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Record W2069515068 · doi:10.12927/cjnl.2011.22335

Bringing Back the House Call: How an Emergency Mobile Nursing Service Is Reducing Avoidable Emergency Department Visits for Residents in Long-Term Care Homes

2011· article· en· W2069515068 on OpenAlexaffvenue
Annabelle Bandurchin, Mary McNally, Mary Ferguson-Paré

Bibliographic record

VenueNursing leadership · 2011
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsOvercrowdingEmergency departmentMedicineNursingLong-term careScope of practiceHealth careEmergency nursingAnxietyMedical emergencyGerontologyPsychiatry

Abstract

fetched live from OpenAlex

Avoidable emergency department (ED) visits are a source of clinical risk, stress and anxiety for older, more vulnerable patients. The complexity of health conditions and the unique challenges associated with the care of older patients can also contribute to overcrowding and longer wait times in EDs--issues of significant concern for both healthcare providers and patients. Generally, older patients are more likely than younger patients to visit EDs and be admitted to hospital. In addition, older adults living in long-term care (LTC) homes are more likely to be transferred to EDs for preventable issues than those living in other settings. This paper describes how mobilizing a team of registered nurses working at full scope of practice might reduce the number of avoidable transfers of older patients to the ED. Utilizing nurses in this capacity demonstrates how the nursing profession can drive systemwide change to improve care between healthcare sectors for older adults.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.130
GPT teacher head0.338
Teacher spread0.208 · 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.

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

Citations16
Published2011
Admission routes2
Has abstractyes

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