Comparing patient-reported outcomes across countries: An assessment of methodological challenges
Bibliographic record
Abstract
OBJECTIVES: There is little published literature on the comparison of patient-reported outcomes between countries. This study aimed to assess pre- and postoperative health among samples of patients undergoing elective groin hernia repair procedures in the National Health Service (NHS), England, and groin hernia patients in Vancouver, Canada. METHODS: We used datasets from two different sources. For the English NHS we used published anonymized patient-level data files which include the EQ-5D(3L) patient-reported outcome measure and a number of demographic and clinical characteristics. For Vancouver, we used data from a sample of Vancouver patients who completed the same instrument during a similar time frame. English patients were matched with Vancouver participant's characteristics using propensity score methods. A linear regression model was used to measure differences in postoperative visual analogue scale values between countries, adjusting for patient characteristics. RESULTS: Our study revealed a range of methodological issues concerning the comparability of patient-reported outcomes following hernia repair surgery in the two health systems. These related to differences in approaches to collecting patient-reported outcome measures and the nature of explanatory variables (self-report vs. administrative data), among other challenges. As a consequence, there were differences between the matched samples and the NHS data, indicating a healthy participant bias. Unadjusted results found that Vancouver patients (N = 280) reported more problems in domains of mobility, self care, usual activities and anxiety/depression than the matched cohort of NHS patients (N = 840). Interpreting differences is challenging given different sampling designs. CONCLUSIONS: There are significant hurdles facing comparisons of surgical patients' outcomes between countries, including adjusting for patient differences, health system factors and approaches to survey administration. While between-country comparisons of surgical outcomes using patient-reported outcomes shows significant promise, much work on standardizing sampling design, variables and analytic methods is needed.
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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 | 0.699 | 0.807 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".