When, where, who, what, and why? The five Ws of workflow analysis for implementing an AI decision support tool at the intensive care

There has been a surge in the development of clinical artificial intelligence (AI) decision support tools. Yet, few of these tools have been implemented into clinical practice. A lack of understanding of the clinical workflow may hamper implementation. This study develops and illustrates a method for the analysis of a clinical decision-making workflow at the ICU to facilitate the safe and efficient implementation of an AI decision support tool. A method is proposed that uses observations to study the context in which clinical decisions occur (physical workflow), and the key factors influencing decision-making (cognitive workflow). This approach provides a comprehensive understanding of the ‘when’, ‘where’, ‘who’, ‘what’, and ‘why’ of the decision-making process. The method was applied to a use case involving the decision to discharge a patient from the ICU to the regular ward. The results showed that the proposed methodology effectively provided a thorough understanding of the physical workflow, in terms of time, location, actors, and materials for receiving decision support with AI. Additionally, it identified the key factors influencing the cognitive workflow. We presented a method for the workflow analysis of clinical decision-making at the ICU before AI implementation. A thorough understanding of the clinical workflow is essential for implementation of an AI decision support tool. This method forms a blueprint and further validation is needed for other clinical contexts.

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Publication Details

Journal
Human Factors in Healthcare
Published
2025-02-20
DOI
https://doi.org/10.1016/j.hfh.2025.100095
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31

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article

When, where, who, what, and why? The five Ws of workflow analysis for implementing an AI decision support tool at the intensive care

Giovanni Cinà, Steffen Lange, Anne de Hond, M. Sesmu Arbous et al.
2 citations
Human Factors in Healthcare
Artificial Intelligence in Healthcare and Education
1.31
article

When, where, who, what, and why? The five Ws of workflow analysis for implementing an AI decision support tool at the intensive care

Giovanni Cinà, Steffen Lange, Anne de Hond, M. Sesmu Arbous, Ewout W. Steyerberg, Suzanne Vosslamber, Friso Engel, Mette Lindhout, Puck Noorlag
article en
2 citations

Abstract

There has been a surge in the development of clinical artificial intelligence (AI) decision support tools. Yet, few of these tools have been implemented into clinical practice. A lack of understanding of the clinical workflow may hamper implementation. This study develops and illustrates a method for the analysis of a clinical decision-making workflow at the ICU to facilitate the safe and efficient implementation of an AI decision support tool. A method is proposed that uses observations to study the context in which clinical decisions occur (physical workflow), and the key factors influencing decision-making (cognitive workflow). This approach provides a comprehensive understanding of the ‘when’, ‘where’, ‘who’, ‘what’, and ‘why’ of the decision-making process. The method was applied to a use case involving the decision to discharge a patient from the ICU to the regular ward. The results showed that the proposed methodology effectively provided a thorough understanding of the physical workflow, in terms of time, location, actors, and materials for receiving decision support with AI. Additionally, it identified the key factors influencing the cognitive workflow. We presented a method for the workflow analysis of clinical decision-making at the ICU before AI implementation. A thorough understanding of the clinical workflow is essential for implementation of an AI decision support tool. This method forms a blueprint and further validation is needed for other clinical contexts.

Human Factors in HealthcareVol. 7
Leiden University (NL), Leiden University Medical Center (NL), Amsterdam UMC Location University of Amsterdam (NL), University Medical Center Utrecht (NL), GGD Amsterdam (NL), Amsterdam University Medical Centers (NL), University of Amsterdam (NL)
Health~Holland
Peace, Justice and strong institutions
Openalex Percentile: Top 17%
Artificial Intelligence in Healthcare and Education
1.31
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