Health Care Resource Use and Costs for Crohn’s Disease before and after Infliximab Therapy
Bibliographic record
Abstract
BACKGROUND: Infliximab therapy in patients with Crohn's disease decreases resource use; however, the overall impact on health-related expenditures is unclear, especially beyond one year of study. METHODS: A retrospective analysis of economic data one and two years before and after infliximab therapy was performed using patients who served as their own controls. Total health care resource use and direct health care costs were compared for patients with or without fistulae. RESULTS: Patients with one (n=66) and two (n=39) years of economic data before and after infliximab treatment had their resource use and direct health care costs estimated. In the year following initiation of infliximab therapy, there were significant decreases in health care use, reflected in total hospital days (495 to 155 [P<0.05]), inpatient colonoscopies (46 to 24 [P<0.05]), outpatient colonoscopies (58 to 33 [P<0.05]) and major surgeries (10 to 2 [P<0.05]). Direct health care costs of inpatient costs for luminal (-$1,747 [P<0.05]) and fistulizing disease (-$2,530 [P<0.05]), major surgeries (-$1240 [P<0.05]) and outpatient colonoscopies (-$184 [P<0.05]) were also significantly reduced before and after infliximab therapy. Total direct health care costs, including the drug cost of infliximab, increased ($21,416 [P<0.05]). In general, the trends in health care costs analyzed over four consecutive years paralleled the two consecutive-year analysis. CONCLUSION: Infliximab therapy in patients with Crohn's disease resulted in a significant decrease in both resource use and health care costs, but an increase in total direct health care costs once the cost of infliximab was added.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".