Cargando…
Using Artificial Intelligence in Infection Prevention
PURPOSE OF REVIEW: Artificial intelligence (AI) offers huge potential in infection prevention and control (IPC). We explore its potential IPC benefits in epidemiology, laboratory infection diagnosis, and hand hygiene. RECENT FINDINGS: AI has the potential to detect transmission events during outbrea...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7095094/ https://www.ncbi.nlm.nih.gov/pubmed/32218708 http://dx.doi.org/10.1007/s40506-020-00216-7 |
_version_ | 1783510596779507712 |
---|---|
author | Fitzpatrick, Fidelma Doherty, Aaron Lacey, Gerard |
author_facet | Fitzpatrick, Fidelma Doherty, Aaron Lacey, Gerard |
author_sort | Fitzpatrick, Fidelma |
collection | PubMed |
description | PURPOSE OF REVIEW: Artificial intelligence (AI) offers huge potential in infection prevention and control (IPC). We explore its potential IPC benefits in epidemiology, laboratory infection diagnosis, and hand hygiene. RECENT FINDINGS: AI has the potential to detect transmission events during outbreaks or predict high-risk patients, enabling development of tailored IPC interventions. AI offers opportunities to enhance diagnostics with objective pattern recognition, standardize the diagnosis of infections with IPC implications, and facilitate the dissemination of IPC expertise. AI hand hygiene applications can deliver behavior change, though it requires further evaluation in different clinical settings. However, staff can become dependent on automatic reminders, and performance returns to baseline if feedback is removed. SUMMARY: Advantages for IPC include speed, consistency, and capability of handling infinitely large datasets. However, many challenges remain; improving the availability of high-quality representative datasets and consideration of biases within preexisting databases are important challenges for future developments. AI in itself will not improve IPC; this requires culture and behavior change. Most studies to date assess performance retrospectively so there is a need for prospective evaluation in the real-life, often chaotic, clinical setting. Close collaboration with IPC experts to interpret outputs and ensure clinical relevance is essential. |
format | Online Article Text |
id | pubmed-7095094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-70950942020-03-26 Using Artificial Intelligence in Infection Prevention Fitzpatrick, Fidelma Doherty, Aaron Lacey, Gerard Curr Treat Options Infect Dis New Technologies and Advances in Infections Prevention (A Marra, Section Editor) PURPOSE OF REVIEW: Artificial intelligence (AI) offers huge potential in infection prevention and control (IPC). We explore its potential IPC benefits in epidemiology, laboratory infection diagnosis, and hand hygiene. RECENT FINDINGS: AI has the potential to detect transmission events during outbreaks or predict high-risk patients, enabling development of tailored IPC interventions. AI offers opportunities to enhance diagnostics with objective pattern recognition, standardize the diagnosis of infections with IPC implications, and facilitate the dissemination of IPC expertise. AI hand hygiene applications can deliver behavior change, though it requires further evaluation in different clinical settings. However, staff can become dependent on automatic reminders, and performance returns to baseline if feedback is removed. SUMMARY: Advantages for IPC include speed, consistency, and capability of handling infinitely large datasets. However, many challenges remain; improving the availability of high-quality representative datasets and consideration of biases within preexisting databases are important challenges for future developments. AI in itself will not improve IPC; this requires culture and behavior change. Most studies to date assess performance retrospectively so there is a need for prospective evaluation in the real-life, often chaotic, clinical setting. Close collaboration with IPC experts to interpret outputs and ensure clinical relevance is essential. Springer US 2020-03-19 2020 /pmc/articles/PMC7095094/ /pubmed/32218708 http://dx.doi.org/10.1007/s40506-020-00216-7 Text en © Springer Science+Business Media, LLC, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | New Technologies and Advances in Infections Prevention (A Marra, Section Editor) Fitzpatrick, Fidelma Doherty, Aaron Lacey, Gerard Using Artificial Intelligence in Infection Prevention |
title | Using Artificial Intelligence in Infection Prevention |
title_full | Using Artificial Intelligence in Infection Prevention |
title_fullStr | Using Artificial Intelligence in Infection Prevention |
title_full_unstemmed | Using Artificial Intelligence in Infection Prevention |
title_short | Using Artificial Intelligence in Infection Prevention |
title_sort | using artificial intelligence in infection prevention |
topic | New Technologies and Advances in Infections Prevention (A Marra, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7095094/ https://www.ncbi.nlm.nih.gov/pubmed/32218708 http://dx.doi.org/10.1007/s40506-020-00216-7 |
work_keys_str_mv | AT fitzpatrickfidelma usingartificialintelligenceininfectionprevention AT dohertyaaron usingartificialintelligenceininfectionprevention AT laceygerard usingartificialintelligenceininfectionprevention |