Validation of a Model Estimating the Budget Impact of Video Capsule Endoscopy for Surveillance of Crohn’s Disease in an Italian Center

Author:

Saunders Rhodri1,Calabrese Carlo23,Gelli Dania23,Davis Jason1,Torrejon Torres Rafael1

Affiliation:

1. Coreva Scientific GmbH, Königswinter, Germany

2. IRCCS, Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy

3. Università di Bologna, Bologna, Italy

Abstract

Background: Crohn’s disease is a chronic ailment affecting the gastrointestinal tract. Mucosal healing, a marker of reduced disease activity, is currently assessed in the colonic sections using ileocolonoscopy and magnetic resonance enteroscopy. Video capsule endoscopy (VCE) offers visualization of the entire GI mucosae. Objective: To validate a Crohn’s disease model estimating the budget impact of VCE compared with the standard of care (SOC) in Italy. Methods: A patient-level, discrete-event simulation was developed to estimate the budget impact of VCE compared with SOC for Crohn’s disease surveillance over 5 years in the Italian setting. Input data were sourced from a physician-initiated study from Sant’Orsola-Malpighi Hospital in Bologna, Italy, and the literature. The care pathway followed hospital clinical practice. Comparators were the current SOC (ileocolonoscopy, with or without magnetic resonance enteroscopy) and VCE. Sensitivity analysis was performed using 500-patient bootstraps. A comparative analysis regarding clinical outcomes (biologics use, surgical interventions, symptom remission) was performed to explore the validity of the model compared with real-world data. Cumulative event incidences were compared annually and semi-annually. Bayesian statistical analysis further validated the model. Results: Implementing VCE yielded an estimated €67 savings per patient per year, with savings in over 55% of patients, compared with SOC. While annual costs are higher up to the second year, VCE becomes cost saving from the third year onward. The real-world validation analysis proved a good agreement between the model and real-world patient records. The highest agreement was found for biologics, where Bayesian analysis estimated an 80.4% probability (95% CI: 72.2%-87.5%) that a decision maker would accept the result as an actual reflection of real-world data. Even where trend data diverged (eg, for surgery [43.1% likelihood of acceptance, 95% CI: 33.7%-52.8%]), the cumulative surgery count over 5 years was within the margin of error of the real-world data. Conclusions: Implementing VCE in the surveillance of patients with Crohn’s disease and small bowel involvement may be cost saving in Italy. The congruence between model predictions and real-world patient records supports using this discrete-event simulation to inform healthcare decisions.

Publisher

The Journal of Health Economics and Outcomes Research

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