AI Clinical Support and Healthcare Worker Satisfaction

This paper, titled “Healthcare professionals satisfaction and AI-based clinical decision support system in public sector hospitals during health crises: a cross-sectional study,” was authored by Nisar Ahmad, Shaofu Du, Fawad Ahmed, Noor ul Amin, and Xu Yi. It was published in Information Technology and Management in 2025.

Overview of the Article: The global focus shifted to digital health management systems following the COVID-19 pandemic, emphasizing the need for information systems that provide health support and minimize the impact of healthcare emergencies. Artificial intelligence (AI) offers alternative techniques, such as Clinical Decision Support Systems (CDSS), which are crucial for managing complex scenarios involving large data volumes, ensuring information accuracy, handling high patient turnover, and improving health management during crises like COVID-19. CDSS utilizes AI-based health information systems (HIS) to be helpful, fast, and effective, offering advanced techniques in emergencies.

This study aims to identify the factors that influence the adoption of CDSS in public sector hospitals, specifically examining the mechanisms that affect healthcare professionals’ (HCP) satisfaction and their intention to use these systems. The research addresses a gap in the literature by providing empirical evidence through a quantitative survey, building upon previous qualitative studies.

Methodology and Framework: The authors based their study on DeLone and McLean’s information system success model (D&M and ISSM), a widely accepted framework for evaluating information systems (IS). They recruited 237 on-duty HCP from three major public hospitals in Wuhan, China, in 2021, collecting data through an online survey questionnaire. The questionnaire measured perceptions of IS success attributes, focusing on five dimensions: information quality, system quality, service quality, HCP satisfaction, and intention to use CDSS. Data analysis was primarily performed using SmartPLS 3.2.8.

Key Findings: The empirical findings demonstrate a strong influence of IS qualities (system, information, and service quality) on user satisfaction. Specifically, the study found that:

• Information quality has a significant positive impact on HCP satisfaction.
• System quality has a significant positive impact on HCP satisfaction.
• Service quality has a significant positive impact on HCP satisfaction.
• Furthermore, HCP satisfaction significantly influences the intention to adopt CDSS.

These results affirm that a better-quality system facilitates the successful implementation of CDSS by enhancing HCP satisfaction, which, in turn, drives CDSS adoption. The study’s findings provide a crucial foundation for CDSS adoption, especially in developing countries.

Implications: The research highlights the importance of addressing HCP satisfaction for successful technological change in healthcare. It suggests that hospital administration and government policies should prioritize adequate training, user support, and infrastructure to meet IS criteria for CDSS. HCP participation throughout the CDSS development cycle is also identified as critical for delivering high-quality systems.

Reference: Ahmad, N., Du, S., Ahmed, F., Amin, N. U., & Yi, X. (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, 26, 205–217. https://doi.org/10.1007/s10799-023-00407-w