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

Authors :
Quentin J. Leclerc
Naomi M. Fuller
Ruth H. Keogh
Karla Diaz-Ordaz
Richard Sekula
Malcolm G. Semple
ISARIC4C Investigators
CMMID COVID-19 Working Group
Katherine E. Atkins
Simon R. Procter
Gwenan M. Knight
Source :
BMC Health Services Research, Vol 21, Iss 1, Pp 1-15 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
14726963
Volume :
21
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Health Services Research
Publication Type :
Academic Journal
Accession number :
edsdoj.838d57580dcb42bfb83f10f6a029eb93
Document Type :
article
Full Text :
https://doi.org/10.1186/s12913-021-06509-x