Budget Impact Analysis of Continuous Glucose Monitoring with Predictive Alarms for Type 1 Diabetes in Chile (T1D): Perspective of the Explicit Health Guarantees Regime.
Author(s)
Daniela Paredes, BSc, MPH1, JUAN VALENCIA, MSc, MD2, Matías Castro, MPhil3;
1Medtronic Chile, Health Economics & Reimbursement, Santiago, Chile, 2Medtronic, Miami, FL, USA, 3Medtronic Chile, Medical Science, Santiago, Chile
1Medtronic Chile, Health Economics & Reimbursement, Santiago, Chile, 2Medtronic, Miami, FL, USA, 3Medtronic Chile, Medical Science, Santiago, Chile
OBJECTIVES: Continuous Glucose Monitoring (CGM) is recommended as the standard of care in T1D. In Chile, this technology is not covered by the Explicit Health Guarantees Regime (GES). This exploratory analysis compares the budget impact of two different CGM technologies with and without predictive alarms, currently accessible only through out-of-pocket expenditure. Predictive alarms have the potential to reduce metabolic dysregulations such as hypoglycemia and hyperglycemia.
METHODS: Employing the six-step Budget Impact Analysis approach, we estimated the eligible population based on prevalence and incidence of Type 1 Diabetes (T1D) and active users of CGM or insulin pumps. No funneling-down technique was used since, according to international guidelines, all patients with T1D are eligible for a CGM device. We selected an annual time horizon with monthly cycles from the patient´s perspective, identified the current direct costs associated with CGM devices without predictive alarms (sensors, lancets, ketone, and glycemia test strips), and projected the treatment mix with the CGM system with predictive alarms (Guardian™ 4). We estimated the current and future CGM costs (2024 CLP), and annual budget impact changes. This analysis has not yet considered the effect of metabolic dysregulations.
RESULTS: A total adjusted demand for sensors of n=20,163 patients in the base year within the GES context was estimated. The impact of coverage of only CGM without predictive alarms resulted in an annual budget impact of 35.9 billion CLP, with an annual cost per patient of $1,778,736 CLP ($148,228 CLP monthly), primarily afforded by out-of-pocket expenditure. The budget impact of incorporating CGM with predictive alarms in the base year amounts to $39.2 billion CLP for the entire cohort, representing $1,944,000 CLP annually per patient and $162,000 CLP monthly (+9.29%).
CONCLUSIONS: Due to the benefit of predictive alarms in reducing hypo/hyperglycemia, future analysis needs to demonstrate that the additional +9.29% are offset by better metabolic control.
METHODS: Employing the six-step Budget Impact Analysis approach, we estimated the eligible population based on prevalence and incidence of Type 1 Diabetes (T1D) and active users of CGM or insulin pumps. No funneling-down technique was used since, according to international guidelines, all patients with T1D are eligible for a CGM device. We selected an annual time horizon with monthly cycles from the patient´s perspective, identified the current direct costs associated with CGM devices without predictive alarms (sensors, lancets, ketone, and glycemia test strips), and projected the treatment mix with the CGM system with predictive alarms (Guardian™ 4). We estimated the current and future CGM costs (2024 CLP), and annual budget impact changes. This analysis has not yet considered the effect of metabolic dysregulations.
RESULTS: A total adjusted demand for sensors of n=20,163 patients in the base year within the GES context was estimated. The impact of coverage of only CGM without predictive alarms resulted in an annual budget impact of 35.9 billion CLP, with an annual cost per patient of $1,778,736 CLP ($148,228 CLP monthly), primarily afforded by out-of-pocket expenditure. The budget impact of incorporating CGM with predictive alarms in the base year amounts to $39.2 billion CLP for the entire cohort, representing $1,944,000 CLP annually per patient and $162,000 CLP monthly (+9.29%).
CONCLUSIONS: Due to the benefit of predictive alarms in reducing hypo/hyperglycemia, future analysis needs to demonstrate that the additional +9.29% are offset by better metabolic control.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
MT29
Topic
Medical Technologies
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity)