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Digital mental health
Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations
  1. Alvaro Barrera1,2,
  2. Carol Gee2,
  3. Andrew Wood2,
  4. Oliver Gibson3,
  5. Daniel Bayley3,
  6. John Geddes1,2
  1. 1 University of Oxford, Oxford, UK
  2. 2 Oxford Health NHS Foundation Trust, Oxford, Oxfordshire, UK
  3. 3 Oxehealth, Oxford, UK
  1. Correspondence to Dr Alvaro Barrera, University of Oxford, Oxford OX1 2JD, UK; alvaro.barrera{at}psych.ox.ac.uk

Abstract

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.

  • adult psychiatry
  • Schizophrenia & psychotic disorders
  • suicide & self-harm
  • depression & mood disorders
http://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/.

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Footnotes

  • Funding The study was supported by the National Institute for Health Research (NIHR), Oxford Health Biomedical Research Centre and the NIHR Oxford Collaboration for Leadership in Applied Health Research and Care.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available upon request. The data are deidentified participant data, available from the corresponding author.

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