The potential of artificial intelligence to improve patient safety: a scoping review

Abstract Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety of care. Major adverse events in healthcare include: healthcare-associated infections, adverse drug events, venous thromboembolism, surgical complications, pressure ulcers, falls, decompensation...

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Autores principales:	David W. Bates, David Levine, Ania Syrowatka, Masha Kuznetsova, Kelly Jean Thomas Craig, Angela Rui, Gretchen Purcell Jackson, Kyu Rhee
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/ffc7611ccde44d46b91c9a2d9807c66e
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spelling	oai:doaj.org-article:ffc7611ccde44d46b91c9a2d9807c66e2021-12-02T11:39:33ZThe potential of artificial intelligence to improve patient safety: a scoping review10.1038/s41746-021-00423-62398-6352https://doaj.org/article/ffc7611ccde44d46b91c9a2d9807c66e2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00423-6https://doaj.org/toc/2398-6352Abstract Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety of care. Major adverse events in healthcare include: healthcare-associated infections, adverse drug events, venous thromboembolism, surgical complications, pressure ulcers, falls, decompensation, and diagnostic errors. The objective of this scoping review was to summarize the relevant literature and evaluate the potential of AI to improve patient safety in these eight harm domains. A structured search was used to query MEDLINE for relevant articles. The scoping review identified studies that described the application of AI for prediction, prevention, or early detection of adverse events in each of the harm domains. The AI literature was narratively synthesized for each domain, and findings were considered in the context of incidence, cost, and preventability to make projections about the likelihood of AI improving safety. Three-hundred and ninety-two studies were included in the scoping review. The literature provided numerous examples of how AI has been applied within each of the eight harm domains using various techniques. The most common novel data were collected using different types of sensing technologies: vital sign monitoring, wearables, pressure sensors, and computer vision. There are significant opportunities to leverage AI and novel data sources to reduce the frequency of harm across all domains. We expect AI to have the greatest impact in areas where current strategies are not effective, and integration and complex analysis of novel, unstructured data are necessary to make accurate predictions; this applies specifically to adverse drug events, decompensation, and diagnostic errors.David W. BatesDavid LevineAnia SyrowatkaMasha KuznetsovaKelly Jean Thomas CraigAngela RuiGretchen Purcell JacksonKyu RheeNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 David W. Bates David Levine Ania Syrowatka Masha Kuznetsova Kelly Jean Thomas Craig Angela Rui Gretchen Purcell Jackson Kyu Rhee The potential of artificial intelligence to improve patient safety: a scoping review
description	Abstract Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety of care. Major adverse events in healthcare include: healthcare-associated infections, adverse drug events, venous thromboembolism, surgical complications, pressure ulcers, falls, decompensation, and diagnostic errors. The objective of this scoping review was to summarize the relevant literature and evaluate the potential of AI to improve patient safety in these eight harm domains. A structured search was used to query MEDLINE for relevant articles. The scoping review identified studies that described the application of AI for prediction, prevention, or early detection of adverse events in each of the harm domains. The AI literature was narratively synthesized for each domain, and findings were considered in the context of incidence, cost, and preventability to make projections about the likelihood of AI improving safety. Three-hundred and ninety-two studies were included in the scoping review. The literature provided numerous examples of how AI has been applied within each of the eight harm domains using various techniques. The most common novel data were collected using different types of sensing technologies: vital sign monitoring, wearables, pressure sensors, and computer vision. There are significant opportunities to leverage AI and novel data sources to reduce the frequency of harm across all domains. We expect AI to have the greatest impact in areas where current strategies are not effective, and integration and complex analysis of novel, unstructured data are necessary to make accurate predictions; this applies specifically to adverse drug events, decompensation, and diagnostic errors.
format	article
author	David W. Bates David Levine Ania Syrowatka Masha Kuznetsova Kelly Jean Thomas Craig Angela Rui Gretchen Purcell Jackson Kyu Rhee
author_facet	David W. Bates David Levine Ania Syrowatka Masha Kuznetsova Kelly Jean Thomas Craig Angela Rui Gretchen Purcell Jackson Kyu Rhee
author_sort	David W. Bates
title	The potential of artificial intelligence to improve patient safety: a scoping review
title_short	The potential of artificial intelligence to improve patient safety: a scoping review
title_full	The potential of artificial intelligence to improve patient safety: a scoping review
title_fullStr	The potential of artificial intelligence to improve patient safety: a scoping review
title_full_unstemmed	The potential of artificial intelligence to improve patient safety: a scoping review
title_sort	potential of artificial intelligence to improve patient safety: a scoping review
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ffc7611ccde44d46b91c9a2d9807c66e
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The potential of artificial intelligence to improve patient safety: a scoping review

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