Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy
Study objectives This study evaluates the feasibility and accuracy of a pragmatic approach to predicting hospital bed occupancy for COVID-19-positive patients, using only simple methods accessible to typical health system teams.Methods We used an observational forecasting design for the study period...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2025-02-01
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| Series: | BMJ Health & Care Informatics |
| Online Access: | https://informatics.bmj.com/content/32/1/e101055.full |
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| _version_ | 1832087422170562560 |
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| author | Azeem Majeed Thomas Woodcock Paul Aylin Julian Redhead Derryn Lovett Jacques Naude |
| author_facet | Azeem Majeed Thomas Woodcock Paul Aylin Julian Redhead Derryn Lovett Jacques Naude |
| author_sort | Azeem Majeed |
| collection | DOAJ |
| description | Study objectives This study evaluates the feasibility and accuracy of a pragmatic approach to predicting hospital bed occupancy for COVID-19-positive patients, using only simple methods accessible to typical health system teams.Methods We used an observational forecasting design for the study period 1st June 2021 to –21st January 2022. Evaluation data covered individuals registered with a general practitioner in North West London, through the Whole Systems Integrated Care deidentified dataset. We extracted data on COVID-19-positive tests, vaccination records and admissions to hospitals with confirmed COVID-19 within the study period. We used linear regression models to predict bed occupancy, using lagged, smoothed numbers of COVID-19 cases among unvaccinated individuals in the community as the predictor. We used mean absolute percentage error (MAPE) to assess model accuracy.Results Model accuracy varied throughout the study period, with a MAPE of 10.8% from 12 July 2021 to 18 October 2021, rising to 20.0% over the subsequent period to 15 December 2021. After that, model accuracy deteriorated considerably, with MAPE 110.4% from December 2021 to 21 January 2022. Model outputs were used by senior healthcare system leaders to aid the planning, organisation and provision of healthcare services to meet demand for hospital beds.Conclusions The model produced useful predictions of COVID-19-positive bed occupancy prior to the emergence of the Omicron variant, but accuracy deteriorated after this. In practice, the model offers a pragmatic approach to predicting bed occupancy within a pandemic wave. However, this approach requires continual monitoring of errors to ensure that the periods of poor performance are identified quickly. |
| format | Article |
| id | doaj-art-c9798816cb0c4fffa75fec9f3a02249c |
| institution | Kabale University |
| issn | 2632-1009 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Health & Care Informatics |
| spelling | doaj-art-c9798816cb0c4fffa75fec9f3a02249c2025-02-06T05:30:10ZengBMJ Publishing GroupBMJ Health & Care Informatics2632-10092025-02-0132110.1136/bmjhci-2024-101055Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancyAzeem Majeed0Thomas Woodcock1Paul Aylin2Julian Redhead3Derryn Lovett4Jacques Naude52 Department of Primary Care and Public Health, Imperial College London, London, UK1 NIHR CLAHRC NWL, Chelsea and Westminster Hosptial, Imperial College London, London, United KingdomDepartment of Primary Care and Public Health, Imperial College London, London, UKnational clinical director for urgent and emergency care1 Department of Primary Care and Public Health, Imperial College London, London, UK3 London North West Healthcare NHS Trust, London, UKStudy objectives This study evaluates the feasibility and accuracy of a pragmatic approach to predicting hospital bed occupancy for COVID-19-positive patients, using only simple methods accessible to typical health system teams.Methods We used an observational forecasting design for the study period 1st June 2021 to –21st January 2022. Evaluation data covered individuals registered with a general practitioner in North West London, through the Whole Systems Integrated Care deidentified dataset. We extracted data on COVID-19-positive tests, vaccination records and admissions to hospitals with confirmed COVID-19 within the study period. We used linear regression models to predict bed occupancy, using lagged, smoothed numbers of COVID-19 cases among unvaccinated individuals in the community as the predictor. We used mean absolute percentage error (MAPE) to assess model accuracy.Results Model accuracy varied throughout the study period, with a MAPE of 10.8% from 12 July 2021 to 18 October 2021, rising to 20.0% over the subsequent period to 15 December 2021. After that, model accuracy deteriorated considerably, with MAPE 110.4% from December 2021 to 21 January 2022. Model outputs were used by senior healthcare system leaders to aid the planning, organisation and provision of healthcare services to meet demand for hospital beds.Conclusions The model produced useful predictions of COVID-19-positive bed occupancy prior to the emergence of the Omicron variant, but accuracy deteriorated after this. In practice, the model offers a pragmatic approach to predicting bed occupancy within a pandemic wave. However, this approach requires continual monitoring of errors to ensure that the periods of poor performance are identified quickly.https://informatics.bmj.com/content/32/1/e101055.full |
| spellingShingle | Azeem Majeed Thomas Woodcock Paul Aylin Julian Redhead Derryn Lovett Jacques Naude Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy BMJ Health & Care Informatics |
| title | Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy |
| title_full | Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy |
| title_fullStr | Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy |
| title_full_unstemmed | Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy |
| title_short | Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy |
| title_sort | evaluation of a pragmatic approach to predicting covid 19 positive hospital bed occupancy |
| url | https://informatics.bmj.com/content/32/1/e101055.full |
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