Integrating Palliative Care Into the Outpatient, Private Practice Oncology Setting
Bibliographic record
Abstract
CONTEXT: Quality care for patients with cancer is a national priority-for those with noncurable cancer, the stakes are even higher. Strategies to promote integration of palliative care into oncology practice may enhance quality. We have developed a model in which palliative care services are integrated into the private, office-based oncology practice setting. We have evaluated the feasibility and assessed outcomes for both the oncologists and the patients they serve. To our knowledge, an embedded clinic in an outpatient, private practice oncology clinic has not been described previously. OBJECTIVE: The primary outcomes assessed were 1) quality care outcomes through assessment of symptom burden and relief achieved through palliative care consultation, 2) provider satisfaction, 3) volume determined by number of palliative care consultations over time, and 4) time saved for the oncologist as a surrogate for the bottom line of the cancer practice. METHODS: Measurement of: symptom burden and relief with the Edmonton Symptom Assessment System (ESAS), physician acceptance of palliative care services through a provider satisfaction survey and volume of referrals, and billing data to determine potential oncologists' time saved. RESULTS: Palliative care consultation was associated with a reduction in symptom burden by 21%, evidenced by decrease in average total ESAS score from 49.3 to 39. Median provider satisfaction scores rating components of palliative care ranged from 8.5 to 9/10, with an overall provider satisfaction of 9/10. Over the study period, the "embedded" oncology group consultation requests increased 87% (67-120), with each individual oncology provider nearly doubled. The total time saved for the oncology practice in Year 2 was just over four weeks (9720 minutes; 162 hours). CONCLUSION: An embedded palliative care clinic integrated into an office-based oncology practice is feasible and may improve the quality of care. Formal study of this service delivery model is warranted.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".