Modeling Disability-Adjusted Life-Years for Policy and Decision Analysis.

Area of Science:

• Health Economics
• Decision Science
• Epidemiology

Background:

• Disability-Adjusted Life-Years (DALYs) are crucial metrics in health economics and epidemiology.
• Accurate DALY estimation is vital for reliable cost-effectiveness analyses.
• Existing modeling approaches may lack flexibility or efficiency for practitioners.

Purpose of the Study:

• To introduce and validate two novel methods for modeling DALYs within standard decision-modeling frameworks.
• To provide practitioners with adaptable tools for estimating DALYs, Years of Life Lost (YLL), and Years Lived with Disability (YLD).
• To compare the accuracy of proposed methods against commonly used shortcut techniques.

Main Methods:

• Development of a beginner DALY modeling approach using Markov trace.
• Implementation of an intermediate DALY modeling approach incorporating non-Markovian elements into transition probability matrices.
• Validation using an existing discrete time Markov cohort model for disease progression.

Main Results:

• Both beginner and intermediate DALY modeling methods produced equivalent results.
• Demonstrated equivalence of DALY estimates and cost-effectiveness analysis outcomes across the proposed methods.
• Identified inaccuracies in commonly used shortcut methods for DALYs, impacting levels and incremental cost-effectiveness ratios.

Conclusions:

• The presented beginner and intermediate methods offer reliable and adaptable tools for DALY estimation in decision modeling.
• These methods can be extended to model other health outcomes like QALYs and life-years.
• Practitioners should exercise caution with shortcut DALY calculation methods due to potential inaccuracies.