Switching from algorithm-based to universal admission screening for COVID-19 in hospital settings

  1. Tjibbe Donker
  2. Hajo Grundmann
  3. Fabian Bürkin
  4. Hartmut Hengel
  5. Hartmut Bürkle
  6. Thorsten Hammer
  7. Frederik Wenz
  8. Winfried Kern

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Abstract

Detection of COVID-19 positive cases on admission to hospitals is crucial to protect patients and staff at the same time. While universal admission screening can prevent more undetected introductions than the algorithm-based screening, which preselects patient based on their symptoms and exposure, it is a more costly strategy as it involves testing a large number of patients.

We construct a simple tool to help determine when the benefit of additionally found cases outweighs the cost of the additionally tested patients, based on the numbers of patients to be screened in an acceptable time span to find an additional case when screening all admitted patients.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.07.20170001: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    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.

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  2. Version published to 10.1101/2020.08.07.20170001v1 on medRxiv