Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis

  1. Bilal Akhter Mateen
  2. Harrison Wilde
  3. John M Dennis
  4. Andrew Duncan
  5. Nick Thomas
  6. Andrew McGovern
  7. Spiros Denaxas
  8. Matt Keeling
  9. Sebastian Vollmer

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Abstract

In this study, we describe the pattern of bed occupancy across England during the peak of the first wave of the COVID-19 pandemic.

Design

Descriptive survey.

Setting

All non-specialist secondary care providers in England from 27 March27to 5 June 2020.

Participants

Acute (non-specialist) trusts with a type 1 (ie, 24 hours/day, consultant-led) accident and emergency department (n=125), Nightingale (field) hospitals (n=7) and independent sector secondary care providers (n=195).

Main outcome measures

Two thresholds for ‘safe occupancy’ were used: 85% as per the Royal College of Emergency Medicine and 92% as per NHS Improvement.

Results

At peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough there were 8.7% (8508) fewer general and acute beds across England, but occupancy never exceeded 72%. The closest to full occupancy of general and acute bed (surge) capacity that any trust in England reached was 99.8% . For beds compatible with mechanical ventilation there were 326 trust-days (3.7%) spent above 85% of surge capacity and 154 trust-days (1.8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust=1, range: 1–17). However, only three sustainability and transformation partnerships (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds.

Conclusions

Throughout the first wave of the pandemic, an adequate supply of all bed types existed at a national level. However, due to an unequal distribution of bed utilisation, many trusts spent a significant period operating above ‘safe-occupancy’ thresholds despite substantial capacity in geographically co-located trusts, a key operational issue to address in preparing for future waves.

Article activity feed

  1. Version published to 10.1136/bmjopen-2020-042945
  2. Version published to 10.1101/2020.06.24.20139048v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.06.24.20139048: (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

    Software and Algorithms
    SentencesResources
    Analysis were carried out in R,25 ggplot2 package.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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 Limitations: There are several strengths to this study. For example, the use of an administrative (i.e. ‘SitRep’) data that is a statutory collection by NHS England, via a well-established reporting mechanism that has been exploited for research,31 confers robustness to the data. One example of how this robustness manifested is, unlike other attempts to collect data at a national level to inform the COVID-19 response plan in the UK,32 the degree of missingness in the data utilized in this study was minimal (see supplementary material). Moreover, in light of the unique access to the raw ‘SitRep’ data, we have been able to present our results not only at the trust-level, to which previous endeavors have been limited,33 but rather have been able to present information at a much more granular layer (i.e. hospital/site-level) thus providing a much richer understanding of resource utilization that is less prone to the diluent effects of higher level geographies. Finally, a further strength of this study is the relative simplicity of the analysis; there are no complex statistical methods utilized as the descriptive summaries presented are sufficient to describe the experiences of nationalized (single-payer) health system in a high-income economy during the first wave of the COVID-19 pandemic. Notably though, there are also several limitations to the dataset and our analysis. Firstly, the changes introduced in ‘SitRep’ data collection half-way through the reporting peri...

    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

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  4. Version published to 10.1101/2020.06.24.20139048v1 on medRxiv