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Hyper acute stroke unit patient suitability for early supported discharge: Coordination and data analysis project

2016· article· en· W2556320897 on OpenAlexaff
Nicola Perkins, Mirek Skrypak, Sarah Barron, Cherry Kilbride, Robert Simister, Hilary Walker

Bibliographic record

VenueInternational Journal of Therapy and Rehabilitation · 2016
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsOntario Stroke Network
Fundersnot available
KeywordsUnit (ring theory)Stroke (engine)MedicineSocial careOrder (exchange)Acute strokeNursingAcute careHealth careMedical emergencyPsychologyBusinessEngineeringPolitical science

Abstract

fetched live from OpenAlex

Research has shown the benefits of early supported discharge (ESD) from stroke units on patient outcomes as well as reducing bed days in hospital. This 6-month project identified that there are higher numbers of patients (12%) who could go home earlier from the hyper acute stroke unit via ESD services when there was an ESD coordinator role in place. In order for this to occur, however, there needs to be a closer interprofessional working relationship with social services with regards to ensuring that both patient health and social needs are met. This role could potentially increase the amount of appropriate patients being discharged to ESD teams, thus allowing access to evidence-based care. This short report describes how appropriate coordination can meet patient needs while saving the local stroke health economy over £230 000 in a 6-month period.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0020.007
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.035
GPT teacher head0.354
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2016
Admission routes1
Has abstractyes

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Same venueInternational Journal of Therapy and RehabilitationSame topicStroke Rehabilitation and RecoveryFrench-language works237,207