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Record W4236201390 · doi:10.1093/jcag/gwz006.000

A1 LONGITUDINAL CHANGES IN THE DIRECT COST OF IBD CARE IN THE BIOLOGIC ERA

2019· article· en· W4236201390 on OpenAlexaffabout
Laura E. Targownik, Julia Witt, C N Bernstein, H Singh, Antonio Aviña Zubieta, Eric I. Benchimol, Stephanie Coward, Jennifer Jones, Gilaad G. Kaplan, Sanjay K. Murthy, G C Nguyen, Juan Nicolás Peña-Sánchez, Seth R. Shaffer, Aruni Tennakoon

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of SaskatchewanUniversity of TorontoMount Sinai HospitalUniversity of OttawaRoyal University HospitalChildren's Hospital of Eastern OntarioUniversity of CalgaryArthritis Research Centre of CanadaOttawa HospitalUniversity of Manitoba
Fundersnot available
KeywordsMedicineIndirect costsHealth careMedical prescriptionPer capitaPopulationEnvironmental healthPopulation healthEpidemiologyHealth economicsInpatient careEmergency medicinePublic healthInternal medicine

Abstract

fetched live from OpenAlex

While biologics are significantly costlier than other medical options for IBD, their use may lead to a diminution in downstream health care costs by decreasing the need for hospitalization and surgeries for uncontrolled symptoms or complications. Previously published work from Manitoba has shown that the prevalence of anti-TNF use has been increasing over time, but the impact of this increased penetrance of anti-TNF use on downstream costs is not well described across the population of IBD. We sought to assess the direct costs of care among a population of Canadians with IBD between 2004–2016 We used the Manitoba IBD Epidemiology Database, which contains health care utilization data for all Manitobans diagnosed with IBD from 1984–2016, and all prescription medication since 1996, and direct costs associated with health care utilization since 2004. For every year between 2004 and 2016, we summed all costs of health care utilized by persons with IBD, and separated these costs into inpatient, outpatient,and anti-TNF medications, and determined the per capita cost per year. All costs were standardized to 2015 Canadian dollars. Univariate linear regression analysis was used to determine if there are significant changes in the direct costs of care over time. The year by year direct health care expenditure for CD, UC, and IBD are shown in the Figure. Between 2004 and 2016, the mean annual costs of care for persons with IBD increased from $5,648 to $10,232, with an average increase of $447 per year (95%CI: $393-$501) The annual cost for CD increased from $6,549 to $13,373 (annual increase $638, 95%CI $557-$716), whereas the mean cost per year for persons with UC rose from $4,753 to $7,320 (annual increase $276; 95%CI: $222–330) Mean inpatient costs decreased by $104 per year for CD (95%CI: $59-$109), but did not change over time with UC (mean annual change -$11 (95%CI -$57 - +$35). Mean annual per capita outpatient costs (excluding the cost of anti-TNF therapy) has remained stable over the time period, for CD and UC. Discussion: The direct costs of IBD have markedly increased between 2005 and 2015, and the increase can be nearly completely ascribed to the increasing use of anti-TNF medications. Despite the increased penetrance of anti-TNF use into practice, there has been only a relatively small impact on the amount per capita spent on hospitalizations, and only in CD. The failure of anti-TNF medication use to significantly impact the direct costs of care represents a gap between the demonstrated efficacy of these medications and their real-world effectiveness. This suggests that there exist opportunities to further optimize our use of anti-TNF medication in clinical practice CCCJanssen Canada

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)0.001
metaresearch head score (Gemma)0.007
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 score0.821
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.116
GPT teacher head0.341
Teacher spread0.225 · 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
Published2019
Admission routes2
Has abstractyes

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