dc.contributor.author | Önen-Dumlu, Z | |
dc.contributor.author | Forte, P | |
dc.contributor.author | Harper, A | |
dc.contributor.author | Pitt, M | |
dc.contributor.author | Vasilakis, C | |
dc.contributor.author | Wood, R | |
dc.date.accessioned | 2023-04-28T12:28:04Z | |
dc.date.issued | 2023-03-27 | |
dc.date.updated | 2023-04-28T09:52:40Z | |
dc.description.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. | en_GB |
dc.description.sponsorship | Health Data Research UK | en_GB |
dc.format.extent | 107-116 | |
dc.identifier.citation | Proceedings of the Operational Research Society Simulation Workshop 2023 (SW23), 27 - 29 March 2023 National Oceanography Centre, Southampton, edited by Christine Currie and Luke Rhodes-Leader, pp. 107-116 | en_GB |
dc.identifier.doi | https://doi.org/10.36819/sw23.013 | |
dc.identifier.grantnumber | CFC0129 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/133048 | |
dc.identifier | ORCID: 0000-0001-5274-5037 (Harper, Alison) | |
dc.language.iso | en | en_GB |
dc.publisher | Operational Research Society | en_GB |
dc.relation.url | https://www.theorsociety.com/events/simulation-workshop/ | en_GB |
dc.relation.url | https://doi.org/10.36819/SW23 | |
dc.rights | © 2023 Operational Research Society | en_GB |
dc.subject | Healthcare management | en_GB |
dc.subject | Resource allocation | en_GB |
dc.subject | Community services | en_GB |
dc.subject | Discharge planning | en_GB |
dc.title | Improving Hospital Discharge Flow Through Scalable Use of Discrete Time Simulation and Scenario Analysis | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2023-04-28T12:28:04Z | |
dc.description | This is the author accepted manuscript. The final version is available from the Operational Research Society via the DOI in this record | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2023-03-27 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2023-04-28T12:26:13Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2023-07-28T15:19:55Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2023-03-27 | |
pubs.name-of-conference | Proceedings of SW21 The OR Society Simulation Workshop | |