Effect of COVID-19 on Critical ICU Capacity in US Acute Care Hospitals

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Abstract

Importance

The current wave of COVID-19 infections has led to media reports of ICUs across the country reaching critical capacity. But the degree to which this has happened and community and institutional characteristics of hospitals where capacity limits have been reached is largely unknown.

Objective

To determine changes in intensive care capacity in US acute care hospitals between September and early December, 2020 and to identify whether hospitals serving more vulnerable populations were more likely to exceed critical-levels of ICU occupancy.

Design, Setting, and Participants

Retrospective observational cohort of US acute care hospitals reporting to the US Department of Health and Human Services (HHS) from September 4, 2020 to December 3, 2020. Hospitals in this cohort were compared to all US acute care hospitals. Multivariate logistic regression was used to assess the relationship between community socioeconomic factors and hospital-structural features with a hospital reaching critical ICU capacity.

Exposure

Community-level socioeconomic status and hospital-structural features

Main Outcomes and Measures

Our primary outcome was reaching critical ICU capacity (>90%) for at least two weeks since September 4. Secondary outcomes included the weekly capacity and occupancy tabulated by state and by hospital referral region.

Results

1,791 hospitals had unsuppressed ICU capacity data in the HHS Protect dataset, with 45% of hospitals reaching critical ICU capacity for at least two weeks during the study period. Hospitals in the South (OR = 2.79, p<0.001), Midwest (OR = 1.76, p=0.01) and West (OR = 1.85, p<0.01) were more likely to reach critical capacity than those in the Northeast. For-profit hospitals (OR = 2.15, p<0.001), rural hospitals (OR = 1.40, p<0.05) and hospitals in areas of high uninsurance (OR = 1.94, p<0.001) were more likely to reach critical ICU capacity, while hospitals with more intensivists (OR = 0.92, p=0.044 and higher nurse-bed ratios (OR = 0.95, p=0.013) were less likely to reach critical capacity.

Conclusions and Relevance

Nearly half of U.S. hospitals reporting data to HHS Protect have reached critical capacity at some point since September. Those that are better resourced with staff were less likely to do so while for for-profit hospitals and those in poorer communities were more likely to reach capacity. Continued non-pharmacologic interventions are clearly needed to spread of the disease to ensure ICUs remain open for all patients needing critical care.

Key Points

Question

With an increasing number of SARS-CoV2 infections , how has the burden on ICU capacity changed over the past three months and what community and institutional factors are associated with hospitals reaching critical capacity?

Finding

45% of US acute care hospitals have reached critical ICU capacity at some point over the past three months. Hospital located in areas with fewer insured people were more likely to reach critical ICU capacity. At an institutional level, for-profit hospitals, rural hospitals, and those that have less baseline staffing of intensivists and nurses were more likely to reach critical ICU capacity.

Meaning

The COVID-19 pandemic appears to be disproportionately straining ICUs with fewer resources and staff, setting up a substantial risk to widen disparities in access to care for already underserved populations.

Article activity feed

  1. SciScore for 10.1101/2020.12.16.20248366: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was exempt by the institutional review board of the Harvard T. H. Chan School of Public Health
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.