The Use of Generic Patient-Reported Outcome Measures in Emergency Department Surveys: Discriminant Validity Evidence for the Veterans RAND 12-Item Health Survey and the EQ-5D
Bibliographic record
Abstract
Objectives This study aimed to compare discriminant validity evidence of 2 generic patient-reported outcome measures (PROMs), the Veterans RAND 12-Item Health Survey (VR-12) and level 5 of EQ-5D (EQ-5D-5L), for use in emergency departments (EDs). Methods Data were obtained via a cross-sectional survey of 5876 patients in British Columbia (Canada) who completed a questionnaire after visiting an ED in 2018. We compared the extent to which the VR-12 and the EQ-5D-5L distinguished among groups of ED patients with different levels of comorbidity burden and self-reported physical and mental or emotional health status. Multivariable logistic regression was used to evaluate the ability of the 2 PROMs to identify patients presenting with a mental health (MH) condition. Results All the measures produced small effect sizes (ESs) for discriminating comorbidity levels (R 2 range: 0.00 [VR-12 mental component summary {MCS}] to 0.10 [VR-12 physical component summary score]). The EQ-5D visual analog scale offered the largest ES for discriminating self-reported physical health (R 2 = 0.48), whereas the MCS, the VR-12 MH domain, and the EQ-5D-5L anxiety/depression dimension had the largest ESs for discriminating self-reported mental or emotional health (R 2 = 0.42, 0.40, and 0.38, respectively). The MCS produced a medium ES (R 2 = 0.42) along with the VR-12 utility score (R 2 = 0.27) compared with the EQ-5D-5L index (R 2 = 0.19). Having a MH condition was predominantly identified by the MCS (Pratt index = 0.56). Conclusions The VR-12 PROM provides a more comprehensive measurement of MH than the EQ-5D-5L, which is important to inform healthcare service needs for patients who present in EDs with MH challenges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".