Feasibility and acceptability of implementing an electronic patient reported outcome (e-PRO) dysphagia screening tool for routine multidisciplinary care.
Bibliographic record
Abstract
155 Background: In Ontario, Canada, longitudinal patient self-reporting of 9 common cancer symptoms and a global health scale (Edmonton Symptom Assessment System, ESAS) is mandated and used clinically as a screening tool for multidisciplinary precision care (chemo/rads/surg). However, a common GI symptom, dysphagia, is not assessed in the same setting. Methods: Mostly gastro-esophageal cancer outpatients (some head and neck and lung cancer patients undergoing radiation were also included for generalizability) received one of two versions (V1, V2) of the dysphagia screening tool based on PRO-CTCAE-derived language. The tool included two screening questions, which when answered affirmatively, led to more comprehensive dysphagia/odynophagia questioning. The survey was introduced on iPads with V1. An assessment of acceptability through patient survey was additionally included in V2, and the duration of survey completion was recorded. Exploratory in-depth interviews were conducted with oncologists to assess usability in the clinic setting. Results: Of 101 approached and eligible, 79 consented, and 66 completed the survey. Median completion time was 2.12 ± 0.80 min. 95% were happy to complete survey on a touchscreen tablet, 88% did not find completion of survey time-consuming, and 91% found completion of survey useful in order to tell the clinician how they feel physically and emotionally. The prevalence of dysphagia based on screening question #1 (“difficulty upon swallowing?”) was 38% (25/66), while for screening question #2 (“pain upon swallowing?”) prevalence was 18% (12/66). Five interviewed physicians found the survey to be clinically informative, not burdensome in terms of time consumption, and felt it would be a valuable addition to outpatient clinics. One recurring suggestion was to combine the two screening questions into one. Results were similar across GI, head and neck, and lung cancer sites. Conclusions: The e-PRO dysphagia screening tool is acceptable and feasible for patients, and useful for clinicians. Next, a modified one-question dysphagia tool will be assessed in the multidisciplinary care of gastro-esophageal cancer patients.
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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 | 0.041 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".