Oral oncolytics: Patient-monitoring improvements in private practice.
Bibliographic record
Abstract
215 Background: The use of oral oncolytics is becoming more common. These drugs have their own unique challenges in managing patient initiation, monitoring side effects and adherence. Methods: We conducted a baseline chart audit of patients prescribed oral oncolytics in our private oncology practice followed by a quality improvement program and subsequent reassessment. Information obtained included: prescription date, actual start date and any documented problems with the oral therapy. The baseline audit included patients from may of 2011 to July 2013. Subsequently we joined the Michigan oncology quality consortium’s oral chemotherapy collaborative and initiated the following: office procedures for identification of all patients on oral therapy, use of the Edmonton Symptoms assessment system (ESAS), and a self-care management education program including patient self-monitoring of symptoms with recommended initial treatments. A postintervention audit was conducted from August 2013 to March 2014. Results: We identified 25 patients in the first time period and 13 in the second. In the first time period we found only 13 of the 25 patients had an actual start date documented, and of these 13, 10 had a >/=4 week delay prior to starting therapy, with 3/13 having a 2-4 week delay prior to start of therapy. 12 of the 25 patients discontinued their drug within the first month due to side effects without consulting their physician. After participating in the quality initiative, we identified only one patient without a documented start date, only 1/13 that had a > 4 week delay from prescription date to starting the drug, with 12/13 having a less than 2 week lapse. We also found that there were no patients who discontinued the drug and only one dose reduction as directed by the physician. Conclusions: The introduction of new office procedures to easily identify all patients on oral therapy and improved patient management of symptoms at home with the use of self-care guidelines, and in the office with use of ESAS contributed to greater adherence to oral chemotherapy regimens.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.004 | 0.014 |
| 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 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".