Involving patients to improve their care through real-time patient reported outcome (PRO)-CTCAE chemotoxicity surveys in an outpatient chemodaycare (DC) setting: Evaluating patient acceptability.
Bibliographic record
Abstract
64 Background: In a busy DC setting, the efficiency of identifying important treatment toxicities is essential to quality care. Using a systematic approach to collecting patient-reported outcomes in the waiting rooms of DC units is one possible means of improving care while involving patients. This study reports such a pilot study, and the associated assessment of patient acceptance of this approach. Methods: 156 cancer patients over the age of 18 receiving chemotherapy treatment at Princess Margaret Cancer Centre completed a patient-reported chemotoxicity assessment using PRO-CTCAE items on tablet technology. Main symptoms assessed were: fatigue, nausea and vomiting, diarrhea and constipation, pain, aching muscles and/or joints and dysgeusia. Patient’s perception on the usefulness of PROMs and their willingness to complete such a tool routinely was assessed. Results: The median age was 53.5 (range: 19-88 years), 38% were male and 66% were Caucasian. Over 80% did not find the survey overly time consuming (or made their visit more difficult). Less than 1% were distressed by the survey questions. Over 80% reported that the survey asked the appropriate questions. While 81% considered the PROMs useful in informing their physician of their symptoms, 25% reported they would not be willing to complete the survey at each clinic visit. Another 25% were unsure of their feelings toward this approach. 93% were happy to complete the survey using tablet touchscreen technology. Conclusions: Most patients found the survey method of self-reporting one’s symptoms to be acceptable, non-distressful, and an important practice. From the patient perspective, the process of reporting one’s symptoms using tablet touchscreen technology is both simple and feasible.Yet, only 50% of patients would be willing to complete this survey at every clinic visit. Additional mixed-methods analysis looking at patient characteristics associated with acceptance/non-acceptance and willingness to complete the survey on a regular basis is ongoing and will be reported at the conference.
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.
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 | 0.017 | 0.033 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".