Examination of Medication Use Patterns by Age Group, Comorbidity, and Month in COVID-19 Positive Patients in a Large Statewide Health System During the Pandemic in 2020

  1. Jonathan H. Watanabe
  2. Jimmy Kwon
  3. Bin Nan
  4. Shira R. Abeles
  5. Sanjay R. Mehta

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Abstract

Background: Understanding medication use patterns for patients with COVID-19 will provide needed insight into the evolution of COVID-19 treatment over the course of the SARS-CoV-2 pandemic and aid clinical management considerations. Objectives: To systematically determine most frequently used medications among COVID-19 patients overall and by hospitalization status. Secondary objective was use measurement of medications considered potential therapeutic options. Methods: Retrospective cohort study was performed using data from the University of California COVID Research Data Set (UC CORDS) patients between March 10, 2020, and December 31, 2020. Main outcomes were percentages of patients prescribed medications, overall, by age group, and by comorbidity based on hospitalization status for COVID-19 patients. Use percentage by month of COVID-19 diagnosis was measured. Cumulative count of potential therapeutic options was measured over time. Results: Dataset included 22 896 unique patients with COVID-19 (mean [SD] age, 42.4 [20.4] years; 12 154 [53%] women). Most frequently used medications in patients overall were acetaminophen (21.2%), albuterol (14.9%), ondansetron (13.9%), and enoxaparin (10.8%). Dexamethasone use increased from fewer than 50 total hospitalized patients through April who had received the medication, to more than 500 patients by mid-August. Cumulative count of enoxaparin users was the largest throughout the study period. Conclusion and Relevance: In this retrospective cohort study, across age and comorbidity groups, predominant utilization was for supportive care therapy. Dexamethasone and remdesivir experienced large increases in use. Conversely, hydroxychloroquine and azithromycin use markedly dropped. Medication utilization rapidly shifted toward more evidence-concordant treatment of patients with COVID-19 as rigorous study findings emerged.

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  1. Version published to 10.1177/87551225211068675
  2. ScreenIT

    SciScore for 10.1101/2021.07.15.21259539: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: 10–12 UC CORDS was operationalized by UC Health as ‘non-human subjects research’ and analyses are considered institutional review board exempt.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Medications used for each patient were determined from the EHR by measurement of all medication active ingredients utilized within 30 days of COVID-19 positive test based on the RxNorm standardized nomenclature for clinical drugs from the National Library of Medicine.17 Given the assumption, in context of COVID-19, of a similar therapeutic class effect of angiotensin converting enzyme-2 inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) usage of these medications was collapsed to the overall category of ‘ACEIs/ARBs’.
    RxNorm
    suggested: (RxNorm, RRID:SCR_006645)
    Data were extracted with module pyodbc, version 4.0.30 in Python, version 3.8.3 (Python Software Foundation).
    Python
    suggested: (IPython, RRID:SCR_001658)
    All analyses performed in R, version 3.6.3 (R Project for Statistical Computing).
    R Project for Statistical
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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:
    Limitations: Outpatient medications for patients in CORDS may require at least a month for complete capture. Use rates are conservative estimates for the non-hospitalized patients since medications for COVID-19 positive patients prescribed medications outside of UC Health are not present in CORDS. While the study demographics were consistent with California overall, given, that this state has a large minority population this may influence generalizability to the US. Consequently, the percentage of COVID-19 positive cases that were Non-Hispanic White in CORDS (28%) was lower than that observed in US national estimates (56%). Hispanics were 37% of the positive cases in our dataset and 21% in the US. A smaller percentage of COVID-19 positive patients were black (6%) than observed in national estimates (12.2%). Asians were 7% of the COVID-19 positive patients in CORDS compared to 4% in US estimates.25

    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

    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.

  3. Version published to 10.1101/2021.07.15.21259539v1 on medRxiv