How well do ICD-9 physician claim diagnostic codes identify confirmed pertussis cases in Alberta, Canada? A Canadian Immunization Research Network (CIRN) Study
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background Rates of Bordetella pertussis have been increasing in Alberta, Canada despite vaccination programs. Waning immunity from existing acellular component vaccines may be contributing to this. Vaccine effectiveness can be estimated using a variety of data sources including diagnostic codes from physician billing claims, public health records, reportable disease and laboratory databases. We sought to determine if diagnostic codes from billing claims (administrative data) are adequately sensitive and specific to identify pertussis cases among patients who had undergone disease-specific laboratory testing. Methods Data were extracted for 2004–2014 from a public health communicable disease database that contained data on patients under investigation for B. pertussis (both those who had laboratory tests and those who were epidemiologically linked to laboratory-confirmed cases) in Alberta, Canada. These were deterministically linked using a unique lifetime person identifier to the provincial billing claims database, which contains International Classification of Disease version 9 (ICD-9) diagnostic codes for physician visits. We examined visits within 90 days of laboratory testing. ICD-9 codes 033 (whooping cough), 033.0 (Bordetella pertussis), 033.1 (B. parapertussis), 033.8 (whooping cough, other specified organism), and 033.9 (whooping cough, other unspecified organism) in any of the three diagnostic fields for a claim were classified as being pertussis-specific codes. We calculated sensitivity, specificity, positive (PPV) and negative (NPV) predictive values. Results We identified 22,883 unique patients under investigation for B. pertussis. Of these, 22,095 underwent laboratory testing. Among those who had a laboratory test, 2360 tested positive for pertussis. The sensitivity of a pertussis-specific ICD-9 code for identifying a laboratory-confirmed case was 38.6%, specificity was 76.9%, PPV was 16.0%, and NPV was 91.6%. Conclusion ICD-9 codes from physician billing claims data have low sensitivity and moderate specificity to identify laboratory-confirmed pertussis among persons tested for pertussis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it