Comparing Health Administrative and Clinical Registry Data: Trends in Incidence and Prevalence of Pediatric Inflammatory Bowel Disease in British Columbia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Canada maintains robust health administrative databases and British Columbia Children's Hospital (BCCH), as the only tertiary care pediatric hospital in British Columbia (BC), maintains a comprehensive clinical inflammatory bowel disease (IBD) registry. To evaluate the strengths and weaknesses of utilizing health administrative and clinical registry data to study the epidemiology of IBD in BC, we conducted a population-based retrospective cohort study of all children <18 years of age who were diagnosed with IBD between 1996 and 2008 in BC. METHODS: IBD cases from health administrative data were identified using a combination of IBD-coded physician encounters and hospitalizations while a separate IBD cohort was identified from the BCCH clinical registry data. Age and gender standardized incidence and prevalence rates were fitted to Poisson regression models. RESULTS: The overall incidence of pediatric IBD identified in health administrative data increased from 7.1 (95% CI 5.5-9.2) in 1996 to 10.3 (95% CI 8.2-12.7) per 100,000 children in 2008. Similarly, the incidence of the BCCH cohort increased from 4.3 (95% CI 3.0-6.0) to 9.7 (95% CI 7.6-12.1) per 100,000. Children aged 10-17 had the highest rise in incidence in both data sources; however, the administrative data identified significantly more 10-17-year-olds and significantly less 6-9-year-olds (p<0.05) compared to clinical registry data. CONCLUSION: While the application of both health administrative and clinical registry data demonstrates that the incidence of IBD is increasing in BC, we identify strengths and limitations to both and suggest that the utilization of either data source requires unique considerations that mitigate misclassification biases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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