Real-World Study of the Implementation of Early and Systematic Palliative Care for Advanced Colorectal Cancer Care—The Palliative Care Early and Systematic Project
Bibliographic record
Abstract
PURPOSE To develop and evaluate real-world interventions to move guidelines on timely palliative care utilization into practice. METHODS A knowledge-to-action cycle theory–informed, process improvement project facilitated implementation of a clinical practice guideline by (1) systematically screening clinic patients for unmet palliative care needs and alerting the oncologist, (2) using a dedicated community-based palliative care nurse for each referral, and (3) using Shared-care letters (structured communication between oncologist, family physician, and patient) to enhance information exchange and awareness of patients' needs. Implementation occurred for advanced colorectal cancer (CRC) within the GI clinics of the Tom Baker Cancer Center, Calgary, AB, Canada, and the neighboring city's Cross Cancer Institute, Edmonton, AB, Canada acted as control. The primary outcome was the proportion of adult decedents with CRC who received early specialist palliative care (SPC; defined as >90 days before death), evaluated using a pragmatic, controlled, before-and-after study. Eligible decedents in each city were identified using provincial cancer registry data and linked with administrative data identifying palliative care consultation, homecare, hospice, or inpatient unit usage. RESULTS The cohort included 695 decedents: 341 baseline period (153 control, 188 intervention, April 2017-December 2018) and 354 implementation period (145 control, 209 intervention, April 2019-December 2020); the mean age was 66.5 years, 60% was male, and 95.2% was urban-dwelling. In the intervention arm, the proportion of decedents who received palliative care >90 days before death increased from 44.7% at baseline to 57.4% after implementation; in the control arm, the proportion decreased from 47.7% to 44.1% (17.7% difference in differences [95% CI, 3.1-32.4]; P = .018). CONCLUSION This intervention effectively increased early SPC utilization and provides a pragmatic approach to achieve and measure system-level change.
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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 | 0.034 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".