Abstract
Abstract
Background
From March 2020 through August 2021, 97,762 hospital-onset SARS-CoV-2 infections were detected in English hospitals. Resulting excess length of stay (LoS) created a potentially substantial health and economic burden for patients and the NHS, but we are currently unaware of any published studies estimating this excess.
Methods
We implemented appropriate causal inference methods to determine the extent to which observed additional hospital stay is attributable to the infection rather than the characteristics of the patients. Hospital admissions records were linked to SARS-CoV-2 test data to establish the study population (7.5 million) of all non-COVID-19 admissions to English hospitals from 1st March 2020 to 31st August 2021 with a stay of at least two days. The excess LoS due to hospital-onset SARS-CoV-2 infection was estimated as the difference between the mean LoS observed and in the counterfactual where infections do not occur. We used inverse probability weighted Kaplan–Meier curves to estimate the mean survival time if all hospital-onset SARS-CoV-2 infections were to be prevented, the weights being based on the daily probability of acquiring an infection. The analysis was carried out for four time periods, reflecting phases of the pandemic differing with respect to overall case numbers, testing policies, vaccine rollout and prevalence of variants.
Results
The observed mean LoS of hospital-onset cases was higher than for non-COVID-19 hospital patients by 16, 20, 13 and 19 days over the four phases, respectively. However, when the causal inference approach was used to appropriately adjust for time to infection and confounding, the estimated mean excess LoS caused by hospital-onset SARS-CoV-2 was: 2.0 [95% confidence interval 1.8–2.2] days (Mar-Jun 2020), 1.4 [1.2–1.6] days (Sep–Dec 2020); 0.9 [0.7–1.1] days (Jan–Apr 2021); 1.5 [1.1–1.9] days (May–Aug 2021).
Conclusions
Hospital-onset SARS-CoV-2 is associated with a small but notable excess LoS, equivalent to 130,000 bed days. The comparatively high LoS observed for hospital-onset COVID-19 patients is mostly explained by the timing of their infections relative to admission. Failing to account for confounding and time to infection leads to overestimates of additional length of stay and therefore overestimates costs of infections, leading to inaccurate evaluations of control strategies.
Funder
Medical Research Council
National Institute for Health Research Health Protection Research Unit
Huo Family Foundation
Publisher
Springer Science and Business Media LLC
Reference25 articles.
1. Bhattacharya A, Collin SM, Stimson J, Thelwall S, Nsonwu O, Gerver S, Robotham J, Wilcox M, Hopkins S, Hope R. Healthcare-associated COVID-19 in England: a national data linkage study. J Infect. 2021;83(5):565–72.
2. Scientific Advisory Group for Emergencies, Paper prepared by Public Health England (PHE) and the London School of Hygiene and Tropical Medicine (LSHTM). PHE and LSHTM: The contribution of nosocomial infections to the first wave, 28 January 2021. Available at: https://www.gov.uk/government/publications/phe-and-lshtm-the-contribution-of-nosocomial-infections-to-the-first-wave-28-january-2021. Accessed 5 Jan 2022.
3. Knight GM, Pham TM, Stimson J, Funk S, Jafari Y, Pople D, Evans S, Yin M, Brown CS, Bhattacharya A, Hope R. The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020. BMC Infect Dis. 2022;22(1):1–4.
4. Vekaria B, Overton C, Wiśniowski A, Ahmad S, Aparicio-Castro A, Curran-Sebastian J, Eddleston J, Hanley NA, House T, Kim J, Olsen W. Hospital length of stay for COVID-19 patients: data-driven methods for forward planning. BMC Infect Dis. 2021;21(1):1–5.
5. Rees EM, Nightingale ES, Jafari Y, Waterlow NR, Clifford S, Pearson BCA, Jombart T, Procter SR, Knight GM. COVID-19 length of hospital stay: a systematic review and data synthesis. BMC Med. 2020;18(1):1–22.
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