DS4SmartDischarge: Data Science Informing Complex Discharge Winter Policy
Project led by Professor Michael Boniface, University of Southampton , coordinated and supported by Health Data Research UK with funding from the National Institute for Health and Care Research (NIHR).
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In 2018/2019, UK patient discharges from hospital were delayed by over 1.5 million days. Almost 75% of delays were due to arrangements for community care not being in place. It is currently estimated that around 20% of hospital beds are being occupied by people well enough to be discharged, creating extra pressure on the NHS.
Unnecessarily prolonged stays in hospital are also bad for patients. The risk of delay to discharge is higher for patients with pre-existing complex care, who then develop further care needs from their longer hospital stays. These include an increased risk of physical and mental deterioration from the sedentary nature of hospital stays, and hospital acquired infections.
To help the NHS understand what sorts of patients are being delayed and what their care needs are, the researchers will use computer algorithms to help understand what causes patients to be delayed or not. The analysis will be done using statistics and machine learning with historical hospital data (health status, procedures, treatments, and care needs assessment) to identify patient groups with different discharge outcomes.