IS in Healthcare
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Paper Type
Short
Paper Number
1692
Description
Artificial intelligence (AI) applications are rapidly revolutionizing the clinical practice in recent years, from imaging to disease screening and diagnosis to treatment planning to clinical outcome prediction. Despite the promising potential of healthcare AI, extant research has primarily focused on the development and validation of AI algorithms. In contrast, few studies have examined how to incorporate AI applications into the existing clinical workflow. More research is thus needed to understand how work design factors influence AI-aided clinical decision making. Drawing from the interpersonal advice taking literature, this study aims to investigate the effects of AI-advice provision timing (i.e., independent versus dependent timing) on physicians’ advice taking behavior and decision outcomes in a clinical diagnosis setting. We will also examine the moderating role of physician expertise. To this end, we will conduct an experiment among physicians using a novel AI-based diagnostic algorithm. Theoretical and practical implications are discussed.
Recommended Citation
Yin, Jiamin; Ngiam, Kee Yuan; and Teo, Hock-Hai, "Work Design in Healthcare Artificial Intelligence Applications: The Role of Advice Provision Timing" (2020). ICIS 2020 Proceedings. 10.
https://aisel.aisnet.org/icis2020/is_health/is_health/10
Work Design in Healthcare Artificial Intelligence Applications: The Role of Advice Provision Timing
Artificial intelligence (AI) applications are rapidly revolutionizing the clinical practice in recent years, from imaging to disease screening and diagnosis to treatment planning to clinical outcome prediction. Despite the promising potential of healthcare AI, extant research has primarily focused on the development and validation of AI algorithms. In contrast, few studies have examined how to incorporate AI applications into the existing clinical workflow. More research is thus needed to understand how work design factors influence AI-aided clinical decision making. Drawing from the interpersonal advice taking literature, this study aims to investigate the effects of AI-advice provision timing (i.e., independent versus dependent timing) on physicians’ advice taking behavior and decision outcomes in a clinical diagnosis setting. We will also examine the moderating role of physician expertise. To this end, we will conduct an experiment among physicians using a novel AI-based diagnostic algorithm. Theoretical and practical implications are discussed.
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