The impact of occupational risk from COVID on GP supply in England: A cross-sectional study

  1. Miqdad Asaria
  2. Rebecca Fisher

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Abstract

Objectives

To identify the risk of general practitioner mortality from COVID and the impact of measures to mitigate this risk on the level and socioeconomic distribution of primary care provision in the English NHS

Design

Cross sectional study

Setting

All GP practices providing primary care under the NHS in England

Participants

45,858 GPs and 6,771 GP practices in the English NHS

Main outcome measures

Numbers of high-risk GPs, high-risk single-handed GP practices, patients associated with these high-risk single-handed practices and the regional and socioeconomic distribution of each. Mortality rates from COVID by age, sex and ethnicity were used to attribute risk to GPs and the Index of Multiple Deprivation was used to determine socioeconomic distributions of the outcomes.

Results

Of 45,858 GPs in our sample 3,632 (7.9%) were classified as high risk or very high risk. Of 6,771 GP practices in our sample 639 (9.4%) were identified as single-handed practices and of these 209 (32.7%) were run by a GP at high or very high risk. These 209 single-handed practices care for 710,043 patients. GPs at the highest levels of risk from COVID, and single-handed practices run by high-risk GPs were concentrated in the most deprived neighbourhoods in the country. London had the highest proportion of both GPs and single-handed GP practices at very high risk of COVID mortality with 1,160 patients per 100,000 population registered to these practices.

Conclusions

A significant proportion of GPs working in England, particularly those serving patients in the most deprived neighbourhoods, are at high risk of dying from COVID. Many of these GPs run single-handed practices. These GPs are particularly concentrated in London. There is an opportunity to provide additional support to mitigate COVID risk for GPs, GP practices and their patients. Failure to do so will likely exacerbate existing health inequalities.

What is already known

  • Known risk factors for morbidity and mortality from COVID-19 include age, sex, ethnicity and certain underlying health conditions.

  • NHS England have suggested that NHS staff who may be at higher risk from COVID are risk assessed and have their activities adjusted accordingly, including ceasing face to face patient contact.

What this study adds

  • This study applies risk scoring to calculate the number of GPs practicing in England who are likely to be at high or very high risk of death from COVID. We examine the potential effect of removing GPs at high or very high risk from COVID from face to face patient contacts, estimating the number of GPs and patients likely to be affected, and relating this to deprivation and geography.

  • We estimate that of 45,858 GPs in our sample, 2,253 (4.9%) were classified as high risk, and 1,379 (3%) as very high risk from COVID. These are likely to be conservative estimates.

  • GPs at high risk of COVID are more likely to work in areas of high socioeconomic deprivation.

  • Almost one in three single-handed GP practices (32.7%, or 209 out of 639) is run by a GP we estimate to be at high or very high risk from COVID. If these GPs did not see patients face to face, 710,043 patients would be left without face to face GP appointments. Single-handed GP practices in areas of high socioeconomic deprivation are more likely to be run by GPs at higher risk of COVID.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.04.20122119: (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 variableRisk scores were calculated by dividing all mortality rates by those for women aged 55–60 (the lowest risk group for whom COVID mortality risk is non-negligible).

    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: We detected the following sentences addressing limitations in the study:
    Strengths and weaknesses: Our study is the first that we are aware of that explores the potential impact of COVID across the GP workforce in the NHS. We use a comprehensive national dataset to quantify the degree of fragility of primary care in the face of the COVID pandemic and highlight the particularly vulnerable position of single-handed GP practices in the delivery of primary care in these times. We also explore the implications of these risks on the regional and socioeconomic distributions of primary care provision and find that risks are patterned by both geography and deprivation. If left un-mitigated, existing health inequalities amongst the patient population are likely to be exacerbated along these dimensions. Our study builds on emerging frameworks that identify COVID risk amongst healthcare staff in the NHS.(5,14) These frameworks were written to identify risk at the individual level, requiring detailed information about underlying health conditions and biomarkers of those being assessed. Our attempt to operationalise these frameworks at a health system level is challenging and has a number of limitations. First, detailed data on underlying health conditions, pregnancy, and biomarkers such as BMI and Vitamin D levels that are found in these frameworks are not recorded in the comprehensive national data sets that cover the NHS workforce underpinning our analysis. We were therefore unable to use these factors in our implementations of the COVID risk scores. Conside...

    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 10.1101/2020.06.04.20122119v1 on medRxiv