Performance of Patient-Reported Outcome Measures in a Large Pragmatic Trial of Home-Based Palliative Care (HomePal): Methodological and Practical Considerations for Embedded Patient-Centered Design
Bibliographic record
Abstract
Background: The research enterprise has embraced patient centeredness in embedded efficient pragmatic trials, but limited data exist on using patient-reported outcomes (PROs) collected as part of usual clinical care for research. Objectives: We sought to assess the performance of different assessment methods for obtaining PROs in a pragmatic cluster randomized trial (HomePal study) designed to compare two models of home-based palliative care (HBPC). Design: Descriptive analytics, comparative trends, and psychometric performance of PROs collected in the HomePal study; measures included Edmonton Symptom Assessment System (ESAS), PROMIS-10, and others administered at baseline, 1, and 6 months. Setting/Subjects: HomePal was conducted in the Southern California and Northwest Kaiser Permanente regions in the United States; subjects were patients receiving HBPC and their caregivers. Measurements: We specifically compared ESAS obtained by research staff with those obtained by clinical HBPC nurses at the time of HBPC enrollment. We also compared ESAS completed by patients versus if done or assisted by a caregiver (proxy). Results: We enrolled 3533 patients and had 2205 ESAS measurements that met the criteria for analysis at baseline and 1447 at the one-month follow-up assessment. Research staff-obtained ESAS at admission to HBPC was higher overall (indicating more symptoms) than the clinically collected measure whether symptoms were reported by patients (31.7 ± 15.4 vs. 26.0 ± 13.4) or by proxies (36.9 ± 15.6 vs. 26.5 ± 13.5). These differences persisted with follow-up ESAS measures. Conclusions: We identified significant variability in PRO responses between different surveyors and whether proxy interaction was needed suggesting complex issues around PRO measure performance for pragmatic embedded trials. ClinicalTrials.gov Identifier: NCT03694431.
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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 | 0.402 | 0.398 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| 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; 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".