Impact of pharmacy interventions on pain management in an oncology palliative medicine (PM) outpatient clinic.
Bibliographic record
Abstract
119 Background: PM can improve the quality of life and survival for cancer patients (pts); however, the demand for PM challenges providers with delayed follow ups resulting in less than one-third of pts achieving significant pain improvement between clinic visits. Engaging pharmacists in the provision of PM may help improve pain management in cancer pts. Methods: Adult cancer pts starting a new pain regimen or requiring changes to an existing regimen at baseline were referred for pharmacy follow up in 3-7 days (assessment #1). The pharmacist evaluated each pt using the Edmonton Symptom Assessment Scale and recommended changes to the referring PM provider, prompting a 2nd follow up in 3-7 days (assessment #2). If no changes were required, pts continued therapy and returned for the final clinic visit (day 28 +/- 7). The primary endpoint was the proportion of pts achieving significant pain improvement (≥ 2-point decrease in pain score on a scale of 0-10) from baseline to final visit, which was compared to historical controls using Fisher’s Exact test. Changes in pain severity from baseline to final visit were compared using Generalized McNemar’s test, and descriptive statistics were used to describe characteristics at assessment #1. Results: Of 102 pts evaluable for the primary endpoint, 76% had stage IV disease, 58% were female, and median age was 57 yrs. Significantly more pts achieved pain improvement from baseline to final visit compared to historical controls (49% v 30%; P < 0.001). Changes in pain severity from baseline to final visit are described in the table. At assessment #1, 70% of pts required an intervention, primarily due to uncontrolled pain (72%), side effects (26%), and/or lack of response to non-pain medications (22%). The most common types of interventions were dose adjustments (62%), education (36%), and/or adding a new medication (30%). Over 90% of recommendations were accepted by the referring PM provider. The median time of assessment was 15 mins. Conclusions: Routine inclusion of pharmacists in the outpatient PM interdisciplinary team improves the effectiveness of pain management. [Table: see text]
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".