Accuracy of Physician Reporting in Routine Public Health Surveillance for Hepatitis C Virus Infection
Bibliographic record
Abstract
OBJECTIVE: From January 2007 to December 2008, the Montréal Public Health Department sent postal questionnaires to physicians and conducted patient interviews for all those newly diagnosed with hepatitis C virus (HCV) infection. We evaluated physician responses to risk factor questions for non-acute HCV cases. METHODS: We compared physician and patient responses with each of nine risk factor questions, determined the sensitivity and specificity of physician responses compared with patient responses, and evaluated agreement using Gwet's agreement coefficient (AC1). We ranked risk factors and compared the distributions by principal exposure category according to physician reporting vs. patient interview using the Chi-square test. RESULTS: The completeness of physicians' responses (yes, no, or unknown) varied by risk factor question from 90.8% to 96.7%. For risk factors present among more than 5% of cases, sensitivity of physician responses ranged from 26.9% to 87.7% and specificity ranged from 93.0% to 98.6%. The AC1 coefficients for agreement between physician and patient responses to lifetime risk factors considered most important in HCV acquisition were 0.80 for injection drug use, 0.95 for blood transfusion before 1990, and 0.86 for birth in a country with high HCV prevalence. Risk distributions by principal exposure category according to physician reporting vs. patient interview were not statistically different (χ(2)[4] = 2.17, p=0.704). CONCLUSION: Postal questionnaires completed by physicians appear valid for determining the principal exposure category among non-acute HCV cases. Physician reporting can be a useful and low-cost component of routine HCV surveillance.
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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 | 0.024 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".