Building capacity for palliative care delivery in primary care settings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To evaluate an intervention aimed at building capacity to deliver palliative care in primary care settings. DESIGN: The INTEGRATE Project was a 3-year pilot project involving interprofessional palliative care education and an integrated care model to promote early identification and support of patients with palliative care needs. A concurrent mixed-methods evaluation was conducted using descriptive data, provider surveys before and after implementation, and interviews with providers and managers. SETTING: Four primary care practices in Ontario. PARTICIPANTS: All providers in each practice were invited to participate. Providers used the "surprise question" as a prompt to determine patient eligibility for inclusion. MAIN OUTCOME MEASURES: Provider attitudes toward and confidence in providing palliative care, use of palliative care tools, delivery of palliative care, and perceived barriers to delivering palliative care. RESULTS: < .05). There was substantial variation across practices regarding the percentage of patients identified using the surprise question (0.2% to 1.5%), the number of advance care planning conversations initiated (50% to 90%), and mean time to conversation (13 to 76 days). This variation is attributable, in part, to contextual differences across practices. CONCLUSION: A standardized model for the early introduction of palliative care to patients can be integrated into the routine practice of primary care practitioners with appropriate training and support. Additional research is needed to understand the practice factors that contribute to the success of palliative care interventions in primary care and to examine patient outcomes.
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.
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) | 0.000 | 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 it