Implementation and assessment of a provincial early palliative care initiative for patients with pancreatic cancer.
Bibliographic record
Abstract
e18742 Background: Early palliative care (EPC) referral reduces health care costs & improves quality of life and survival in some advanced cancers. One barrier to EPC is hesitancy of care providers to refer. In April 2022, our provincial cancer centre (CCMB) implemented a clinical nurse specialist (CNS)-led intervention for patients with advanced pancreatic cancer (PANC), circumventing known barriers. New PANC referrals received at the centralized referral office are triaged by an oncologist & concurrently referred to the CNS. CNS consultation focuses on physical & psychological symptoms, medication review, patient/family coping, & goals of care. Education is provided on PANC diagnosis, prognosis, symptoms, potential treatment options, navigating the cancer system & community palliative care/hospice supports, with close collaboration with the patient’s primary care provider. The primary aim of this study is to assess the impact of the CNS role on referral to multidisciplinary palliative care/hospice services within 8 weeks of diagnosis. Methods: We compared patients with PANC in the pre-implementation period (April 1, 2021 to December 31, 2021) to the post-implementation period (April 1, 2022 to December 31, 2022). Patients were identified using the Manitoba Cancer Registry & the CNS clinical database. Descriptive statistics were used to report quality measures. A one sample test of proportions was used to compare EPC referral in the pre- & post-implementation periods. Results: In the pre-implementation period, 64 patients were referred to CCMB with PANC. Fifty-nine (92%) were diagnosed via biopsy, 52 (81%) had consultation with a medical oncologist, 32 (50%) received chemotherapy. Forty-four (69%) were referred to a palliative care/hospice program. In the post implementation period, 88 patients were referred to CCMB. Eighty-five (97%) accepted a consultation with the CNS, with a median time to meeting of 6 days (range, 0-18), and 75% of patients seen within 10 days. After CNS consultation, 28 (32%) declined biopsy, oncology appointment or both. Overall, sixty-three (72%) patients in this cohort had a diagnostic biopsy, 59 (67%) had a consultation with a medical oncologist, 29 (33%) received chemotherapy. Fifty-nine (67%) were referred to a palliative care/hospice program. In the pre-implementation period, 24 (38%) patients were referred to palliative care/hospice within 8 weeks of diagnosis, compared to 44 (50%) in the post-implementation period (p = 0.0154). Conclusions: This novel approach demonstrates CNS assessment & education soon after diagnosis of PANC, at the time of referral to CCMB, results in an increased proportion of patients being referred for community-based palliative care/hospice within 8 weeks of diagnosis. Exploring patient goals early may also spare patients from invasive & timely procedures, allowing those with a life limiting illness to focus on quality of life.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".