Artificial Intelligence and Surgical Decision-making

Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes that artificial intelligence should be used to augment surgical decisio...

Full description

Saved in:
Bibliographic Details
Published in:JAMA surgery Vol. 155; no. 2; p. 148
Main Authors: Loftus, Tyler J, Tighe, Patrick J, Filiberto, Amanda C, Efron, Philip A, Brakenridge, Scott C, Mohr, Alicia M, Rashidi, Parisa, Upchurch, Jr, Gilbert R, Bihorac, Azra
Format: Journal Article
Language:English
Published: United States 01.02.2020
Subjects:
Artificial Intelligence - ethics
Clinical Decision-Making
Decision Support Systems, Clinical
Electronic Health Records
Emotions
Humans
Intuition
Surgical Procedures, Operative
Time Factors
Uncertainty
ISSN:2168-6262, 2168-6262
Online Access:Get more information
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Surgeons make complex, high-stakes decisions under time constraints and uncertainty, with significant effect on patient outcomes. This review describes the weaknesses of traditional clinical decision-support systems and proposes that artificial intelligence should be used to augment surgical decision-making. Surgical decision-making is dominated by hypothetical-deductive reasoning, individual judgment, and heuristics. These factors can lead to bias, error, and preventable harm. Traditional predictive analytics and clinical decision-support systems are intended to augment surgical decision-making, but their clinical utility is compromised by time-consuming manual data management and suboptimal accuracy. These challenges can be overcome by automated artificial intelligence models fed by livestreaming electronic health record data with mobile device outputs. This approach would require data standardization, advances in model interpretability, careful implementation and monitoring, attention to ethical challenges involving algorithm bias and accountability for errors, and preservation of bedside assessment and human intuition in the decision-making process. Integration of artificial intelligence with surgical decision-making has the potential to transform care by augmenting the decision to operate, informed consent process, identification and mitigation of modifiable risk factors, decisions regarding postoperative management, and shared decisions regarding resource use.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ISSN:2168-6262
2168-6262
DOI:10.1001/jamasurg.2019.4917