Discharge to post-acute care and other predictors of prolonged length of stay during the initial COVID-19 surge: a single site analysis

Jessica C O'neil; Benjamin P Geisler; Donna Rusinak; Ingrid V Bassett; Virginia A Triant; Rachael Mckenzie; Melissa L Mattison; Amy W Baughman

doi:10.1093/intqhc/mzac098

Discharge to post-acute care and other predictors of prolonged length of stay during the initial COVID-19 surge: a single site analysis

Int J Qual Health Care. 2023 Jan 2;35(1):mzac098. doi: 10.1093/intqhc/mzac098.

Authors

Jessica C O'neil^{1

2}, Benjamin P Geisler^{1

2

3}, Donna Rusinak⁴, Ingrid V Bassett^{1

2}, Virginia A Triant^{1

2}, Rachael Mckenzie⁵, Melissa L Mattison^{1

2}, Amy W Baughman^{1

2

5}

Affiliations

¹ Department of Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
² Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA.
³ Institute for Medical Information Processing, Biometry and Epidemiology, Marchioninistr, 15, München 81377, Germany.
⁴ Performance Analysis and Improvement, Massachusetts General Hospital, 125 Nashua Street, Boston, MA 02114, USA.
⁵ Department of Case Management, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.

Abstract

Background: During the initial surge of coronavirus disease 2019 (COVID-19), health-care utilization fluctuated dramatically, straining acute hospital capacity across the USA and potentially contributing to excess mortality.

Methods: This was an observational retrospective study of patients with COVID-19 admitted to a large US urban academic medical center during a 12-week COVID-19 surge in the Spring of 2020. We describe patterns in length of stay (LOS) over time. Our outcome of interest was prolonged LOS (PLOS), which we defined as 7 or more days. We performed univariate analyses of patient characteristics, clinical outcomes and discharge disposition to evaluate the association of each variable with PLOS and developed a final multivariate model via backward elimination, wherein all variables with a P-value above 0.05 were eliminated in a stepwise fashion.

Results: The cohort included 1366 patients, of whom 13% died and 29% were readmitted within 30 days. The LOS (mean: 12.6) fell over time (P < 0.0001). Predictors of PLOS included discharge to a post-acute care (PAC) facility (odds ratio [OR]: 11.9, 95% confidence interval [CI] 2.6-54.0), uninsured status (OR 3.2, CI 1.1-9.1) and requiring intensive care and intubation (OR 18.4, CI 11.5-29.6). Patients had a higher readmission rate if discharged to PAC facilities (40%) or home with home health agency (HHA) services (38%) as compared to patients discharged home without HHA services (26%) (P < 0.0001).

Conclusion: Patients hospitalized with COVID-19 during a US COVID-19 surge had a PLOS and high readmission rate. Lack of insurance, an intensive care unit stay and a decision to discharge to a PAC facility were associated with a PLOS. Efforts to decrease LOS and optimize hospital capacity during COVID-19 surges may benefit from focusing on increasing PAC and HHA capacity and resources.

Keywords: COVID-19; bed capacity; length of stay; post–acute care; readmissions.

© The Author(s) 2023. Published by Oxford University Press on behalf of International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Publication types

Observational Study

MeSH terms

COVID-19* / epidemiology
Humans
Length of Stay
Patient Discharge*
Patient Readmission
Retrospective Studies
Risk Factors
Subacute Care

Abstract

Publication types

MeSH terms

Grants and funding