Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review. Issue 4 (April 2021)
- Record Type:
- Journal Article
- Title:
- Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review. Issue 4 (April 2021)
- Main Title:
- Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review
- Authors:
- Cecula, Paulina
Yu, Jiakun
Dawoodbhoy, Fatema Mustansir
Delaney, Jack
Tan, Joseph
Peacock, Iain
Cox, Benita - Abstract:
- Abstract: Background: Despite a growing body of research into both Artificial intelligence and mental health inpatient flow issues, few studies adequately combine the two. This review summarises findings in the fields of AI in psychiatry and patient flow from the past 5 years, finds links and identifies gaps for future research. Methods: The OVID database was used to access Embase and Medline. Top journals such as JAMA, Nature and The Lancet were screened for other relevant studies. Selection bias was limited by strict inclusion and exclusion criteria. Research: 3, 675 papers were identified in March 2020, of which a limited number focused on AI for mental health unit patient flow. After initial screening, 323 were selected and 83 were subsequently analysed. The literature review revealed a wide range of applications with three main themes: diagnosis (33%), prognosis (39%) and treatment (28%). The main themes that emerged from AI in patient flow studies were: readmissions (41%), resource allocation (44%) and limitations (91%). The review extrapolates those solutions and suggests how they could potentially improve patient flow on mental health units, along with challenges and limitations they could face. Conclusion: Research widely addresses potential uses of AI in mental health, with some focused on its applicability in psychiatric inpatients units, however research rarely discusses improvements in patient flow. Studies investigated various uses of AI to improve patient flowAbstract: Background: Despite a growing body of research into both Artificial intelligence and mental health inpatient flow issues, few studies adequately combine the two. This review summarises findings in the fields of AI in psychiatry and patient flow from the past 5 years, finds links and identifies gaps for future research. Methods: The OVID database was used to access Embase and Medline. Top journals such as JAMA, Nature and The Lancet were screened for other relevant studies. Selection bias was limited by strict inclusion and exclusion criteria. Research: 3, 675 papers were identified in March 2020, of which a limited number focused on AI for mental health unit patient flow. After initial screening, 323 were selected and 83 were subsequently analysed. The literature review revealed a wide range of applications with three main themes: diagnosis (33%), prognosis (39%) and treatment (28%). The main themes that emerged from AI in patient flow studies were: readmissions (41%), resource allocation (44%) and limitations (91%). The review extrapolates those solutions and suggests how they could potentially improve patient flow on mental health units, along with challenges and limitations they could face. Conclusion: Research widely addresses potential uses of AI in mental health, with some focused on its applicability in psychiatric inpatients units, however research rarely discusses improvements in patient flow. Studies investigated various uses of AI to improve patient flow across specialities. This review highlights a gap in research and the unique research opportunity it presents. Abstract : Mental Health, Patient Flow, Artificial Intelligence, National Health Service, Inpatient Units … (more)
- Is Part Of:
- Heliyon. Volume 7:Issue 4(2021)
- Journal:
- Heliyon
- Issue:
- Volume 7:Issue 4(2021)
- Issue Display:
- Volume 7, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 7
- Issue:
- 4
- Issue Sort Value:
- 2021-0007-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04
- Subjects:
- Mental health -- Patient flow -- Artificial intelligence -- National health service -- Inpatient units
Research -- Periodicals
Medical sciences -- Periodicals
Natural history -- Periodicals
Social sciences -- Periodicals
Earth sciences -- Periodicals
Physical sciences -- Periodicals
507.2 - Journal URLs:
- http://www.sciencedirect.com/science/journal/24058440/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.heliyon.2021.e06626 ↗
- Languages:
- English
- ISSNs:
- 2405-8440
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22867.xml