![]() ![]() Follow-up could be conducted until 8 March 2021, at which point the dataset was closed. The datasets used in analyses in this paper are drawn from a population of all patients with a symptom onset date, or hospital admission date, recorded between March and December 2020 inclusive. Additional data contributed to ISARIC via other mechanisms have not been included due to differences in data structure. ![]() MethodsĪs previously described ( ISARIC Clinical Characterisation Group, 2021), eligible for recruitment were patients with confirmed or suspected COVID-19 infection admitted to an ISARIC partner site and submitted to the ISARIC-hosted REDCap system. We use this dataset to determine whether these variables did indeed change over the course of the SARS-CoV-2 pandemic during 2020, and where there are changes, explore if there are predictable influences that account for this. This is to our knowledge the largest, prospective international cohort including standardised clinical data, and, as of the time of writing, includes data collected from 26 January 2020 to 20 September 2021 on 708,085 people hospitalised with COVID-19 in 1669 sites in 64 countries. In this paper, we assess temporal changes in hospital admission, length of stay, and escalation of care for hospitalised patients with SARS-CoV-2 infection included in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol International cohort ( ISARIC Clinical Characterisation Group, 2020). ![]() We hypothesise that there is significant variation in the patient journey over a pandemic period, and that this variability may limit the way these data can be responsibly used. There may also be changes in policy to admit patients for indications that are not clinical – such as to facilitate effective quarantine ( Wuhan Novel Coronavirus, 2021) or supervise provision of treatments in clinical trials. ventilators, intensive care beds, staff) that may be rationed during the peak of a pandemic, but abundant at other phases of an outbreak ( Tyrrell et al., 2021 National Institute for Health and Care Excellence, 2021 Pagel et al., 2020). However, decisions about whether to admit or escalate care are also dependent on logistic factors such as the availability of resources (e.g. Moreover, the introduction of effective treatments ( Rochwerg et al., 2020) and standardisation of care may rapidly reduce the severity or time course of illness ( Dennis et al., 2021). There are changes in clinical practice ( World Health Organisation, 2021) – clinical understanding of the natural history of diseases improves with time ( Docherty et al., 2021), and so too does confidence in safe discharge criteria or in alternative models of care ( Rojek and Horby, 2016), such as remote monitoring ( Nunan et al., 2020 Bell et al., 2021). Often, the extent to which patient journeys vary during an epidemic is not understood. And for clinical research, these measures are used as trial outcomes to determine the efficacy of novel treatments. Policy makers use these data to inform system wide planning for staffing, infrastructure, to predict requirements for consumables (such as personal protective equipment), and to assess performance of the hospital system. Clinicians use these data as a proxy for disease severity, and to provide prognostic information to patients and their families. Royal Melbourne Hospital, Melbourne, Australia Centre for Integrated Critical Care, University of Melbourne, Australia ĭuring an epidemic or pandemic of a novel infectious disease, variations in the duration of each stage of a hospitalised patient’s progress from symptom onset, to hospital admission, and hence to outcome are critical for an effective response.Infectious Diseases Data Observatory, Centre for Tropical Medicine and Global Health, University of Oxford, United Kingdom.MRC Population Health Research Unit, Clinical Trials Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom.MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics and Department of Infectious Disease Epidemiology, Imperial College London, United Kingdom.Department of Statistics, University of Oxford, United Kingdom.ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, United Kingdom.Big Data Institute, Nuffield Department of Medicine, University of Oxford, United Kingdom. ![]()
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