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King Z, Farrington J, Utley M, Kung E, Elkhodair S, Harris S, Sekula R, Gillham J, Li K, Crowe S. Machine learning for real-time aggregated prediction of hospital admission for emergency patients. NPJ Digit Med 2022; 5:104. [PMID: 35882903 PMCID: PMC9321296 DOI: 10.1038/s41746-022-00649-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/04/2022] [Indexed: 12/23/2022] Open
Abstract
Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabilistic forecasts of emergency admissions. A set of XGBoost classifiers applied to 109,465 ED visits yielded AUROCs from 0.82 to 0.90 depending on elapsed visit-time at the point of prediction. Patient-level probabilities of admission were aggregated to forecast the number of admissions among current ED patients and, incorporating patients yet to arrive, total emergency admissions within specified time-windows. The pipeline gave a mean absolute error (MAE) of 4.0 admissions (mean percentage error of 17%) versus 6.5 (32%) for a benchmark metric. Models developed with 104,504 later visits during the Covid-19 pandemic gave AUROCs of 0.68–0.90 and MAE of 4.2 (30%) versus a 4.9 (33%) benchmark. We discuss how we surmounted challenges of designing and implementing models for real-time use, including temporal framing, data preparation, and changing operational conditions.
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Affiliation(s)
- Zella King
- Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK. .,Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.
| | - Joseph Farrington
- Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK
| | - Martin Utley
- Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK
| | - Enoch Kung
- Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK
| | - Samer Elkhodair
- University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK
| | - Steve Harris
- University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK
| | - Richard Sekula
- University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK
| | - Jonathan Gillham
- University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK
| | - Kezhi Li
- Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK
| | - Sonya Crowe
- Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK
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