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Annual cost of care for Crohn's disease: a payor perspective

2000· article· en· W2015052479 on OpenAlexaff
Brian G. Feagan, Mary Glenn Vreeland, Leanne R. Larson, Mohan Bala

Bibliographic record

VenueThe American Journal of Gastroenterology · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineCrohn's diseaseReimbursementInternal medicineDiseaseCrohn diseaseHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to estimate the annual cost of care of patients with Crohn's disease according to treatment setting. METHODS: Using a 1994 integrated claims database, patients with a Crohn's-related medical claim (ICD-9 code 555) from 10/01/94 to 09/30/95 were included in this analysis. These patients were stratified into three mutually exclusive disease severity groups: group 1, required hospitalization for Crohn's; group 2, required chronic glucocorticoid or immunosuppressive drug therapy for >6 months; group 3, all remaining patients. Direct charges (based on reimbursement) and utilization of resources were reported for each group. RESULTS: Six-hundred-seven patients were analyzed: 117(19%) in group 1, 31(5%) in group 2, and 459(76%) in group 3. Average age of all patients was 48 years and 43% of these patients were men. Average annual charges for all patients totaled $12,417. Group I patients experienced the highest mean charges ($37,135), whereas patients in groups 2 and 3 incurred $10,033 and $6,277. Approximately 25% of patients accounted for 80% of the total charges. CONCLUSIONS: Crohn's disease is associated with high cost. Although a minority of Crohn's patients required hospitalization, they tended to have higher utilization and were responsible for a majority of total expenditures. New therapies have the potential to reduce overall cost of care, if they prevent Crohn's-related hospitalizations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.246
Teacher spread0.243 · 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 teacher head, 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

Citations192
Published2000
Admission routes1
Has abstractyes

Explore more

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