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Record W4318539341 · doi:10.1093/ecco-jcc/jjac190.0981

P851 Impact of an integrated model of care for inflammatory bowel disease on direct healthcare costs: A population-based matched cohort study from Saskatchewan, Canada

2023· article· en· W4318539341 on OpenAlexaffabout
Fernando Maldonado, Erika Penz, John Verrier Jones, JN Peña-Sánchez

Bibliographic record

VenueJournal of Crohn s and Colitis · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsDalhousie UniversitySaskatchewan Health Quality CouncilUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineHealth careResidenceIndirect costsInflammatory bowel diseaseCohortPropensity score matchingCohort studyDisease burdenPopulationDiseaseDemographyEnvironmental healthEmergency medicineInternal medicine

Abstract

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Abstract Background Integrated models of care (IMC) for IBD lead to reduced hospitalizations, surgeries, comorbidities, and overall improved outcomes. There are limited studies assessing the impact of IMC on direct healthcare costs. We aimed to estimate the impact of exposure to an IMC on direct healthcare costs among individuals diagnosed with IBD. Methods We conducted a quasi-experimental difference-in-difference (DID) cost analysis using administrative health data from Saskatchewan, Canada. We included individuals ≥18 years old meeting a validated administrative IBD case definition between January 2009 and March 2015. IBD cases were classified as exposed or non-exposed to the Saskatchewan IMC and required to have three years of healthcare coverage after baseline (i.e., first visit with an IMC [exposed] or a non-IMC [non-exposed] gastroenterologist). The direct healthcare costs were derived from the administrative databases, adjusted to 2014/15 Canadian dollars, and categorized into hospitalizations, physician visits, and medication claim costs (i.e., immunomodulators [IMM], biologics [BIOL], aminosalicylates[5-ASA]). Propensity scores (PS) were calculated based on healthcare utilization and comorbidities in the 12 months before baseline. Cases (exposed) were matched 1:5 controls (non-exposed) based on PS and disease duration. DID estimators were determined for each cost category using mixed linear regression models including age, sex, disease type, and area of residence as covariables. Results In total, 2905 IBD cases were included in the study, 597 exposed and 2308 non-exposed individuals (Figure); the majority were females (52%), lived in urban areas (74%), and had Crohn’s Disease (61%). The mean age was 44.6 years (SD=15.5) and the average disease duration at baseline was 5.7 years (SD=5). In comparison to the non-exposed group, the costs of physician visits (IBD-related [DID= $-139, 95%CI -209 to -68], IBD-specific [DID=$-155, 95%CI -212 to -97], and specialty visits [DID=$-135, 95%CI -201 to -69]); and IMM dispensations (DID=$-18, 95%CI -35 to -2) were lower in the exposed group. Conversely, we identified higher total healthcare costs (DID=$1707, 95%CI 369 to 3044); IBD-related medication (DID=$2341, 95%CI 1484 to 3197) and BIOL (DID= $2467, 95%CI 1605 to 3328) dispensations costs in the exposed group. There were no other statistically significant differences between the groups. Conclusion We identified lower physician visit and IMM costs in the exposed group than in the non-exposed one. Total healthcare costs were higher among the exposed group, largely driven by higher BIOL costs. These results highlight the potential cost impact of IMC for IBD and the need for cost-effectiveness studies of IMC to further assess value of this care model.

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)0.005
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 score0.036
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.005
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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