Comparing the Validity of Different Sources of Information on Emergency Department Visits
Bibliographic record
Abstract
BACKGROUND: Emergency department (ED) use in Quebec may be measured from varied sources, eg, patient's self-reports, hospital medical charts, and provincial health insurance claims databases. Determining the relative validity of each source is complicated because none is a gold standard. OBJECTIVE: We sought to compare the validity of different measures of ED use without arbitrarily assuming one is perfect. SUBJECTS: Data were obtained from a nursing liaison intervention study for frail seniors visiting EDs at 4 university-affiliated hospitals in Montreal. MEASURES: The number of ED visits during 2 consecutive follow-up periods of 1 and 4 months after baseline was obtained from patient interviews, from medical charts of participating hospitals, and from the provincial health insurance claims database. METHODS: Latent class analysis was used to estimate the validity of each source. The impact of the following covariates on validity was evaluated: hospital visited, patient's demographic/clinical characteristics, risk of functional decline, nursing liaison intervention, duration of recall, previous ED use, and previous hospitalization. RESULTS: The patient's self-report was found to be the least accurate (sensitivity: 70%, specificity: 88%). Claims databases had the greatest validity, especially after defining claims made on consecutive days as part of the same ED visit (sensitivity: 98%, specificity: 98%). The validity of the medical chart was intermediate. Lower sensitivity (or under-reporting) on the self-report appeared to be associated with higher age, low comorbidity and shorter length of recall. CONCLUSION: The claims database is the most valid method of measuring ED use among seniors in Quebec compared with hospital medical charts and patient-reported use.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".