Delicate Decisions at the Intersection of Intensive Care and Machine Learning - How Human Information Needs inform the Development of Decision Support

Abstract

A hospital intensive care unit (ICU) is a complex, dynamic, high-stakes environment in which an array of health professionals monitor, make decisions and work together to keep critically ill patients alive. An ICU is also an information-rich environment where large amounts of digital information intermingle with information in the form of human observations, knowledge and communications. Clinical decision support systems (CDSS) that harness machine learning (ML), artificial intelligence (AI) and other information technologies are seen as potentially powerful allies to support clinicians. While there is a significant and growing body of research on ICU applications of ML and AI, relatively little is understood about the decision-making needs and values of the highly trained professionals responsible for decisions in that challenging information environment. We interviewed 31 ICU clinicians from 9 (mostly Queensland) institutions on their decision needs and values. This paper presents a comprehensible slice of our findings about information needs in the ICU; discusses implications for AI/ML CDSS development; and concludes with the view that clinicians and technologists face delicate decisions about the extent and nature of AI/ML CDSS in the ICU.

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