Validity of Chronic Obstructive Pulmonary Disease Diagnoses in a Large Administrative Database
Bibliographic record
Abstract
BACKGROUND: Administrative databases are often used for research purposes, with minimal attention devoted to the validity of the included diagnoses. AIMS: To determine whether the principal diagnoses of chronic obstructive pulmonary disease (COPD) made in hospitalized patients and recorded in a large administrative database are valid. METHODS: The medical charts of 1221 patients hospitalized in 40 acute care centres in Quebec and discharged between April 1, 2003 and March 31, 2004, with a principal discharge diagnosis of COPD (International Classification of Diseases, Ninth Revision codes 491, 492 or 496) were reviewed. The diagnosis of COPD was independently adjudicated by two pulmonologists using clinical history (including smoking status) and spirometry. The primary outcome measure was the positive predictive value (PPV) of the database for the diagnosis of COPD (ie, the proportion of patients with an accurate diagnosis of COPD corroborated by clinical history and spirometry). RESULTS: The diagnosis of COPD was validated in 616 patients (PPV 50.4% [95% CI 47.7% to 53.3%]), with 372 patients (30.5%) classified as 'indeterminate'. Older age and female sex were associated with a lower probability of an accurate diagnosis of COPD. Hospitalization in a teaching institution was associated with a twofold increase in the probability of a correct diagnosis. CONCLUSIONS: The results support the routine ascertainment of the validity of diagnoses before using administrative databases in clinical and health services research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".