Minimum and optimal numbers of psychiatric beds: expert consensus using a Delphi process
Author
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Mundt, Adrian P.
Author
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Rozas Serri, Enzo Fernando
Author
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Irarrázaval, Matías
Author
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O'Reilly, Richard
Author
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Allison, Stephen
Author
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Bastiampillai, Tarun
Author
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Musisi, Seggane
Author
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Kagee, Ashraf
Author
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Golenkov, Andrei
Author
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El-Khoury, Joseph
Author
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Park, Seon-Cheol
Author
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Chwastiak, Lydia
Author
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Priebe, Stefan
Admission date
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2022-12-22T21:00:24Z
Available date
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2022-12-22T21:00:24Z
Publication date
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2022
Cita de ítem
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Molecular Psychiatry (2022) 27:1873 – 1879
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Identifier
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10.1038/s41380-021-01435-0
Identifier
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https://repositorio.uchile.cl/handle/2250/189976
Abstract
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The required minimum number of psychiatric inpatient beds is highly debated and has substantial resource implications. The
present study used the Delphi method to try to reach a global consensus on the minimum and optimal psychiatric bed numbers.
An international board of scientific advisors nominated the Delphi panel members. In the first round, the expert panel provided
responses exploring estimate ranges for a minimum to optimal numbers of psychiatric beds and three levels of shortage. In a
second round, the panel reconsidered their responses using the input from the total group to achieve consensus. The Delphi panel
comprised 65 experts (42% women, 54% based in low- and middle-income countries) from 40 countries in the six regions of the
World Health Organization. Sixty psychiatric beds per 100 000 population were considered optimal and 30 the minimum, whilst
25–30 was regarded as mild, 15–25 as moderate, and less than 15 as severe shortage. This is the first expert consensus on minimum
and optimal bed numbers involving experts from HICs and LMICs. Many high-income countries have psychiatric bed numbers that
fall within the recommended range. In contrast, the number of beds in many LMIC is below the minimum recommended rate.
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Patrocinador
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Agencia Nacional de Investigacion y Desarrollo, Chile, FONDECYT Regular 1190613
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Lenguage
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en
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Publisher
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Springernature
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Type of license
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Attribution-NonCommercial-NoDerivs 3.0 United States