Integrating early palliative care into routine practice for patients with cancer: A mixed methods evaluation of the INTEGRATE Project
Bibliographic record
Abstract
OBJECTIVE: With increasing evidence from controlled trials on benefits of early palliative care, there is a need for studies examining implementation in real-world settings. The INTEGRATE Project was a 3-year real-world project that promoted early identification and support of patients with cancer who may benefit from palliative care. This study assesses feasibility, stakeholder experiences, and early impact of the INTEGRATE Project METHODS: The INTEGRATE Project was implemented in four cancer centers in Ontario, Canada, and consisted of interdisciplinary provider education and an integrated care model. Providers used the Surprise Question to identify patients for inclusion. A mixed methods evaluation of INTEGRATE was conducted using descriptive data, interviews with providers and managers, and provider surveys. RESULTS: A total of 760 patients with cancer (lung, glioblastoma, head and neck, gastrointestinal) were included. Results suggest improvement in provider confidence to deliver palliative care and to initiate the Advanced Care Planning (ACP) conversation. The majority of patients (85%) had an ACP or goals of care (GOC) conversation initiated within a mean time to conversation of 5-46 days (SD 20-93) across centers. A primary care report was transmitted to family doctors 48-100% of the time within a mean time to transmission of 7-54 days (SD 9-27) across centers. Enablers and barriers influencing success of the model were also identified. CONCLUSIONS: A standardized model for the early introduction of palliative care for patients with cancer can be integrated into the routine practice of oncology providers, with appropriate education, integration into existing clinical workflows, and administrative support.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".