectional questionnaire survey including 246 participants from February to August 2019 in China. Cronbach’s alpha, corrected item-total correlation, and factor loadings were used to assess reliability. Exploratory factor analysis and confirmatory factor analysis were applied to evaluate the validity by assessing factor structures and correlations. RESULTS: Reliability analysis revealed excellent internal consistency. Acceptable validity was confirmed through tests of convergent validity and discriminant validity. Regarding the domains that DHTDICS contributes, the results highlighted 4 domains: personal beliefs (including dimensions of attitudes, subjective norms and perceived behavioral control), technical drivers (including dimensions of ease of use and price rationality), organizational readiness (including dimensions of organizational culture, technology absorptive willingness and technology sharing willingness), and external environment (dimension of industry competition pressure). CONCLUSION: The findings confirmed the reliability and validity of the scale on DHTDICS. The scale will be not only a scientific tool in determining the dynamics of health technology diffusion in the ICS, but also a helpful reference for developing future interventions to promote health technology diffusion.