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Record W2008980858 · doi:10.1089/jpm.2008.0002

Palliative Care Telephone Consultation: Who Calls and What do they Need to Know?

2008· article· en· W2008980858 on OpenAlexaff
Julia Ridley, Romayne Gallagher

Bibliographic record

VenueJournal of Palliative Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsProvidence Health Care
Fundersnot available
KeywordsMedicinePalliative careFamily medicineMEDLINENeed to knowNursingMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Access to expertise in palliative management in areas not served by palliative care consultants is an ongoing challenge. This study examines a unique service offered in British Columbia: a 24-hour telephone hotline available to physicians, nurses, and pharmacists across the province. METHODS: Records of calls to the hotline over 4 years were collected. Call data included information on the caller, patient, and problem. The resulting database was analyzed for trends, including cross-tabulations to look for associations between call characteristics. RESULTS: Six hundred ninety-two calls were included. A large variety of topics were addressed in significant numbers, ranging from symptom control to ethical concerns. The primary reason for calls to the line was pain management, followed by gastrointestinal symptoms such as nausea, diarrhea, and bowel obstruction. Patients with cancer diagnoses dominated the call volume; lung, colon, breast, prostate, and pancreatic cancer were the most common specific diagnoses. The majority of calls, when analyzed by population, came from areas with significant rural populations. CONCLUSION: British Columbia's Palliative Care Hotline provides a valuable service that has been utilized province-wide with increasing frequency over the 6 years it has been in operation. It serves a variety of professionals and significant number of patients. Rural communities utilize the service with the most frequency, indicating the support needed in these communities. Similar services should be considered in other jurisdictions.

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)0.003
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 score0.097
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.090
GPT teacher head0.407
Teacher spread0.317 · 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

Citations17
Published2008
Admission routes1
Has abstractyes

Explore more

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