Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an observational study of 4.3 million adults over the age of 65

  1. Anna Schultze
  2. Emily Nightingale
  3. David Evans
  4. William Hulme
  5. Alicia Rosello
  6. Chris Bates
  7. Jonathan Cockburn
  8. Brian MacKenna
  9. Helen J Curtis
  10. Caroline E Morton
  11. Richard Croker
  12. Seb Bacon
  13. Helen I McDonald
  14. Christopher T Rentsch
  15. Krishnan Bhaskaran
  16. Rohini Mathur
  17. Laurie A Tomlinson
  18. Elizabeth J Williamson
  19. Harriet Forbes
  20. John Tazare
  21. Daniel Grint
  22. Alex J Walker
  23. Peter Inglesby
  24. Nicholas J DeVito
  25. Amir Mehrkar
  26. George Hickman
  27. Simon Davy
  28. Tom Ward
  29. Louis Fisher
  30. Amelia CA Green
  31. Kevin Wing
  32. Angel YS Wong
  33. Robert McManus
  34. John Parry
  35. Frank Hester
  36. Sam Harper
  37. Stephen JW Evans
  38. Ian J Douglas
  39. Liam Smeeth
  40. Rosalind M Eggo
  41. Ben Goldacre
  42. David A Leon

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Abstract

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  1. Version published to 10.1016/j.lanepe.2021.100295
  2. ScreenIT

    SciScore for 10.1101/2021.07.07.21253295: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableTo account for differences in the age of care home and private home residents, mortality risks for men and women were directly standardised to the European Standard (2013) population using five-year age-bands (9).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data management was performed using OpenSAFELY tools in Python 3.8 and analyses carried out using R version 3.6.2.
    Python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and Limitations: Our study has several strengths. Most notably, we had access to clearly defined and time-updated population at risk (denominators) as well as deaths (numerators) by place of residence through the address linkage to CQC care home addresses in OpenSAFELY-TPP. This has allowed us to contrast the absolute mortality risks of care home residents to those in private homes, and therefore builds on updates provided by the ONS on place of death, which only provides numerator data. The most significant limitation concerns the identification of care home residents in UK EHR data (6). Here, we used an address linkage with CQC data. Although this likely has a high positive predictive value (7), the prevalence of care home residency is approximately a third lower than indicated based on estimates from the 2011 census (15). Location of death should not have impacted on these analyses, as the ONS data captures deaths occurring both in hospital and within the community. However, we cannot rule out that some of the differences we observe in the mortality risks between care home and private home residents might be due to data quality issues, for example if there has been poorer ascertainment of whether someone lives in a care home during the second wave due to more dynamic movements of people. It should also be noted that our findings may not be generalisable to the English total care home population, as TPP only covers a proportion of English residents. Interpretation...

    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 10.1101/2021.07.07.21253295v1 on medRxiv