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Record W2782821284 · doi:10.12968/bjon.2018.27.1.24

Rapid response: a multiprofessional approach to hospital at home

2018· article· en· W2782821284 on OpenAlexaboutno aff
Sara Dowell, George Donelson Moss, Katy Mara Odedra

Bibliographic record

VenueBritish Journal of Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcute hospitalService (business)Quarter (Canadian coin)Acute careHospital admissionPopulation ageingPopulationEmergency medicineMedical emergencyNursingHealth careBusiness

Abstract

fetched live from OpenAlex

The provision of 'hospital at home' is not new to the 21st century but pressure from the reduction in the number of hospital beds, population growth, an ageing population and subsequent extended time living with long-term conditions means such services are increasingly necessary. However, research by the authors found services that already exist do not operate 24 hours a day or provide a single multiprofessional approach. Gloucestershire's rapid response (RR) service provides specialist, coordinated, comprehensive and supportive assessment and treatment 24 hours a day in the patient's own home. Data were collected over a 5-month period detailing the number of patients admitted to the service and its impact on hospital admission avoidance and patient outcome. The cost savings and reduction in length of hospital stay is considerable (to almost a quarter of the cost and number of bed days of an acute hospital admission). The position of the hospital as the main provider of urgent/acute care is shifting. The RR service demonstrates its position as a provider of an innovative service that breaks down the boundaries between acute, primary and social care.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.818
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.030
GPT teacher head0.325
Teacher spread0.295 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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