Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS)

Wenjuan Fan (), Jingnan Liu, Shuwan Zhu and Panos M. Pardalos
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Wenjuan Fan: Hefei University of Technology
Jingnan Liu: Hefei University of Technology
Shuwan Zhu: Hefei University of Technology
Panos M. Pardalos: University of Florida

Annals of Operations Research, 2020, vol. 294, issue 1, No 25, 567-592

Abstract: Abstract Compared to the booming industry of AIMDSS, the usage of AIMDSS among healthcare professionals is relatively low in the hospital. Thus, a research on the acceptance and adoption intention of AIMDSS by health professionals is imperative. In this study, an integration of Unified theory of user acceptance of technology and trust theory is proposed for exploring the adoption of AIMDSS. Besides, two groups of additional factors, related to AIMDSS (task complexity, technology characteristics, and perceived substitution crisis) and health professionals’ characteristics (propensity to trust and personal innovativeness in IT) are considered in the integrated model. The data set of proposed research model is collected through paper survey and Internet survey in China. The empirical examination demonstrates a high predictive power of this proposed model in explaining AIMDSS adoption. Finally, the theoretical contribution and practical implications of this research are discussed.

Keywords: AIMDSS; UTAUT; Adopt intention; Initial trust (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s10479-018-2818-y

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