Cargando…

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England

BACKGROUND: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In t...

Descripción completa

Detalles Bibliográficos
Autores principales: Leclerc, Quentin J., Fuller, Naomi M., Keogh, Ruth H., Diaz-Ordaz, Karla, Sekula, Richard, Semple, Malcolm G., Atkins, Katherine E., Procter, Simon R., Knight, Gwenan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188158/
https://www.ncbi.nlm.nih.gov/pubmed/34107928
http://dx.doi.org/10.1186/s12913-021-06509-x
_version_ 1783705282116845568
author Leclerc, Quentin J.
Fuller, Naomi M.
Keogh, Ruth H.
Diaz-Ordaz, Karla
Sekula, Richard
Semple, Malcolm G.
Atkins, Katherine E.
Procter, Simon R.
Knight, Gwenan M.
author_facet Leclerc, Quentin J.
Fuller, Naomi M.
Keogh, Ruth H.
Diaz-Ordaz, Karla
Sekula, Richard
Semple, Malcolm G.
Atkins, Katherine E.
Procter, Simon R.
Knight, Gwenan M.
author_sort Leclerc, Quentin J.
collection PubMed
description BACKGROUND: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. METHODS: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. RESULTS: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. CONCLUSIONS: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. TRIAL REGISTRATION: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06509-x.
format Online
Article
Text
id pubmed-8188158
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-81881582021-06-09 Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England Leclerc, Quentin J. Fuller, Naomi M. Keogh, Ruth H. Diaz-Ordaz, Karla Sekula, Richard Semple, Malcolm G. Atkins, Katherine E. Procter, Simon R. Knight, Gwenan M. BMC Health Serv Res Research Article BACKGROUND: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. METHODS: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. RESULTS: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. CONCLUSIONS: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. TRIAL REGISTRATION: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06509-x. BioMed Central 2021-06-09 /pmc/articles/PMC8188158/ /pubmed/34107928 http://dx.doi.org/10.1186/s12913-021-06509-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Leclerc, Quentin J.
Fuller, Naomi M.
Keogh, Ruth H.
Diaz-Ordaz, Karla
Sekula, Richard
Semple, Malcolm G.
Atkins, Katherine E.
Procter, Simon R.
Knight, Gwenan M.
Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
title Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
title_full Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
title_fullStr Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
title_full_unstemmed Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
title_short Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England
title_sort importance of patient bed pathways and length of stay differences in predicting covid-19 hospital bed occupancy in england
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188158/
https://www.ncbi.nlm.nih.gov/pubmed/34107928
http://dx.doi.org/10.1186/s12913-021-06509-x
work_keys_str_mv AT leclercquentinj importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT fullernaomim importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT keoghruthh importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT diazordazkarla importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT sekularichard importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT semplemalcolmg importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT atkinskatherinee importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT proctersimonr importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland
AT knightgwenanm importanceofpatientbedpathwaysandlengthofstaydifferencesinpredictingcovid19hospitalbedoccupancyinengland