This project aims to alleviate the shortage of acute beds, resulting from delays in discharge to social care. The team will develop research methods to improve the flow between acute, community, and social care and ultimately improve patient experience and health outcomes.
Lack of availability of social care services is a recognised contributor to the pressures faced by hospitals. Across England (2019) approximately 500,000 acute bed days were lost due to delays in discharge, directly attributable to non-availability of social care. Additionally, bottlenecks in the capacity of social care propagate delays upstream leading to emergency department overcrowding and ambulances being unable to unload patients.
This project aims to alleviate these pressures through capacity reallocation strategies across the pathway from readiness for discharge from acute care to intermediate ‘step down’ community services and social care provision. It aims to represent the flow of patients from acute discharge readiness through to longer-term domiciliary home visits and care home placements, to allow the optimal balance of capacity along this clinical pathway to be identified. This modelling will provide insight into how responsive total spend is to social care capacity, and so will test the assumption that the cost of increasing social care capacity will more than offset the reduced need of hospital resources.
The Impact and Outcomes
Central to this project is the principle that the NHS can better meet patient needs if efficiency gains can be found and delivered. Keeping patients in a bedded setting longer than they need to be leads to both physical and mental deterioration, such as the development of pressure sores and healthcare acquired infections. Improving capacity distribution through the system will support an earlier discharge from hospital and reduce the likelihood of patients having to go on to a residential placement.
Better Care Loop
Dr Richard Wood, Head of Modelling and Analytics, BNSSG CCG and Visiting Research Fellow, University of Bath School of Management
COVID-19 mortality risk for inflammatory arthritis patients: a cohort study using SAIL Databank
24 November 2022
A study of inflammatory arthritis (IA) patients found that shielding reduced the incidence of COVID-19. IA was not associated with an increased risk of dying within 28 days, but being vulnerable...
Can we accurately forecast non-elective bed occupancy and admissions in the NHS? A time-series MSARIMA analysis of longitudinal data from an NHS Trust
1 July 2022
Hospitals need to be able to predict their capacity for admitting patients when planning elective surgeries. Researchers funded by HDR UK developed a new model for making forecasts that were more...
A population-based cohort study of obesity, ethnicity and COVID-19 mortality in 12.6 million adults in England
21 June 2022
Obesity dramatically increases the risk of death from COVID-19 but, the extent of this risk across different body weights and ethnic groups was not clear. Researchers using health and Census...