Validity of Canadian discharge abstract data for hypertension and diabetes from 2002 to 2013
Bibliographic record
Abstract
BACKGROUND: Surveillance using coded administrative health data has shown that the prevalence of hypertension and diabetes in Canada increased substantially between 1998 to 2008. These findings require an assumption that the validity of hypertension and diabetes coding is stable over time. We tested this assumption by examining temporal trends in the validity of coding for hypertension and diabetes in the Canadian hospital Discharge Abstract Database. METHODS: We used the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH) database, a clinical registry, as the reference standard to evaluate the validity of the Discharge Abstract Database in recording hypertension and diabetes in Alberta. The APPROACH database contains data for all Alberta residents who have undergone cardiac catheterization and includes prospective ascertainment of comorbid conditions before each procedure. We linked patient data between the 2 databases for 2002 to 2013 using patient provincial health number. Temporal trends in sensitivity, specificity, positive predictive value, negative predictive value and Cohen κ were calculated for both hypertension and diabetes in the Discharge Abstract Database. RESULTS: We matched 63 483 patients between the APPROACH database and the Discharge Abstract Database. The validity of the Discharge Abstract Database for hypertension and diabetes remained mostly consistent over time. Between 2002 and 2013, sensitivity, specificity, positive predictive value and negative predictive value ranged from 66% to 87% for hypertension and from 81% to 98% for diabetes; the corresponding κ scores ranged from 0.50 to 0.62 and from 0.80 to 0.89. No significant differences in the validity of coding were found across age, sex or hospital location subgroups. INTERPRETATION: The validity of coding for hypertension and diabetes in the Discharge Abstract Database remained fairly consistent between 2002 and 2013. Our findings support the use of the Discharge Abstract Database for hypertension and diabetes surveillance in hospital settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".