MétaCan
Menu
Back to cohort
Record W1946496733 · doi:10.1111/imj.12919

Improving discharge planning communication between hospitals and patients

2015· article· en· W1946496733 on OpenAlexaff
Peter W. New, Karen E. McDougall, Charlotte Scroggie

Bibliographic record

VenueInternal Medicine Journal · 2015
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
KeywordsMedicineHospital dischargeMedical emergencyPatient dischargeDischarge planningMEDLINEFamily medicineNursingIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: A potential barrier to patient discharge from hospital is communication problems between the treating team and the patient or family regarding discharge planning. AIM: To determine if a bedside 'Leaving Hospital Information Sheet' increases patient and family's knowledge of discharge date and destination and the name of the key clinician primarily responsible for team-patient communication. METHODS: This article is a 'before-after' study of patients, their families and the interdisciplinary ward-based clinical team. Outcomes assessed pre-implementation and post-implementation of a bedside 'Leaving Hospital Information Sheet' containing discharge information for patients and families. Patients and families were asked if they knew the key clinician for team-patient communication and the proposed discharge date and discharge destination. Responses were compared with those set by the team. Staff were surveyed regarding their perceptions of patient awareness of discharge plans and the benefit of the 'Leaving Hospital Information Sheet'. RESULTS: Significant improvement occurred regarding patients' knowledge of their key clinician for team-patient communication (31% vs 75%; P = 0.0001), correctly identifying who they were (47% vs 79%; P = 0.02), and correctly reporting their anticipated discharge date (54% vs 86%; P = 0.004). There was significant improvement in the family's knowledge of the anticipated discharge date (78% vs 96%; P = 0.04). Staff reported the 'Leaving Hospital Information Sheet' assisted with communication regarding anticipated discharge date and destination (very helpful n = 11, 39%; a little bit helpful n = 11, 39%). CONCLUSIONS: A bedside 'Leaving Hospital Information Sheet' can potentially improve communication between patients, families and their treating team.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.124
GPT teacher head0.425
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternal Medicine JournalSame topicFamily and Patient Care in Intensive Care UnitsFrench-language works237,207