Frequency, Timing, and Predictors of Palliative Care Consultation in Patients with Advanced Cancer at a Tertiary Cancer Center: Secondary Analysis of Routinely Collected Health Data
Bibliographic record
Abstract
INTRODUCTION: Early integration of palliative care (PC) with oncological care is associated with improved outcomes in patients with advanced cancer. Limited information exists on the frequency, timing, and predictors of PC consultation in patients receiving oncological care. The Cross Cancer Institute (CCI) is the sole tertiary cancer center serving the northern half of the Canadian province of Alberta, located in the city of Edmonton. The objectives of this study were to estimate the proportion of patients with advanced cancer at the CCI who received consultation by the CCI PC program and the comprehensive integrated PC program in Edmonton, and to determine the timing and predictors of consultation. MATERIALS AND METHODS: In this secondary analysis of routinely collected health data, adult patients who died between April 2013 and March 2014, and had advanced disease while under the care of a CCI oncologist, were eligible. Data from the Alberta Cancer Registry, electronic medical records, and Edmonton PC program database were linked. RESULTS: Of 2,253 eligible patients, 810 (36%) received CCI PC consultation. Median time between consultation and death was 2 months (range, 1.1-5.4). In multivariable logistic regression analysis, age, residence, income, cancer type, and interval from advanced cancer diagnosis to death influenced odds of receiving consultation. Among 1,439 patients residing in Edmonton, 1,121 (78%) were referred to the Edmonton PC program. CONCLUSION: A minority of patients with advanced cancer received PC consultation at the tertiary cancer center, occurring late in the disease trajectory. Frequency and timing of PC consultation varied significantly, according to multiple factors. IMPLICATIONS FOR PRACTICE: Clinical and demographic factors are associated with variations in frequency and timing of palliative care consultation at a cancer center and may, in some cases, reflect barriers to access that warrant attention.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".