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Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study
BACKGROUND: The ability to provide medical care during sudden increases in patient volume during a disaster or other high-consequence event is a serious concern for health-care systems. Identification of inpatients for safe early discharge (ie, reverse triage) could create additional hospital surge...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138047/ https://www.ncbi.nlm.nih.gov/pubmed/17141705 http://dx.doi.org/10.1016/S0140-6736(06)69808-5 |
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author | Kelen, Gabor D Kraus, Chadd K McCarthy, Melissa L Bass, Eric Hsu, Edbert B Li, Guohua Scheulen, James J Shahan, Judy B Brill, Justin D Green, Gary B |
author_facet | Kelen, Gabor D Kraus, Chadd K McCarthy, Melissa L Bass, Eric Hsu, Edbert B Li, Guohua Scheulen, James J Shahan, Judy B Brill, Justin D Green, Gary B |
author_sort | Kelen, Gabor D |
collection | PubMed |
description | BACKGROUND: The ability to provide medical care during sudden increases in patient volume during a disaster or other high-consequence event is a serious concern for health-care systems. Identification of inpatients for safe early discharge (ie, reverse triage) could create additional hospital surge capacity. We sought to develop a disposition classification system that categorises inpatients according to suitability for immediate discharge on the basis of risk tolerance for a subsequent consequential medical event. METHODS: We did a warfare analysis laboratory exercise using evidence-based techniques, combined with a consensus process of 39 expert panellists. These panellists were asked to define the categories of a disposition classification system, assign risk tolerance of a consequential medical event to each category, identify critical interventions, and rank each (using a scale of 1–10) according to the likelihood of a resultant consequential medical event if a critical intervention is withdrawn or withheld because of discharge. FINDINGS: The panellists unanimously agreed on a five-category disposition classification system. The upper limit of risk tolerance for a consequential medical event in the lowest risk group if discharged early was less than 4%. The next categories had upper limits of risk tolerance of about 12% (IQR 8–15%), 33% (25–50%), 60% (45–80%) and 100% (95–100%), respectively. The expert panellists identified 28 critical interventions with a likelihood of association with a consequential medical event if withdrawn, ranging from 3 to 10 on the 10-point scale. INTERPRETATION: The disposition classification system allows conceptual classification of patients for suitable disposition, including those deemed safe for early discharge home during surges in demand. Clinical criteria allowing real-time categorisation of patients are awaited. |
format | Online Article Text |
id | pubmed-7138047 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71380472020-04-07 Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study Kelen, Gabor D Kraus, Chadd K McCarthy, Melissa L Bass, Eric Hsu, Edbert B Li, Guohua Scheulen, James J Shahan, Judy B Brill, Justin D Green, Gary B Lancet Article BACKGROUND: The ability to provide medical care during sudden increases in patient volume during a disaster or other high-consequence event is a serious concern for health-care systems. Identification of inpatients for safe early discharge (ie, reverse triage) could create additional hospital surge capacity. We sought to develop a disposition classification system that categorises inpatients according to suitability for immediate discharge on the basis of risk tolerance for a subsequent consequential medical event. METHODS: We did a warfare analysis laboratory exercise using evidence-based techniques, combined with a consensus process of 39 expert panellists. These panellists were asked to define the categories of a disposition classification system, assign risk tolerance of a consequential medical event to each category, identify critical interventions, and rank each (using a scale of 1–10) according to the likelihood of a resultant consequential medical event if a critical intervention is withdrawn or withheld because of discharge. FINDINGS: The panellists unanimously agreed on a five-category disposition classification system. The upper limit of risk tolerance for a consequential medical event in the lowest risk group if discharged early was less than 4%. The next categories had upper limits of risk tolerance of about 12% (IQR 8–15%), 33% (25–50%), 60% (45–80%) and 100% (95–100%), respectively. The expert panellists identified 28 critical interventions with a likelihood of association with a consequential medical event if withdrawn, ranging from 3 to 10 on the 10-point scale. INTERPRETATION: The disposition classification system allows conceptual classification of patients for suitable disposition, including those deemed safe for early discharge home during surges in demand. Clinical criteria allowing real-time categorisation of patients are awaited. Elsevier Ltd. 2006 2006-11-30 /pmc/articles/PMC7138047/ /pubmed/17141705 http://dx.doi.org/10.1016/S0140-6736(06)69808-5 Text en Copyright © 2006 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Kelen, Gabor D Kraus, Chadd K McCarthy, Melissa L Bass, Eric Hsu, Edbert B Li, Guohua Scheulen, James J Shahan, Judy B Brill, Justin D Green, Gary B Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
title | Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
title_full | Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
title_fullStr | Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
title_full_unstemmed | Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
title_short | Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
title_sort | inpatient disposition classification for the creation of hospital surge capacity: a multiphase study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138047/ https://www.ncbi.nlm.nih.gov/pubmed/17141705 http://dx.doi.org/10.1016/S0140-6736(06)69808-5 |
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