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Record W2587513965 · doi:10.1093/ecco-jcc/jjx002.849

P725 The impact of an integrated model of care for patients with inflammatory bowel disease in Canada

2017· article· en· W2587513965 on OpenAlexaffabout
Juan Nicolás Peña-Sánchez, Lisa M. Lix, Gary Teare, W. Li, Sharyle Fowler, Jennifer Jones

Bibliographic record

VenueJournal of Crohn s and Colitis · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsDalhousie UniversitySaskatchewan Health Quality CouncilUniversity of ManitobaUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineInflammatory bowel diseasePropensity score matchingHazard ratioUlcerative colitisInternal medicineConfidence intervalLogistic regressionProportional hazards modelRetrospective cohort studyPopulationCohortHealth careEmergency medicineDiseaseEnvironmental health

Abstract

fetched live from OpenAlex

Background: Integrated models of care (IMC) for inflammatory bowel disease (IBD) have been implemented to improve the quality of care and disease management, and reduce adverse outcomes. Studies providing a systematic assessment of the impact of IMC for IBD on health care utilization have not previously been undertaken. This study compared health care services and medication use for IBD patients who were and were not exposed to an IMC. Methods: A retrospective population-based cohort study was conducted between 2009 and 2015 using administrative health data for the province of Saskatchewan (SK), Canada. The SK IMC for IBD (the Multidisciplinary IBD Clinic—MDIBDC) was introduced in 2009. Patients with IBD were identified with a validated administrative case definition applied to hospital and physician billing records. The criteria for measuring exposure to the IMC included baseline and follow-up visits with MDIBDC physicians. Cox proportional hazard regression models with propensity-score matching were used to test for differences in IBD-related hospitalizations, surgeries, and medications use (5-aminosalicylic acid—5-ASA, immune modulator—IM, and biologics) between patients with and without MDIBDC exposure. Adjusted hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated. Conditional logistic regression was used to test for differences in the probability of corticosteroid dependency (CsD) over a 6-month period. Results: The study included 2312 IBD patients. In the sample, the mean age was 44.1 (SD=15.8) years, 51.5% were women, 74.7% had urban residence, 39.6% had ulcerative colitis (UC), and 24.3% were defined as exposed. The exposed group had a lower rate of IBD-related surgeries (HR=0.72, 95% CI 0.57–0.91), higher rate of IM (HR=1.75, 95% CI 1.48–2.05), higher biologic use (HR=1.75, 95% CI 1.48–2.05), and lower 5-ASA use (HR=0.79, 95% CI 0.68–0.92) than the non-exposed group. Analyses stratified by disease type revealed a lower rate of IBD-related hospitalization in exposed UC patients (HR=0.71, 95% CI 0.53–0.94). The odds of CsD amongst patients with UC in the exposed group was 0.39 (95% CI 0.15–0.98) that of the non-exposed group. No significant differences in CsD were identified in the full group analysis. Conclusions: Differences in adverse disease outcomes between exposed and non-exposed patients reflect the improved quality of care provided within an IMC for IBD. Increased use of steroid-sparing maintenance therapies, specifically IM and biologics, is an indicator of improved access to IBD therapies, as is the lower CsD use amongst patients with UC. Integrated models can positively impact the health care outcomes of patients with IBD, and, subsequently, lead to effective use of health care resources.

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)0.012
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 score0.114
Threshold uncertainty score0.827

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0020.002
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 head0.004
GPT teacher head0.229
Teacher spread0.224 · 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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Citations0
Published2017
Admission routes2
Has abstractyes

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