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Healthcare professionals satisfaction and AI-based clinical decision support system in public sector hospitals during health crises: a cross-sectional study

Author

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  • Nisar Ahmad

    (University of Science and Technology of China)

  • Shaofu Du

    (University of Science and Technology of China)

  • Fawad Ahmed

    (Entrepreneur College, (Taicang), Xian Jiaotong-Liverpool University)

  • Noor ul Amin

    (University of Science and Technology of China)

  • Xu Yi

    (University of Science and Technology of China)

Abstract

The entire world’s focus has shifted to a digital health management system after the COVID-19 pandemic and crisis management through information systems that provide potential health support and minimize the effects of similar healthcare emergencies. Artificial intelligence (AI) can create alternative techniques such as Clinical Decision Support System (CDSS), which can aid complex scenarios such as large volumes of data, information accuracy, patient turnover, and health management regimes. CDSS uses an AI-based health information system that is helpful, fast, effective, and offers advanced techniques in emergencies and pandemics such as COVID-19. Therefore, it is essential to analyze mechanisms that can influence the degree of health care professionals (HCP) satisfaction and intention to adopt CDSS. Based on DeLone and McLean’s information system success model (D&M and ISSM), the researchers recruited 237 on-duty HCP from three major hospitals in Wuhan, China, in 2021. Data is collected through an online survey questionnaire with the consent of the hospital administration. The empirical findings show the strong influence of IS qualities (system, information, and service quality) and user satisfaction. These findings support the foundation for CDSS adoption in developing countries.

Suggested Citation

  • Nisar Ahmad & Shaofu Du & Fawad Ahmed & Noor ul Amin & Xu Yi, 2025. "Healthcare professionals satisfaction and AI-based clinical decision support system in public sector hospitals during health crises: a cross-sectional study," Information Technology and Management, Springer, vol. 26(2), pages 205-217, June.
    • Handle: RePEc:spr:infotm:v:26:y:2025:i:2:d:10.1007_s10799-023-00407-w
    DOI: 10.1007/s10799-023-00407-w
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    References listed on IDEAS

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