Developing a Cost-Effectiveness Model of Digital Therapeutics for Smoking Cessation
Sung Goo Yoo1, Dai Jin Kim1,2, Ji Won Chun1
1Department of Medical Informatics, College of Medicine, The Catholic University of Korea.
Studies in Health Technology and Informatics
|January 25, 2024
Summary
This study developed a Markov model for digital therapeutics (DTx) in Korean adult smokers. Nicotine replacement therapy (NRT) emerged as the dominant strategy, with DTx complementing pharmacotherapy as a cost-effective option.
Area of Science:
- Health Economics
- Digital Health
- Pharmacoeconomics
Background:
- Smoking remains a significant public health issue in Korea.
- Predicting the long-term economic impact of smoking cessation interventions is crucial.
- Digital therapeutics (DTx) offer novel approaches to behavior change and health management.
Purpose of the Study:
- To construct a Markov model to predict lifetime costs and consequences of smoking cessation in Korean adults.
- To evaluate the economic viability of digital therapeutics (DTx) as a smoking cessation strategy.
- To compare DTx with existing interventions like Nicotine Replacement Therapy (NRT).
Main Methods:
- Development of an annual cycle Markov model.
- Simulation of a hypothetical cohort of adult smokers in Korea attempting to quit.
- Analysis of lifetime costs and health consequences associated with different cessation strategies.
Main Results:
- The Markov model predicted lifetime costs and consequences for adult smokers in Korea.
- Nicotine Replacement Therapy (NRT) was identified as the dominant cost-effective strategy.
- Digital therapeutics (DTx) demonstrated potential as a complementary, low-cost addition to pharmacotherapy.
Conclusions:
- NRT is the leading strategy for smoking cessation in the modeled Korean population.
- Digital therapeutics (DTx) can serve as a valuable, cost-effective adjunct to pharmacotherapy for smoking cessation.
- Further research into the integration of DTx in public health strategies is warranted.
Keywords:
Cost-effectiveness analysisDigital therapeuticsMarkov chainMonte Carlo simulationsmoking cessationMore Related Videos
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