QALY (Quality-Adjusted Life Year)

Formula

QALY = Years × Quality; Cost/QALY = Cost / QALYs Gained

## QALY Formulas **Basic QALY Calculation**: QALY = Years × Quality Weight **QALY with Changing Quality**: QALY = Σ(Years_i × Quality_i) for each period i **QALYs Gained**: Gained = QALY(intervention) - QALY(baseline) **Cost per QALY**: Cost/QALY = Intervention Cost / QALYs Gained **Incremental Cost-Effectiveness Ratio (ICER)**: ICER = (Cost_new - Cost_current) / (QALY_new - QALY_current) ## Why QALYs Combine Quality and Quantity The insight behind QALYs is that both longevity and quality matter for well-being. Living 10 years in severe pain may be worse than 5 years healthy. How do we compare? QALYs multiply years by quality, treating 0.5 quality as "half" a year of perfect health. This creates equivalencies: 2 years at 0.5 quality = 1 year at 1.0 quality = 4 years at 0.25 quality. All equal 1 QALY. Whether this equivalence matches reality is debatable, but it enables comparison. The cost-per-QALY threshold represents society's willingness to pay for health improvement. At $100,000/QALY threshold, society considers 1 QALY worth $100,000 investment. Interventions below threshold provide "good value"—more health per dollar than the threshold implies.

Worked Examples

Example 1: Joint Replacement Surgery

Problem:65-year-old with arthritis. Current quality: 0.6 (moderate pain/mobility issues). Life expectancy: 20 years. Hip replacement costs $40,000, expected to improve quality to 0.85 for 15 years.

Solution:Baseline (no surgery): QALY = 20 years × 0.6 quality = 12.0 QALYs With hip replacement: Years 1-15: 0.85 quality Years 16-20: 0.6 quality (assumed decline) QALY = (15 × 0.85) + (5 × 0.6) QALY = 12.75 + 3.0 = 15.75 QALYs QALY gained: 15.75 - 12.0 = 3.75 QALYs Cost per QALY: $40,000 / 3.75 = $10,667 per QALY Assessment: Well below $50,000 threshold Very cost-effective intervention Clear recommendation for coverage

Result:3.75 QALYs gained | $10,667 per QALY | Very cost-effective

Example 2: Expensive Cancer Drug

Problem:Stage 4 cancer patient. Current quality: 0.4 (significant symptoms). Life expectancy without treatment: 1 year. New drug costs $200,000, extends life 8 months at quality 0.5.

Solution:Baseline (no drug): QALY = 1 year × 0.4 quality = 0.4 QALYs With drug: Total time: 1 year + 8 months = 1.67 years Assume quality 0.5 for extended period, 0.4 for original expectancy QALY = (1 × 0.4) + (0.67 × 0.5) QALY = 0.4 + 0.33 = 0.73 QALYs QALY gained: 0.73 - 0.4 = 0.33 QALYs Cost per QALY: $200,000 / 0.33 = $606,060 per QALY Assessment: Far exceeds $150,000 threshold Not cost-effective by standard metrics May still be approved under end-of-life exceptions or patient advocacy

Result:0.33 QALYs gained | $606,060 per QALY | Not cost-effective by standard thresholds

Example 3: Preventive Intervention

Problem:Lifestyle program for diabetes prevention. Costs $5,000. Reduces diabetes risk by 50% over 10 years. Without intervention: 30% chance of diabetes (quality drops from 0.9 to 0.7). 25 years remaining life expectancy.

Solution:Baseline (no intervention): 70% chance: healthy = 25 × 0.9 = 22.5 QALYs 30% chance: diabetes at year 5 = (5 × 0.9) + (20 × 0.7) = 18.5 QALYs Expected: 0.7 × 22.5 + 0.3 × 18.5 = 15.75 + 5.55 = 21.3 QALYs With intervention (50% risk reduction → 15% chance): 85% healthy: 22.5 QALYs 15% diabetes: 18.5 QALYs Expected: 0.85 × 22.5 + 0.15 × 18.5 = 19.125 + 2.775 = 21.9 QALYs QALY gained: 21.9 - 21.3 = 0.6 QALYs Cost per QALY: $5,000 / 0.6 = $8,333 per QALY Assessment: Highly cost-effective prevention Even better if population-level

Result:0.6 QALYs gained | $8,333 per QALY | Highly cost-effective prevention

Frequently Asked Questions

What is a QALY?

Quality-Adjusted Life Year (QALY) combines quantity and quality of life into a single metric. 1 QALY = 1 year lived in perfect health. 0.5 QALY = 1 year at 50% quality OR 6 months at perfect health. Used to compare health interventions that affect both lifespan and quality of life.

How is quality of life measured for QALY?

Quality weights (0-1) come from standardized surveys: EQ-5D (mobility, self-care, activities, pain, anxiety), SF-6D, or HUI. Weights are derived from population preferences—how much of lifespan people would trade for better quality. 1.0 = perfect health, 0 = death, negative values = states worse than death.

What's a cost-effective QALY threshold?

Common thresholds: US typically $50,000-150,000 per QALY, UK's NICE uses £20,000-30,000 (~$25,000-38,000). These aren't absolute—orphan diseases, end-of-life care, and severity may justify higher costs. Below threshold = recommended, above = may still be approved with justification.

Why do economists use QALYs?

QALYs enable comparison across different health conditions and interventions. Comparing: cancer drug extending life 6 months vs hip replacement improving mobility 10 years requires common metric. QALYs capture both effects. Alternative: just count lives saved—but this ignores quality improvement interventions.

What are QALY limitations?

Limitations: 1) Assumes quality can be quantified, 2) May undervalue elderly (fewer years to gain), 3) Weights come from general public, not patients, 4) Doesn't capture non-health value (work, family), 5) Controversial for severe disabilities (some see as discriminatory). DALYs are alternative metric.

What's the difference between QALY and DALY?

QALY measures health gained (more is better). DALY (Disability-Adjusted Life Year) measures health lost (fewer is better). DALYs = Years of Life Lost + Years Lived with Disability. WHO uses DALYs for global burden of disease. Both serve similar purposes with opposite framing.

Can QALYs be negative?

Quality weights can be negative for states considered worse than death (severe pain, complete dependence, certain dementias). Survey respondents indicate they'd prefer death to living in such states. Negative weights are controversial—who decides what's worse than death?

How do you estimate quality weights?

Methods: 1) Standard Gamble—choose between certain health state vs gamble on perfect health/death, 2) Time Trade-Off—years in poor health you'd trade for fewer in perfect health, 3) EQ-5D survey—standardized questionnaire mapped to weights. Clinical trials often use EQ-5D.

Should individuals use QALYs for personal decisions?

Cautiously. QALYs help structure thinking about trade-offs (quality vs quantity of life). But personal values differ from population averages—your quality weight may differ from surveys. For personal decisions, consider your own preferences, not just QALY calculations.

Why is QALY controversial?

Critics argue: 1) Puts dollar value on life, 2) May discriminate against disabled/elderly (fewer QALYs to gain), 3) Quality is subjective—who decides?, 4) Ignores patient preferences for their specific situation. Defenders: resource allocation requires some framework, QALYs are transparent about trade-offs.

Background & Theory

## Concept Overview Quality-Adjusted Life Years (QALYs) combine longevity and quality of life into a single metric for comparing health interventions. One QALY equals one year of life in perfect health. A year at 80% quality equals 0.8 QALYs. This enables comparison across conditions: cancer treatments extending life vs arthritis treatments improving quality. Cost-per-QALY analysis divides intervention cost by QALYs gained to assess value. Lower cost-per-QALY means more health purchased per dollar. Thresholds (commonly $50,000-150,000 in US) guide coverage and pricing decisions. Below threshold suggests good value; above suggests poor value requiring justification. The framework enables explicit, transparent trade-offs in healthcare resource allocation. Rather than implicit rationing (wait times, physician discretion), QALY analysis makes trade-offs visible and debatable. Critics argue this reduces health decisions to economics; defenders argue explicit analysis is more fair than hidden rationing. ## Key Variables and Their Intuition **Years Remaining**: Life expectancy or time horizon for analysis. Longer horizons allow more QALYs to accumulate. Age affects this—interventions in younger patients may yield more QALYs simply due to longer remaining life. **Quality Weight (0-1)**: Health-related quality of life. 1.0 = perfect health, 0 = death. Measured via standardized instruments (EQ-5D). Weights below 0 exist for states considered worse than death (controversial). **Intervention Effect**: How treatment changes quality and/or duration. Some interventions extend life, others improve quality, many do both. Duration of effect matters—temporary relief yields fewer QALYs than lasting improvement. **Intervention Cost**: Total cost of treatment including: drug cost, administration, monitoring, side effect management. Should include full treatment course, not just first dose. ## Assumptions in QALY Analysis - Quality can be meaningfully quantified (0-1 scale) - Population preferences apply to individual patients - A QALY is a QALY regardless of who receives it - Future QALYs are worth same as present (or discounted consistently) - Side effects are captured in quality weights - Comparator (baseline) is well-defined ## Limitations and Edge Cases **Age Discrimination**: Younger patients have more years to gain QALYs, potentially biasing against elderly interventions. Countered by equal per-QALY valuation, but structural bias remains. **Disability Paradox**: People with disabilities often report higher quality than external observers predict. Using general population weights may undervalue interventions for disabled patients. **End-of-Life**: Society may value end-of-life care more than QALY calculations suggest. NICE has specific end-of-life criteria that allow higher cost-per-QALY for terminal patients. **Example Edge Case**: A 90-year-old with 2-year life expectancy might gain only 0.5 QALYs from treatment costing $100,000 ($200,000/QALY—not cost-effective). But many would argue elderly patients deserve treatment regardless of QALY calculus. ## Interpretation Guide **Baseline QALYs**: Expected quality-adjusted life without intervention. Baseline for comparison. **Intervention QALYs**: Expected quality-adjusted life with intervention. Higher is better. **QALYs Gained**: Difference between intervention and baseline. The "benefit" of treatment. **Cost per QALY**: Investment required for each QALY gained. Compare to thresholds for cost-effectiveness assessment. ## Practical Tips - **Consider multiple scenarios**: Optimistic, realistic, and pessimistic projections. - **Include all costs**: Not just drug cost—administration, monitoring, side effects. - **Use appropriate comparator**: Compare to current standard of care, not doing nothing. - **Discount future years**: Standard practice discounts future QALYs 3% per year. - **Sensitivity analysis**: How do results change with different assumptions? - **Consider non-QALY factors**: Equity, innovation, patient preferences matter beyond QALYs. ## Common Mistakes - **Ignoring quality for life extension**: A treatment adding 1 year at 0.3 quality = 0.3 QALYs, not 1.0. - **Using wrong comparator**: Comparing to placebo when standard treatment exists. - **Forgetting treatment duration**: 10-year drug course costs more than one-time procedure. - **Applying individual preferences as population weights**: Personal QALY differs from policy QALY. - **Treating threshold as absolute**: Context (severity, alternatives, equity) affects acceptable cost-per-QALY. - **Double-counting**: If quality weight already includes pain, don't add separate pain adjustment. ## When NOT to Use QALY Analysis - **For individual clinical decisions**: QALYs guide policy, not personal treatment choices where individual values differ. - **For non-health interventions**: Education, safety, environment require different metrics. - **When quality data is unavailable**: Garbage in, garbage out. - **For moral absolutes**: Some believe certain treatments (life-saving for children, rare diseases) shouldn't be subject to cost-effectiveness thresholds.

History

## Origins of Health Economics The QALY concept emerged from the need to compare different health interventions. Early cost-effectiveness analysis (1960s-70s) counted only lives saved or life-years gained, ignoring quality. This made it impossible to evaluate interventions that improved quality without extending life (pain relief, mobility aids). Weinstein and Stason formally introduced QALYs in a 1977 New England Journal of Medicine paper. They proposed combining quantity and quality into a single metric, enabling comparison across diverse health conditions and interventions. ## Development of Quality Weights Early quality weights were physician estimates—problematic because they differed from patient preferences. The 1980s-90s brought standardized instruments: EQ-5D (European), SF-6D (US), and HUI (Canadian). These survey-based tools capture patient-reported health status. The critical innovation was deriving weights from population preferences. Time Trade-Off and Standard Gamble methods asked representative samples: "How many years of healthy life equal X years in health state Y?" This grounded weights in societal values rather than expert opinion. ## Policy Adoption The UK's National Institute for Health and Care Excellence (NICE), established 1999, pioneered systematic QALY-based assessment for drug coverage decisions. Their £20,000-30,000 per QALY threshold became influential globally. The US has been more reluctant—the Affordable Care Act initially prohibited Medicare from using QALYs. However, the Institute for Clinical and Economic Review (ICER) provides QALY-based assessments for the US market. Debate continues about appropriate thresholds and methodology. ## Common Historical Misconceptions - **"QALYs put a price on life"**: QALYs measure health gain, not life value. The threshold is for resource allocation, not valuing life. - **"Patients with disabilities are worth less"**: QALY measures change from intervention, not absolute value. A treatment improving disabled person's quality is equally valued per QALY. - **"Higher threshold always better"**: Higher thresholds fund more interventions but reduce overall health purchased per dollar. Trade-off exists. - **"QALYs are objective science"**: Quality weights reflect societal values, which are subjective and vary culturally. - **"One QALY always equals one QALY"**: Severity, rarity, and end-of-life context may justify different valuations in practice.