Evidence map›Paper›PMID 40447438›Full record

ArticleBMJ open2025

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

Dan Burns, Chris Duckworth, Carlos Lamas-Fernandez, Rachael Leyland, Mark Wright, Matt Stammers, Michael George, Michael Boniface

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Dan BurnsSchool of Electronics and Computer Science, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0001-6976-1068
Chris DuckworthSchool of Electronics and Computer Science, University of Southampton, Southampton, UK.
Carlos Lamas-FernandezSouthampton Business School, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0001-5329-7619
Rachael LeylandUniversity Hospital Southampton Foundation Trust, Southampton, UK.
Mark WrightUniversity Hospital Southampton Foundation Trust, Southampton, UK.
Matt StammersUniversity Hospital Southampton Foundation Trust, Southampton, UK.ORCID http://orcid.org/0000-0003-3850-3116
Michael GeorgeUniversity Hospital Southampton Foundation Trust, Southampton, UK.
Michael BonifaceSchool of Electronics and Computer Science, University of Southampton, Southampton, UK M.J.Boniface@soton.ac.uk.ORCID http://orcid.org/0000-0002-9281-6095

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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.

designRetrospective cohort study.

settingUniversity Hospital Southampton National Health Service Foundation Trust (UHS).

participantsAll 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.

resultsOut 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.

conclusionsThis 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.

Indexed as

Patient DischargePatient TransferAdultAgedAged, 80 and overFemaleHumansLength of StayLogistic ModelsMaleMiddle AgedPatient HandoffRetrospective StudiesTime FactorsDecision MakingElectronic Health RecordsHospitalsOrganisation of health servicesRisk management

Identifiers

PMID40447438
PMCPMC12128396

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.