Abstract

Objectives

Bariatric surgery is an important therapy for managing obesity; however, most low- and middle-income countries have more eligible patients than the healthcare system can accommodate. Despite ample literature about its effectiveness, as well as many economic studies comparing it with other interventions, decision-analytic studies on which patients should be prioritized for the procedure are lacking. A predictive scoring system to anticipate success after surgery grounded in clinical parameters observed before the procedure was previously proposed; here, we aim to assess its cost-effectiveness when compared with the current paradigm of directing the patients to a reference center based on a simple queue, the “first in, first out” approach.

Methods

We developed a Monte Carlo microsimulation branching model in RStudio, to assess costs and quality-adjusted life-years, across 6 different supply constraints, comparing a simulated cohort undergoing surgery based on their predictive success scores with another group undergoing surgery according to their position within a straightforward queue. The analysis adopted the perspective of the Brazilian National Health System, with a monthly cycle duration, with a 5% annual discount rate.

Results

Across all analyzed scenarios, the incremental cost-effectiveness ratio of using the success score over performing surgery via queue ranged from R$227 to R$2883 ($45 to $579 in the current exchange rate), falling well below commonly used willingness-to-pay thresholds. The cohorts prioritized by the score had longer total life-years, less cardiovascular mortality, and slightly higher costs associated with surgical procedures and management of chronic illnesses.

Conclusions

Prioritizing patients based on predicted success is a promising strategy to improve health outcomes at an affordable cost, across different levels of supply constraints.