Imperial College London
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Dr Benita Cox

Business School

Pastoral Care Tutor
 
 
 
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Contact

 

+44 (0)20 7594 9164b.cox

 
 
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Location

 

456ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Cecula:2021:10.1016/j.heliyon.2021.e06626,
author = {Cecula, P and Yu, J and Dawoodbhoy, F and Delaney, J and Tan, J and Peacock, I and Cox, B},
doi = {10.1016/j.heliyon.2021.e06626},
journal = {Heliyon},
title = {Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review},
url = {http://dx.doi.org/10.1016/j.heliyon.2021.e06626},
volume = {7},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Cecula,P
AU  - Yu,J
AU  - Dawoodbhoy,F
AU  - Delaney,J
AU  - Tan,J
AU  - Peacock,I
AU  - Cox,B
DO  - 10.1016/j.heliyon.2021.e06626
PY  - 2021///
SN  - 2405-8440
TI  - Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review
T2  - Heliyon
UR  - http://dx.doi.org/10.1016/j.heliyon.2021.e06626
UR  - http://hdl.handle.net/10044/1/89076
VL  - 7
ER  -
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