Abstract
Inadequate patient flow from hospitals into community care is often blamed for bed blockages in the acute setting. This is bad for patient experience and outcomes and has an upstream knock-on effect for Accident and Emergency performance and, in turn, ambulance offload delays and response times. Despite the large numbers of acute bed-days lost to delayed discharges and the ambition to expand home-based community care, there has been a deficit of modelling studies investigating the dynamics of this pathway and providing the relevant insights to service planners. Working closely with healthcare managers, this paper reports on the development and deployment of versatile simulation tools for modelling both the home-based and bedded community step-down pathways, known as 'Discharge to Assess' or D2A in England's NHS. Developed in open source 'R', these tools offer scalable solutions for exploring different scenarios relating to demand, capacity and patient length of stay.
| Original language | English |
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| Title of host publication | 11th Simulation Workshop, SW 2023 |
| Editors | Christine Currie, Luke Rhodes-Leader |
| Publisher | The OR Society |
| Pages | 107-116 |
| Number of pages | 10 |
| ISBN (Electronic) | 9781713870951 |
| DOIs | |
| Publication status | Published - 27 Mar 2023 |
| Event | 11th Operational Research Society Simulation Workshop, SW 2023 - Southampton, UK United Kingdom Duration: 27 Mar 2023 → 29 Mar 2023 |
Publication series
| Name | 11th Simulation Workshop, SW 2023 |
|---|
Conference
| Conference | 11th Operational Research Society Simulation Workshop, SW 2023 |
|---|---|
| Country/Territory | UK United Kingdom |
| City | Southampton |
| Period | 27/03/23 → 29/03/23 |
Bibliographical note
Funding Information:This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, National Institute for Health Research, Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (South Western Ireland), British Heart Foundation and Wellcome (award number CFC0129). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Alison Harper and Martin Pitt are funded by the National Institute for Health Research Applied Research Collaboration South West Peninsula. The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.
Publisher Copyright:
© SW 2023.All rights reserved
Funding
This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, National Institute for Health Research, Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (South Western Ireland), British Heart Foundation and Wellcome (award number CFC0129). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Alison Harper and Martin Pitt are funded by the National Institute for Health Research Applied Research Collaboration South West Peninsula. The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.
Keywords
- Community services
- Discharge planning
- Healthcare management
- Resource allocation
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Modelling and Simulation