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 to epidemiological data

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

Objectives

Healthcare workers have a greater exposure to individuals with confirmed SARS-novel coronavirus 2, and an estimated 5-fold higher probability of contracting coronavirus disease (COVID)-19, than the general population. Many organisations have called for risk assessments to be put in place to minimise this risk. We wished to explore the predictive role of basic demographics in order 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 medRxiv, a pre-print server (<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://www.medrxiv.org">https://www.medrxiv.org</ext-link>: date of last search: December 21, 2020). We explored the relative risk of mortality from readily available demographics in order to identify the population at highest risk.

Results

The only 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, people of black and minority ethnicity groups had higher susceptibility to both hospitalisation and mortality. Co-morbid Disease. Vascular disease, renal disease, diabetes and chronic pulmonary disease further increased risk.

Risk stratification tool

A risk stratification tool was compiled using a Caucasian female <50years with no comorbidities as a reference. A point allocated to risk factors 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 to remote supportive roles.

Conclusions

We have generated a tool which can provide a framework for objective risk stratification of doctors and health care 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.

Strengths and limitations of this study

  • There is an increased risk of mortality in the clinical workforce due to the effects of COVID-19.

  • This manuscript outlines a simple risk stratification tool that helps to quantify an individual’s biological risk

  • This will assist team leaders when allocating roles within clinical departments.

  • This tool does not incorporate other external factors, such as high-risk household members or those at higher risk of mental health issues, that may require additional consideration when allocating clinical duties in an appropriate clinical domain.

  • This population-based analysis did not explain for the very high risk observed in BAME healthcare workers suggesting there are other issues at play that require addressing.

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