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Impact of accurate initial discharge planning and inpatient transfers of care on discharge delays: a retrospective cohort study

Impact of accurate initial discharge planning and inpatient transfers of care on discharge delays: a retrospective cohort study
Impact of accurate initial discharge planning and inpatient transfers of care on discharge delays: a retrospective cohort study
Objective: to investigate the association between initial discharge planning and transfers of inpatient care with discharge delay. To identify operational changes which could expedite discharge within the Discharge to Assess (D2A) model.

Design: retrospective cohort study.

Setting: University Hospital Southampton National Health Service Foundation Trust (UHS).

Participants: all adults (≥18 years) who registered a hospital inpatient stay in UHS between 1 January 2021 and 31 December 2022 (n=258 051). After excluding inpatient stays without complete discharge planning data or key demographic/clinical information, 65 491 inpatient stays were included in the final analysis. Data included demographics, comorbidities, ward movements, care team handovers and discharge planning records.

Primary and secondary outcome measures: the primary outcome was discharge delay, defined as the number of days between the final estimated discharge date and the actual discharge date. For the purposes of OR analysis, discharge delay was modelled as a binary outcome: any delay (>0 days) versus no delay. Logistic regression models were used to examine associations between initial discharge planning accuracy, the number of ward moves and the number of in-specialty handovers and the likelihood of discharge delay, adjusting for demographic and patient complexity factors.

Results: out of 65 491 inpatient stays, 10 619 had an initial planned discharge pathway that was different from the final discharge pathway. 7790 of these inpatient stays (75.1%) recorded a discharge delay. In contrast, among the 54 872 inpatient stays where the initial and final pathway matched, 10 216 (18.6%) recorded a delay. Using logistic regression modelling a binary outcome (any discharge delay vs no delay), an inaccurate initial pathway was associated with significantly increased odds of delay (adjusted OR (aOR) 2.72, 95% CI 2.55 to 2.91). Each additional ward move (aOR 1.25, 95% CI 1.23 to 1.28) and each in-specialty handover (aOR 1.17, 95% CI 1.14 to 1.20) were also associated with higher odds of discharge delay.

Conclusions: this study finds a strong association between inaccurate initial discharge plans and inpatient transfers of care with discharge delay, after controlling for patient complexity and acuity. This highlights the need to consider how initial plans and inpatient transfers affect discharge planning. Given the lead times for organising onward care, operational inefficiencies are most impactful for patients eventually discharged on pathways with higher planning complexity.
Decision Making, Electronic Health Records, Hospitals, Organisation of health services, Risk management
2044-6055
Burns, Dan
40b9dc88-a54a-4365-b747-4456d9203146
Duckworth, Chris
992c216c-8f66-48a8-8de6-2f04b4f736e6
Lamas Fernandez, Carlos
e96b5deb-74d5-4c9b-a0ce-448c99526b09
Leyland, Rachael
d972dc0b-1c49-4283-bf48-b4e30e8d6e48
Wright, Mark
96332a4d-46f9-499a-8b28-9f36a22b6e9f
Stammers, Matt
85e202da-1879-4f96-8e24-5059a1fa3f1e
George, Michael
5bd91b32-01fd-4cf1-bc24-f3c4102865c3
Boniface, Michael
f30bfd7d-20ed-451b-b405-34e3e22fdfba
Burns, Dan
40b9dc88-a54a-4365-b747-4456d9203146
Duckworth, Chris
992c216c-8f66-48a8-8de6-2f04b4f736e6
Lamas Fernandez, Carlos
e96b5deb-74d5-4c9b-a0ce-448c99526b09
Leyland, Rachael
d972dc0b-1c49-4283-bf48-b4e30e8d6e48
Wright, Mark
96332a4d-46f9-499a-8b28-9f36a22b6e9f
Stammers, Matt
85e202da-1879-4f96-8e24-5059a1fa3f1e
George, Michael
5bd91b32-01fd-4cf1-bc24-f3c4102865c3
Boniface, Michael
f30bfd7d-20ed-451b-b405-34e3e22fdfba

Burns, Dan, Duckworth, Chris, Lamas Fernandez, Carlos, Leyland, Rachael, Wright, Mark, Stammers, Matt, George, Michael and Boniface, Michael (2025) Impact of accurate initial discharge planning and inpatient transfers of care on discharge delays: a retrospective cohort study. BMJ Open, 15 (5), [e097563]. (doi:10.1136/bmjopen-2024-097563).

Record type: Article

Abstract

Objective: to investigate the association between initial discharge planning and transfers of inpatient care with discharge delay. To identify operational changes which could expedite discharge within the Discharge to Assess (D2A) model.

Design: retrospective cohort study.

Setting: University Hospital Southampton National Health Service Foundation Trust (UHS).

Participants: all adults (≥18 years) who registered a hospital inpatient stay in UHS between 1 January 2021 and 31 December 2022 (n=258 051). After excluding inpatient stays without complete discharge planning data or key demographic/clinical information, 65 491 inpatient stays were included in the final analysis. Data included demographics, comorbidities, ward movements, care team handovers and discharge planning records.

Primary and secondary outcome measures: the primary outcome was discharge delay, defined as the number of days between the final estimated discharge date and the actual discharge date. For the purposes of OR analysis, discharge delay was modelled as a binary outcome: any delay (>0 days) versus no delay. Logistic regression models were used to examine associations between initial discharge planning accuracy, the number of ward moves and the number of in-specialty handovers and the likelihood of discharge delay, adjusting for demographic and patient complexity factors.

Results: out of 65 491 inpatient stays, 10 619 had an initial planned discharge pathway that was different from the final discharge pathway. 7790 of these inpatient stays (75.1%) recorded a discharge delay. In contrast, among the 54 872 inpatient stays where the initial and final pathway matched, 10 216 (18.6%) recorded a delay. Using logistic regression modelling a binary outcome (any discharge delay vs no delay), an inaccurate initial pathway was associated with significantly increased odds of delay (adjusted OR (aOR) 2.72, 95% CI 2.55 to 2.91). Each additional ward move (aOR 1.25, 95% CI 1.23 to 1.28) and each in-specialty handover (aOR 1.17, 95% CI 1.14 to 1.20) were also associated with higher odds of discharge delay.

Conclusions: this study finds a strong association between inaccurate initial discharge plans and inpatient transfers of care with discharge delay, after controlling for patient complexity and acuity. This highlights the need to consider how initial plans and inpatient transfers affect discharge planning. Given the lead times for organising onward care, operational inefficiencies are most impactful for patients eventually discharged on pathways with higher planning complexity.

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Accepted/In Press date: 16 May 2025
Published date: 30 May 2025
Keywords: Decision Making, Electronic Health Records, Hospitals, Organisation of health services, Risk management

Identifiers

Local EPrints ID: 503383
URI: http://eprints.soton.ac.uk/id/eprint/503383
ISSN: 2044-6055
PURE UUID: 45428ef8-b44e-445a-bc4e-f2656c1aa3d1
ORCID for Dan Burns: ORCID iD orcid.org/0000-0001-6976-1068
ORCID for Chris Duckworth: ORCID iD orcid.org/0000-0003-0659-2177
ORCID for Carlos Lamas Fernandez: ORCID iD orcid.org/0000-0001-5329-7619
ORCID for Michael Boniface: ORCID iD orcid.org/0000-0002-9281-6095

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Date deposited: 30 Jul 2025 16:31
Last modified: 22 Aug 2025 02:31

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Contributors

Author: Dan Burns ORCID iD
Author: Chris Duckworth ORCID iD
Author: Carlos Lamas Fernandez ORCID iD
Author: Rachael Leyland
Author: Mark Wright
Author: Matt Stammers
Author: Michael George

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