Defining a patient-reported outcome measure (PROM) selection process: What criteria should be considered when choosing a PROM for routine symptom assessment in clinical practice?
Bibliographic record
Abstract
187 Background: PROMs capture the patient’s perspective on their health status and thus improve person-centred care. The Edmonton Symptom Assessment System has been the standard PROM used for all patients in Ontario. Recently, Cancer Care Ontario has chosen to expand the use of PROMs by adding cancer specific tools. The objective of this work was to develop a process to systematically evaluate and select PROMs for routine use in clinical practice. Methods: The development of the PROM selection process included several steps: 1) a literature scan to identify existing PROM selection guidelines and considerations; 2) development of clinically relevant criteria by a panel of methodological experts and patient advisors; and 3) use of a case study to test the process and identify gaps. In the case study, disease-site experts and patients were given the opportunity to review the PROMs and provide feedback. Results: The literature scan highlighted six resources endorsing three common considerations for PROM selection: symptom coverage, usability, and psychometric properties. The expert panel further developed criteria for each consideration. Symptom coverage criteria include percentage of prevalent, bothersome and expert endorsed symptoms addressed by the PROM. Usability criteria include: reference time-frame, scale, time to complete, scoring, plain language and translations. Psychometric criteria are: internal consistency, reliability, responsiveness, discrimination ability, meaningful change and translation validity. Each consideration is scored as weak, average or good based on how well the criteria are met. A summary matrix illustrates the overall assessment. In the case study, the selection process identified two top-performing PROMs; disease-specific patient focus groups were held to inform the final decision. Conclusions: This rigorous evaluation of candidate measures resulted in the selection of a PROM that was accepted by methodological experts, clinical advisors and patients. The case study demonstrated the value of disease-specific patient input on PROM selection.
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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 | 0.562 | 0.672 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".