Development and presentation of an objective risk stratification tool for healthcare workers when dealing with the COVID-19 pandemic in the UK: risk modelling based on hospitalisation and mortality statistics compared with epidemiological data

  1. W David Strain
  2. Janusz Jankowski
  3. Angharad P Davies
  4. Peter English
  5. Ellis Friedman
  6. Helena McKeown
  7. Su Sethi
  8. Mala Rao

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Abstract

Healthcare workers have greater exposure to SARS-CoV-2 and an estimated 2.5-fold increased risk of contracting COVID-19 than the general population. We wished to explore the predictive role of basic demographics to establish a simple tool that could help risk stratify healthcare workers.

Setting

We undertook a review of the published literature (including multiple search strategies in MEDLINE with PubMed interface) and critically assessed early reports on preprint servers. We explored the relative risk of mortality from readily available demographics to identify the population at the highest risk.

Results

The published studies specifically assessing the risk of healthcare workers had limited demographics available; therefore, we explored the general population in the literature. Clinician demographics : Mortality increased with increasing age from 50 years onwards. Male sex at birth, and people of black and minority ethnicity groups had higher susceptibility to both hospitalisation and mortality. Comorbid disease . Vascular disease, renal disease, diabetes and chronic pulmonary disease further increased risk. Risk stratification tool : A risk stratification tool was compiled using a white female aged <50 years with no comorbidities as a reference. A point allocated to risk factors was associated with an approximate doubling in risk. This tool provides numerical support for healthcare workers when determining which team members should be allocated to patient facing clinical duties compared with remote supportive roles.

Conclusions

We generated a tool that provides a framework for objective risk stratification of doctors and healthcare professionals during the COVID-19 pandemic, without requiring disclosure of information that an individual may not wish to share with their direct line manager during the risk assessment process. This tool has been made freely available through the British Medical Association website and is widely used in the National Health Service and other external organisations.

Article activity feed

  1. Version published to 10.1136/bmjopen-2020-042225
  2. Version published to 10.1101/2020.05.05.20091967v4 on medRxiv
  3. Version published to 10.1101/2020.05.05.20091967v3 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.05.05.20091967: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationNo published or completed prospective cohort studies or randomized controlled trials were present in this literature search.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableRisk was normalised to a female aged 40-49, and an integer to approximate the impact of demographics, such as age13, ethnicity14 and important co-morbidities15 assigned.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We reviewed the published literature (including multiple search strategies in MEDLINE with PubMed interface), EMBASE and critically assessed early reports on medRxiv, a pre-print server (https://www.medrxiv.org/) (date of last search: December 21, 2020).
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    EMBASE
    suggested: (EMBASE, RRID:SCR_001650)
    Eligibility criteria: Studies were included according to the following criteria Information sources and search strategy: We searched the following electronic databases: MEDLINE, EMBASE, and the preprint server MedRxiv from inception to 22nd December 2020.
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    All reports were assessed for risk of bias (ROB) using the Cochrane ROB 2.0 tool 11, however this assessment was used to inform the weighting given to the information contained therein when being reviewed by the experts in order to form a consensus risk assessment tool.
    Cochrane ROB
    suggested: (Robot Reviewer, RRID:SCR_018961)

    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:
    Study limitations: Selection bias in testing, care and reporting can lead to differences in prevalence estimates of pre-existing risk factors and presentation across the reports from various countries. The majority of the existing analyses are based on retrospective and often single-centre series. No published or completed prospective cohort studies or randomised controlled trials were present in this literature search. A limitation is that we only searched Pubmed, EMBASE and preprint servers. There is an urgent need for high quality research, using individual level data for healthcare workers that will allow full mediation analyses in order to determine whether (for example) it is the age, the diabetes, or the cardiovascular disease that actually carries the greatest prognostic risk, given that these conditions commonly co-exist, and explore the disparity in BAME individuals between the general population and the healthcare deaths. There are currently only limited observational data for COVID-19 related deaths in health care workers or doctors, again without full access to all potentially pertinent information.. Importantly, this tool was derived from UK data, and therefore may not be relevant in other countries, however the methods employed here can be replicated in other healthcare settings. Patient and public involvement: The primary target of this research was healthcare professionals, occupational health teams and medical managers. There was significant engagement with ...

    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.

  5. Version published to 10.1101/2020.05.05.20091967v2 on medRxiv
  6. Version published to 10.1101/2020.05.05.20091967v1 on medRxiv