Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.
Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.
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DOI：
10.1186/s12913-021-06509-x
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发表时间：
2021-06-09
影响因子：
2.8
通讯作者：
Knight GM
中科院分区：
文献类型：
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作者：
Leclerc QJ;Fuller NM;Keogh RH;Diaz-Ordaz K;Sekula R;Semple MG;ISARIC4C Investigators;CMMID COVID-19 Working Group;Atkins KE;Procter SR;Knight GM
预测COVID-19住院患者的床位占用率需要了解住院时间（LoS），特别是床位类型。LoS可以根据患者的“床路径”而变化-在住院期间在床类型之间转移个体患者的顺序。在这项研究中，我们分析了这些途径，以及它们对预测医院床位占用率的影响。我们从大学学院医院（UCH）和ISARIC 4C COVID-19临床信息网络（CO-CIN）获得了需要在普通病房或重症监护（CC）病床上接受护理的COVID-19住院患者的数据，以确定可能的病床路径和LoS。我们开发了一个离散时间模型来研究使用床路径或仅使用床类型的平均LoS来预测床占用率的影响。我们将模型预测的床位入住率与2020年3月至8月期间英格兰COVID-19的公开床位入住率数据进行了比较。在UCH和CO-CIN数据集中，82%的COVID-19住院患者仅在普通病房床位接受护理。我们确定了两个数据集中存在的其他四个床路径：“Ward，CC，Ward”，“Ward，CC”，“CC”和“CC，Ward”。平均LoS因床类型、路径和数据集而异，在1.78和13.53天之间。对于UCH，我们发现使用床路径提高了床占用率预测的准确性，而仅使用每种床类型的平均LoS低估了真实的床占用率。然而，使用CO-CIN LoS数据集，我们无法复制英格兰过去的床位占用数据，这表明区域LoS异质性。我们确定了五个床的途径，与床类型，途径和地理的LoS的实质性变化。这可能是由患者特征、临床护理策略或资源可用性的地方差异引起的，并表明全国LoS平均值可能不适合用于COVID-19的床位占用率的地方预测。ISARIC WHO CCP-UK研究ISRCTN 66726260于2020年4月21日回顾性注册，并被NIHR指定为紧急公共卫生研究。在线版本包含补充材料，可通过10.1186/s12913-021-06509-x获得。
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. 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. 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. 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. The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR. The online version contains supplementary material available at 10.1186/s12913-021-06509-x.