Patient-reported symptoms obtained through telephonic nursing services in an oncology disease management program.
Bibliographic record
Abstract
147 Background: Telephonic nursing (RN) outreach was provided as part of an oncology disease management program to provide symptom (sx) management education, assess patient-reported sxs during treatment (tx), and reduce acute care utilization. The Edmonton Symptom Assessment Scale (ESAS) was used to assess sx severity in patients (pts) receiving active chemotherapy. Methods: ESAS scores were obtained at scheduled intervals and documented in the electronic health record for eligible pts receiving chemotherapy between 6/2010-12/2012. Participation was voluntary. Pts were categorized according to cancer diagnosis (dx) and tx setting (early vs. advanced). Repeated measures logistic regression analysis was used to test for differences in ESAS scores between dx and tx settings. Results: 365 pts had 2,198 calls with ESAS scores. Mean age was 53 yrs, 67% female, 33% male. Pts were managed an average of 97 days and received on avg 6 calls/pt. The majority of pts had breast, colon, and non-small cell lung (NSCL) cancer (74%). Of these pts, the most frequent reported sx of any severity other than zero during post-tx calls were for mild/moderate tiredness, appetite, and pain. There was no evidence of a significant difference in the severity of sxs by tx setting in these cohorts; p=NS. One hundred and nine breast, colon, and NSCL pts (40%) received additional unscheduled calls based on sx scores or RN assessment. Outcomes related to acute care utilization are being evaluated. Conclusions: Pt reported sxs obtained through telephonic RN support demonstrated mild/moderate ESAS scores for mainly tiredness, appetite, and pain. This is lower than previously reported in different contexts. Regular RN contact as a supplement to clinic visits may help reduce sx severity. While the ESAS tool is traditionally used for palliative care, in this active tx setting it supported identification of sxs for referrals back to the practice with the goal to reinforce education and avoid acute care utilization. [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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.006 | 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".