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Record W2999602252 · doi:10.1093/ecco-jcc/jjz203.899

P771 Increasing prevalence and direct health care cost of inflammatory bowel disease: A population-based evidence from a western Canadian province

2020· article· en· W2999602252 on OpenAlexaffabout
Jessica Amankwah Osei, Juan Nicolás Peña-Sánchez, Sharyle Fowler, Nazeem Muhajarine, Gilaad G. Kaplan, Lisa M. Lix

Bibliographic record

VenueJournal of Crohn s and Colitis · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of ManitobaUniversity of CalgaryUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseHealth careIndirect costsPopulationEpidemiologyEnvironmental healthComorbidityDemographyActivity-based costingCohortDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background More than 0.3% of the populations in Europe, North America, and Oceania live with inflammatory bowel disease (IBD). Canada has increasing prevalence trends of IBD with 1% of Canadians estimated to have IBD by 2030. Evidence about IBD prevalence and health care costs over time can contribute to health resources allocation and health care planning. Our study aimed to 1) estimate the prevalence and direct health care costs of IBD in the province of Saskatchewan (SK), Canada, and 2) test if trends in the prevalence and direct health care costs of IBD increased over two decades. Methods We conducted a retrospective population-based cohort study using administrative health data of SK between 1999/00 and 2016/17 fiscal years. A validated case definition was used to identify prevalent IBD cases. The costing method adopted by the Canadian Institute for Health Information was used to estimate direct health care costs in 2013/14 Canadian dollars among IBD cases. Generalised linear models (GLMs) with generalised estimating equations were used to test the trends. Negative binomial and gamma distributions were used to, respectively, model prevalence and health care cost trends. Sex and age group were covariates in all models; the Charlson comorbidity index was also included in the cost model. Annual prevalence rates and direct health care cost estimates with their 95% confidence intervals (95%CI) were reported. Results In 2016, there were 6468 (Crohn’s disease: 3663 [56.63%], ulcerative colitis: 2805 [43.37%]) IBD cases ascertained in SK. The number of prevalent cases increased over the analysis period by 56%. The total direct health care costs increased from $7.8 million in 1999 to $50.8 million in 2016. The average annual IBD prevalence increased from 341/100,000 (95%CI 340–341) in 1999 to 664/100,000 (95%CI 663–665) in 2016, a 3.3% (95%CI 2.4–4.3) average annual increase. The total average annual direct health care costs of IBD increased from $1.8 (95%CI $1.6–2.0) thousand per patient in 1999 to $7.1 (95%CI $6.7–7.5) thousand per patient in 2016, an average annual increase of 9.2% (95% CI 8.5–9.8), Figure 1. Conclusion In the Canadian province of SK, prevalence and direct health care costs, respectively, tripled and quadrupled over two decades. Our results provide relevant information and analysis on the burden of IBD in SK. These findings are in agreement with previous studies from other provinces. The evidence of constant increasing prevalence and health care cost trends of IBD needs to be recognised by health care decision-makers to promote cost-effective health care policies at provincial and national levels and respond to the needs of patients living with IBD.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0050.014
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.009
GPT teacher head0.246
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations2
Published2020
Admission routes2
Has abstractyes

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