Determinants of hospital outcomes for COVID-19 infections in a large Pennsylvania Health System

  1. Pamela A. Shaw
  2. Jasper B. Yang
  3. Danielle L. Mowery
  4. Emily R. Schriver
  5. Kevin B. Mahoney
  6. Katharine J. Bar
  7. Susan S. Ellenberg

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Abstract

There is growing evidence that racial and ethnic minorities bear a disproportionate burden from COVID-19. Temporal changes in the pandemic epidemiology and diversity in the clinical course require careful study to identify determinants of poor outcomes.

We analyzed 6255 individuals admitted with PCR-confirmed COVID-19 to one of 5 hospitals in the University of Pennsylvania Health System between March 2020 and March 2021, using electronic health records to assess risk factors and outcomes through 8 weeks post-admission. Discharge, readmission and mortality outcomes were analyzed in a multi-state model with multivariable Cox models for each transition.

Mortality varied markedly over time, with cumulative incidence (95% CI) 30 days post-admission of 19.1% (16.9, 21.3) in March-April 2020, 5.7% (4.2, 7.5) in July-October 2020 and 10.5% (9.1,12.0) in January-March 2021; 26% of deaths occurred after discharge. Average age (SD) at admission varied from 62.7 (17.6) to 54.8 (19.9) to 60.5 (18.1); mechanical ventilation use declined from 21.3% to 9-11%.

Compared to Caucasian, Black race was associated with more severe disease at admission, higher rates of co-morbidities and low-income resident zip code. Between-race risk differences in mortality risk diminished in multivariable models; while admitting hospital, increasing age, admission early in the pandemic, and severe disease and low blood pressure at admission were associated with increased mortality hazard. Hispanic ethnicity was associated with fewer baseline co-morbidities and lower mortality hazard (0.57, 95% CI: 0.37, .087).

Multi-state modeling allows for a unified framework to analyze multiple outcomes throughout the disease course. Morbidity and mortality for hospitalized COVID-19 patients varied over time but post-discharge mortality remained non-trivial. Black race was associated with more risk factors for morbidity and with treatment at hospitals with lower mortality. Multivariable models suggest there are not between-race differences in outcomes. Future work is needed to better understand the identified between-hospital differences in mortality.

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  1. ScreenIT

    SciScore for 10.1101/2021.09.08.21263311: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Prior to study start, this study was approved and deemed exempt by the University of Pennsylvania Institutional Review Board (UPenn IRB).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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: We detected the following sentences addressing limitations in the study:
    A key limitation of our analysis is the reliance on EHR, which could introduce confounding if the level of completeness was disproportionally affected by ethnicity. Our findings corroborate the impact of COVID-19 in the elderly seen broadly. Patients over age 75 were at greatest risk for death and/or readmission. Improved strategies for post-discharge care of COVID-19 patients are needed to address the sustained vulnerability of these patients [23]. Passive data collection through routine electronic health records facilitates rapid research; however, the data are subject to a number of limitations. Records of comorbidities at hospital admission may be incomplete. Further, comorbidities diagnosed and treated outside the Penn health care system may not have been captured. Information regarding discharge destination (e.g. independent living or nursing home facility) was not available. Penn EHR may also have missed readmissions or deaths that occurred outside the Penn system. Linkage with federal and state registries will provide more complete data on survival, but these registries take time to be updated. Future work is needed to fully capture long-term outcomes of COVID-19.

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.09.08.21263311v1 on medRxiv