COVID-19 testing capabilities at urgent care centers in states with greatest disease burden

  1. Walter Hsiang
  2. Howard Forman
  3. Siddharth Jain
  4. Akshay Khunte
  5. Grace Jin
  6. Laurie Yousman
  7. Michael Najem
  8. Alison Mosier-Mills
  9. Daniel Wiznia

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Abstract

While rapid and accessible diagnosis is paramount to monitoring and reducing the spread of disease, COVID-19 testing capabilities across the U.S. remain constrained. For many individuals, urgent care centers (UCCs) may offer the most accessible avenue to be tested. Through a phone survey, we describe the COVID-19 testing capabilities at UCCs and provide a snapshot highlighting the limited COVID-19 testing capabilities at UCCs in states with the greatest disease burden.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.22.20040923: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomization2 25 UCCs, defined as walk-in clinics in ambulatory medical facilities, were randomly selected and called from each state using the Urgent Care Association “Find an Urgent Care” directory.
    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: We detected the following sentences addressing limitations in the study:
    This report has limitations. The small number of UCCs contacted per state may not accurately represent the state’s urgent care climate. Additionally, the rapidly changing nature of the COVID-19 pandemic may affect these findings. However, this study serves as an important snapshot that highlights the limited COVID-19 testing capabilities at UCCs in the most heavily burdened states.

    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.

  2. Version published to 10.12688/f1000research.23203.1
  3. Version published to 10.1101/2020.03.22.20040923v1 on medRxiv