Human factors: bridging artificial intelligence and patient safety

The recent launch of complex artificial intelligence (AI) in the domain of healthcare has embedded perplexities within patients, clinicians, and policymakers. The opaque and complex nature of artificial intelligence makes it challenging for clinicians to interpret its outcome. Incorrect interpretation and poor utilization of AI might hamper patient safety. The principles of human factors and ergonomics (HFE) can assist in simplifying AI design and consecutively optimize human performance ensuring better understanding of AI outcome, their interaction with the clinical workflow. In this paper, we discuss the interactions of providers with AI and how HFE can influence these interacting components to patient safety.

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Faculty Opinions recommendation of Human factors and ergonomics as a patient safety practice.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718060610.793481653 ◽

2013 ◽

Author(s):

Yan Xiao

Keyword(s):

Patient Safety ◽

Human Factors ◽

Safety Practice ◽

Human Factors And Ergonomics

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O14 Human factors and ergonomics in the COVID19 era – learning from ICU, COVID wards and ED through the application of the (SEIPS) systems engineering initiative for patient safety model

10.1136/bmjstel-2020-aspihconf.14 ◽

2020 ◽

Author(s):

Gil Smith

Keyword(s):

Patient Safety ◽

Human Factors ◽

Systems Engineering ◽

Human Factors And Ergonomics

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Human factors challenges for the safe use of artificial intelligence in patient care

BMJ Health & Care Informatics ◽

10.1136/bmjhci-2019-100081 ◽

2019 ◽

Vol 26 (1) ◽

pp. e100081 ◽

Cited By ~ 4

Author(s):

Mark Sujan ◽

Dominic Furniss ◽

Kath Grundy ◽

Howard Grundy ◽

David Nelson ◽

...

Keyword(s):

Artificial Intelligence ◽

Human Factors ◽

Patient Care ◽

Situation Awareness ◽

Human Performance ◽

Independent Evaluation ◽

The Impact ◽

Human Factors Research

The use of artificial intelligence (AI) in patient care can offer significant benefits. However, there is a lack of independent evaluation considering AI in use. The paper argues that consideration should be given to how AI will be incorporated into clinical processes and services. Human factors challenges that are likely to arise at this level include cognitive aspects (automation bias and human performance), handover and communication between clinicians and AI systems, situation awareness and the impact on the interaction with patients. Human factors research should accompany the development of AI from the outset.

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