Trends in paediatric inflammatory bowel disease‐attributable direct costs: a population‐based analysis
Bibliographic record
Abstract
BACKGROUND: In addition to its morbidities, inflammatory bowel disease (IBD) has a major financial burden on patients and healthcare systems. However, there is a paucity of evidence on IBD-attributable costs in children. AIMS: To determine the trends of IBD-attributable direct costs over time using a population-based analysis. METHODS: Data were extracted from Manitoba Health Provider Claims and other population registry datasets from 1995 to 2017. Children with IBD were matched by age, sex and location with children without IBD. IBD-attributable direct costs were calculated using utilization counts from the administrative data and cost estimates from different sources. Inpatient hospitalisation and outpatient procedure costs were estimated using the resource intensity weight (RIW) that is attached to each record in the data. Costs were expressed in Canadian dollars. RESULTS: We included 733 (428 with Crohn's disease) prevalent cases who were diagnosed with IBD before the age of 18 years and were followed for 2450 person-years. A matched control group of 6763 persons who were followed for 21 558 person-years was included. The median annual costs of physician services billed per patient increased from $381 (IQR 215-1064) in 1995 to $936 (IQR 579-1932) in 2017 (P < 0.001). The annual medication costs per patient increased from a median of $270 in 1995 to $7944 in 2017 (P < 0.0001). The median annual direct cost per patient was $1810 in 2004 as compared to $14 791 (P < 0.0001) in 2017. CONCLUSIONS: Over two decades, there was a significant increase in the paediatric IBD-attributable direct costs mainly driven by medication costs.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".