A patient satisfaction survey and educational package to improve the care of people hospitalised with COVID-19: an observational study, Liverpool, UK

  1. Muhammad Shamsher Ahmed
  2. Scott Rory Hicks
  3. Rebecca Watson
  4. Rajia Akter Ahmed
  5. Lewis Jones
  6. Marcella Vaselli
  7. Meng-San Wu
  8. Fatima Hayat
  9. Libuse Ratcliffe
  10. Mark McKenna
  11. Paul Hine
  12. Sylviane Defres
  13. Tom Wingfield

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Abstract

The experiences of people hospitalised with COVID-19 are under-researched. We designed a COVID-19 patient satisfaction survey and collected responses (n=94) during Liverpool’s first wave (April-June 2020). Although care was generally rated highly, including among people of BAME background, sleep-quality and communication about medications and discharge-planning were identified as areas for improvement. In response, we implemented an education and training package for healthcare professionals working on COVID-19 wards. During Liverpool’s second/third COVID-19 wave, survey responses (n=101) suggested improvement in patient satisfaction across all care domains except discharge-planning and sleep-quality. These UK-first findings are informing local strategies to improve COVID-19 care.

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  1. ScreenIT

    SciScore for 10.1101/2021.03.23.21253630: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    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.

  2. Version published to 10.1101/2021.03.23.21253630 on medRxiv