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Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations
BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures patient safety, it can also disturb patients’ sleep, w...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034347/ https://www.ncbi.nlm.nih.gov/pubmed/32046991 http://dx.doi.org/10.1136/ebmental-2019-300136 |
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author | Barrera, Alvaro Gee, Carol Wood, Andrew Gibson, Oliver Bayley, Daniel Geddes, John |
author_facet | Barrera, Alvaro Gee, Carol Wood, Andrew Gibson, Oliver Bayley, Daniel Geddes, John |
author_sort | Barrera, Alvaro |
collection | PubMed |
description | BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures patient safety, it can also disturb patients’ sleep, which in turn can impact negatively on their recovery. OBJECTIVE: This article describes the process of introducing artificial intelligence (‘digitally assisted nursing observations’) in an acute mental health inpatient ward, to enable staff to carry out the hourly and the 15 minutes observations, minimising disruption of patients’ sleep while maintaining their safety. FINDINGS: The preliminary data obtained indicate that the digitally assisted nursing observations agreed with the observations without sensors when both were carried out in parallel and that over an estimated 755 patient nights, the new system has not been associated with any untoward incidents. Preliminary qualitative data suggest that the new technology improves patients’ and staff’s experience at night. DISCUSSION: This project suggests that the digitally assisted nursing observations could maintain patients’ safety while potentially improving patients’ and staff’s experience in an acute psychiatric ward. The limitations of this study, namely, its narrative character and the fact that patients were not randomised to the new technology, suggest taking the reported findings as qualitative and preliminary. CLINICAL IMPLICATIONS: These results suggest that the care provided at night in acute inpatient psychiatric units could be substantially improved with this technology. This warrants a more thorough and stringent evaluation. |
format | Online Article Text |
id | pubmed-7034347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-70343472020-03-03 Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations Barrera, Alvaro Gee, Carol Wood, Andrew Gibson, Oliver Bayley, Daniel Geddes, John Evid Based Ment Health Original Research BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures patient safety, it can also disturb patients’ sleep, which in turn can impact negatively on their recovery. OBJECTIVE: This article describes the process of introducing artificial intelligence (‘digitally assisted nursing observations’) in an acute mental health inpatient ward, to enable staff to carry out the hourly and the 15 minutes observations, minimising disruption of patients’ sleep while maintaining their safety. FINDINGS: The preliminary data obtained indicate that the digitally assisted nursing observations agreed with the observations without sensors when both were carried out in parallel and that over an estimated 755 patient nights, the new system has not been associated with any untoward incidents. Preliminary qualitative data suggest that the new technology improves patients’ and staff’s experience at night. DISCUSSION: This project suggests that the digitally assisted nursing observations could maintain patients’ safety while potentially improving patients’ and staff’s experience in an acute psychiatric ward. The limitations of this study, namely, its narrative character and the fact that patients were not randomised to the new technology, suggest taking the reported findings as qualitative and preliminary. CLINICAL IMPLICATIONS: These results suggest that the care provided at night in acute inpatient psychiatric units could be substantially improved with this technology. This warrants a more thorough and stringent evaluation. BMJ Publishing Group 2020-02 2020-02-11 /pmc/articles/PMC7034347/ /pubmed/32046991 http://dx.doi.org/10.1136/ebmental-2019-300136 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Barrera, Alvaro Gee, Carol Wood, Andrew Gibson, Oliver Bayley, Daniel Geddes, John Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
title | Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
title_full | Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
title_fullStr | Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
title_full_unstemmed | Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
title_short | Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
title_sort | introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7034347/ https://www.ncbi.nlm.nih.gov/pubmed/32046991 http://dx.doi.org/10.1136/ebmental-2019-300136 |
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