Palliative Care Telephone Consultation: Who Calls and What do they Need to Know?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".