Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review
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...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844021007295 |
| _version_ | 1818940584047411200 |
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| author | Paulina Cecula Jiakun Yu Fatema Mustansir Dawoodbhoy Jack Delaney Joseph Tan Iain Peacock Benita Cox |
| author_facet | Paulina Cecula Jiakun Yu Fatema Mustansir Dawoodbhoy Jack Delaney Joseph Tan Iain Peacock Benita Cox |
| author_sort | Paulina Cecula |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T06:41:58Z |
| format | Article |
| id | doaj.art-b63430c658124e6996440df682c056e0 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-12-20T06:41:58Z |
| publishDate | 2021-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-b63430c658124e6996440df682c056e02022-12-21T19:49:49ZengElsevierHeliyon2405-84402021-04-0174e06626Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature reviewPaulina Cecula0Jiakun Yu1Fatema Mustansir Dawoodbhoy2Jack Delaney3Joseph Tan4Iain Peacock5Benita Cox6Imperial College London Business School, London, UK; Imperial College School of Medicine, South Kensington Campus, London, SW7 2BU, UKImperial College London Business School, London, UK; Imperial College School of Medicine, South Kensington Campus, London, SW7 2BU, UKImperial College London Business School, London, UK; Imperial College School of Medicine, South Kensington Campus, London, SW7 2BU, UK; Corresponding author.Imperial College London Business School, London, UK; Imperial College School of Medicine, South Kensington Campus, London, SW7 2BU, UKImperial College London Business School, London, UK; Brighton and Sussex Medical School, Brighton, East Sussex, BN1 9PX, UKImperial College London Business School, London, UK; Brighton and Sussex Medical School, Brighton, East Sussex, BN1 9PX, UKImperial College London Business School, London, UKBackground: 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.http://www.sciencedirect.com/science/article/pii/S2405844021007295Mental healthPatient flowArtificial intelligenceNational health serviceInpatient units |
| spellingShingle | Paulina Cecula Jiakun Yu Fatema Mustansir Dawoodbhoy Jack Delaney Joseph Tan Iain Peacock Benita Cox Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review Heliyon Mental health Patient flow Artificial intelligence National health service Inpatient units |
| title | Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review |
| title_full | Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review |
| title_fullStr | Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review |
| title_full_unstemmed | Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review |
| title_short | Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review |
| title_sort | applications of artificial intelligence to improve patient flow on mental health inpatient units narrative literature review |
| topic | Mental health Patient flow Artificial intelligence National health service Inpatient units |
| url | http://www.sciencedirect.com/science/article/pii/S2405844021007295 |
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