Disability-Adjusted Life Years

Learning Objectives

01

Today: Background on DALY health outcomes

02

Friday: Tips and tricks for modeling DALYs in Amua

Overview of DALY Outcomes

01

Summary

  • DALYs not as frequently used in HTAs or CEAs.
  • Used for resource allocation in LMICs, but with sparse methodological guidance.

Common Outcomes

  1. Occupancy-based payoffs:
  • Utility/DALY weight applied for a time period / step.
  • Treatment/disease cost per time period / step.
  1. Transition-based payoffs:
  • One-time event-based cost (e.g., disease-related death, initial Dx, etc.).
  • One-time health outcome (e.g., years of life lost to premature mortality)

Disability-Adjusted Life Years (DALYs)

  • Reflect both occupancy- and transition-based payoffs.
  • There’s also very little guidance on how to structure a decision model for DALY outcomes.
  • We’ll show you how this week!

DALYs

  • Origin story: Global Burden of Disease Study

  • Deliberately a measure of health, not welfare/utility

  • Similar to QALYs, two dimensions of interest:

    • Length of life (differences in life expectancy)

    • Quality of life (measured by disability weight)

DALYs

DALYs = YLL + YLD

  • YLL (Years of Life Lost)
  • YLD (Years Lived with Disability)

Years of Life Lost to Disease

For a given condition c,

YLD(c) = D_c \cdot L_c

  • D_c is the condition’s disability weight
  • L_c is the time lived with the disease.

Years of Life Lost to Premature Mortality

Years of Life Lost to Premature Mortality

  • YLL are defined by by a “loss function.”
  • Drawn from a reference life table, indicating remaining life expectancy at age a.
  • YLL(a)= Ex(a)

Life Expectancy & YLL

  • Contextual Choices: Remaining life expectancy values may vary by research context (Anand and Reddy 2019).
  • Historical Method: GBD uses an exogenous life table approximating maximum human lifespan.
  • Alternatives: Endogenous tables or models may be preferred in certain cases.

Exogenous vs. Endogenous Life Tables

  • Distinction: Source of life expectancy values (external vs. internal).
  • Exogenous: Independent mortality risks, using GBD’s reference table.
  • Endogenous: Specific to the population’s mortality risks and health states.

DALYs

DALY(c,a) = YLD(c) + YLL(a)

Evolution of DALY Calculations

  • Historical Practice: Initial GBD studies applied age-weighting and 3% annual time discounting.
  • Changes Post-2010: Discontinuation of these practices for a more descriptive DALY measure.

Current Discounting Practices

  • WHO-CHOICE: Time discounting of health outcomes.

Key Takeaways

Modeling Without Discounting

  • Modeling DALYs in Amua is straightforward if you don’t use discounting.
    • For YLDs, use disability weight like you would a utility weight.
    • For YLLs, use one-time “cost” of remaining life expectancy.
      • YLL = tbl_reference_life_table[initial_age + t, 1]

Key Takeaways

Modeling With Discounting

  • But if you do need to discount …
    • You’re going to see some math expressions that take care of discounting for YLL outcomes.
    • This math adds some complexity but not much insight, so we won’t belabor it in slides.
    • We’ll provide you the formulas to use here and in the .amua model file on Friday.

Thanks!

References

Anand, Sudhir, and Sanjay G. Reddy. 2019. “The Construction of the DALY: Implications and Anomalies.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3451311.
Fox-Rushby, Ja, and K Hanson. 2001. “Calculating and Presenting Disability Adjusted Life Years (DALYs) in Cost-Effectiveness Analysis.” Health Policy and Planning 16 (3): 326–31. https://doi.org/10.1093/heapol/16.3.326.
Larson, Bruce A. 2013. “Calculating Disability-Adjusted-Life-Years Lost (DALYs) in Discrete-Time.” Cost Effectiveness and Resource Allocation 11 (1): 1–6.
Sassi, Franco. 2006. “Calculating QALYs, Comparing QALY and DALY Calculations.” Health Policy and Planning 21 (5): 402–8.