Introduction to Economic Evaluation - Key Terms (Week 1)

Course Context & Terminology.

• Key concentric relationship diagram shown:

  • Economics → Health Economics → Economic Evaluation.

• Early warning: “Not all decisions are this easy – ‘Right way vs Wrong way’” – stresses complexity of real-world resource allocation.

The Need for Economic Evaluation

• Premise: Health-care resources are scarce; budgets are fixed or tightly constrained.

• Aim: Maximise total health (or welfare) generated from available resources.

• Economic evaluation supplies a systematic & explicit method for comparing costs and benefits of alternative actions.

• Used in two broad decision arenas:

  • Health Technology Appraisal (HTA): case-by-case "yes/no" funding decisions.

  • Priority setting / league tables: choices across programmes.

Scarcity, Opportunity Cost & Fixed Budgets

• Medicare and similar schemes operate under a finite budget – "not an endless pot of money".

• Opportunity cost:

  • Resources spent on X (e.g.
    heart transplants) forego benefits of the next-best alternative Y (e.g.
    hip replacements).

  • Formal definition: benefits forgone by not allocating resources to the best alternative use.

• Goal under a fixed budget: maximise health across all disease areas; interventions must justify their displacement costs.

Evidence on Variability in Value for Money

• Tengs et al. (1994): Reviewed 500 life-saving interventions – found orders-of-magnitude variation in cost per life-year saved.

  • Highlighted potential to save more lives by reallocating funds from poor-value to good-value interventions.

• Strategic Review of Australian Health & Medical Research (McKeon Review, 2013) – emphasised that health outcomes depend on productivity & cost-effectiveness of interventions.

Theoretical Foundations of Economic Evaluation

• Welfarism (Welfare Economics):

  • Social welfare = sum of individual utilities (consumer sovereignty).

  • Prioritise individual preferences; autonomy is key.

• Extra-Welfarism:

  • Supplements utility with socially important outcomes (e.g.
    health, equity).

  • Recognises merit goods – the government may supply above market level for social justice.

Key Economic Concepts Introduced

• Benefit: What the decision-maker tries to maximise (health, utility, equity, etc.).

• Scarcity, Choice, Opportunity Cost.

• Allocative vs Technical efficiency (see dedicated heading below).

• Incremental & Marginal analysis (distinction emphasised later).

Incremental Analysis & the ICER

Incremental analysis: comparing the costs and outcomes of different interventions to determine the additional benefits provided by one option over another.

• Central question: Are incremental benefits worth incremental costs?

• Incremental Cost-Effectiveness Ratio (ICER):

  ICER = Cost of new treatment – Cost of standard treatment (comparator) / Effect of new treatment – Effect of standard treatment (comparator).

  This ratio helps in determining the value of a new intervention relative to existing options.

• Plotted on the cost-effectiveness plane (NE, NW, SE, SW quadrants):

  • NE: More effective & more costly.

  • SE: More effective & less costly – dominant.

  • NW: Less effective & more costly – dominated.

  • SW: Less effective & less costly.

    

  • Cost-effectiveness analysis: A method to compare the relative costs and outcomes of different interventions, helping to determine the most efficient option.

• ICER is a ratio; magnitude alone doesn’t decide: (20/0.001) = (20{,}000/1) = (2{,}000{,}000/100) all equal

• \$20{,}000\text{ per life-year} despite huge numerator/denominator differences.

• Life year: a measure used to quantify the value of health outcomes, representing one year of life gained through a specific intervention.

Decision Rules for Cost-Effectiveness Analysis

• Recommend if new intervention dominates (better outcomes, lower cost).

• Reject if dominated.

• For NE & SW quadrants:

  • Compare ICER to a willingness-to-pay (WTP) threshold / ceiling ratio.

  • Or use league tables ranking interventions by ICER.

• willingness-to-pay (WTP) threshold: the maximum amount a decision-maker is willing to pay for an additional unit of health benefit, often expressed as a cost per quality-adjusted life year (QALY).

• ceiling ratio: the highest value of ICER that is acceptable for intervention funding, which helps to guide resource allocation decisions in healthcare.

Types of Economic Evaluation

• Not economic evaluation: Cost (burden) of illness studies – describe economic impact of a disease but do not compare alternatives.

Marginal vs Incremental Analysis

• Marginal analysis: Very small change within same programme – compares marginal cost MC with marginal benefit MB.

  • e.g.
    cost per extra mammography in existing screening service.

• Incremental analysis: Substituting / adding a different programme.

  • e.g.
    expanding screening to younger age cohort.

• Note: Marginal or incremental costs ≠ average cost.

Technical vs Allocative Efficiency

• Technical efficiency – "doing things right": Achieving a given objective with minimal resources.

  • Example questions: Day surgery vs inpatient stay for tonsillectomy; local vs hospital asthma clinics.

• Allocative efficiency – "doing the right things": Choosing the mix of programmes that maximises social welfare given opportunity costs.

  • Example questions: Should government subsidise breastfeeding incentives or expanded tram line vs asthma services?

Selecting Outcome Measures for CEA

• Desired properties of a natural unit:

  1. Closely linked to meaningful health outcome (e.g.
     life-years, cases detected).

  2. Interval scale – equal unit change => equal health change regardless of baseline.

  3. Understandable to decision-makers & allows cross-study comparison.

• Examples:

  • \frac{\$}{LY\;gained} for renal failure therapies.

  • \frac{\$}{\text{Down’s syndrome foetus detected}} for screening options.

• Quality-of-Life (QoL) instruments (Karnofsky, SF-36):

  • Multi-domain, patient-reported.

  • Lack interval properties, ambiguous if some domains improve while others worsen.

  • Advantage: reflect patient experience;

  • Disadvantage: limited for allocative efficiency.

Cost-Utility Analysis (CUA)

• Specialised CEA where outcome = utility-weighted life expectancy.

• Common measures:

  • Quality-Adjusted Life Years (QALYs).

  • Disability-Adjusted Life Years (DALYs).

  • Healthy-Year Equivalents (HYEs).

• Utility scale: 0 = dead (QALY) or perfect health (DALY); 1 = perfect health (QALY) or dead (DALY); states <0 possible (worse than dead).

• Computation example:

  • No operation: utility 0.5 × 2 years = 1.0 QALY.

  • Operation: utility 0.9 × 5 years = 4.5 QALYs.

  • Gain: \Delta QALY = 3.5.

• Broad rule: DALYs averted ≈ QALYs gained (opposite orientation of scale).

Why QALYs Are Popular

• Combine length & quality of life; include preference weights.

• Interval-scaled, so valid arithmetic operations.

• Enable comparison across all disease areas → suitable for allocative efficiency.

• Convenient for modelling & threshold-based decision rules.

Caveats

• May be insensitive to subtle but important changes.

• Deriving utilities (e.g.
  TTO, SG, EQ-5D mapping) poses methodological challenges.

• Linking to intermediate public-health outputs (e.g.
  reduced smoking prevalence) not always straightforward.

Cost-Benefit Analysis (CBA)

• Targets allocative efficiency across health & non-health sectors.

• Values all incremental benefits in monetary terms, then computes Net Social Benefit (NSB):

  NSB = \Delta Benefits\;-(minus)\;\Delta Costs

  • If NSB > 0$$ → intervention considered cost-effective.

• Monetary valuation approaches:

  1. Human-Capital: future wages / productivity lost or gained.

  2. Revealed Preferences: market behaviour proxies (risk wage premiums, car safety spending).

  3. Stated Preferences: willingness-to-pay (WTP) surveys, contingent valuation.

Challenges

• Ethical & equity issues (e.g.
  valuing life of lower-income individuals less?).

• Non-market & unpaid work hard to price.

• Gender pay gap example (ABS 2018) shows wage-based valuations can embed systemic inequities.

Budget Impact Analysis (BIA)

• Distinct from cost-effectiveness: focuses on affordability for a specific budget holder over 3-6 years; usually no discounting.

• Can accompany CEA when an intervention is cost-effective but high-cost (e.g.
  hepatitis C drug sofosbuvir).

• Common modelling elements:

  • Population size & eligibility.

  • Uptake speed/market share.

  • Resource use changes (drug units, monitoring, displaced treatments).

  • Counterfactual (world without intervention).

• PBAC (Australia) requires 6-year BIA with epidemiological or market-share approaches; includes uncertainty & Quality Use of Medicines plans.

Multidisciplinary Expertise Needed

• Economics, epidemiology, disease modelling, biostatistics, systematic review & meta-analysis, clinical sciences (medicine, pharmacy), medical technology, implementation science, patient-level outcome research.

Session Aims & Learning Objectives Recap

• Describe main techniques & foundations of economic evaluation.

• Define key terms: CEA, CUA, QALY, DALY, CBA, CMA, CCA, ICER, HTA, Budget Impact, etc.

• Distinguish allocative vs technical efficiency; apply incremental reasoning.

• Understand the scope of economic evaluation in guiding public-health & health-care decisions.

Week 1 Take-Home Messages

• Economic evaluation = comparative analysis of costs & consequences to aid policy choice.

• Scarcity implies opportunity cost; efficiency requires weighing marginal/incremental trade-offs.

• Different evaluation types suit different questions; CEA/CUA dominate clinical technology decisions, CBA more for broad public-health or cross-sector choices.

• ICER & thresholds underpin many HTA bodies’ decisions (e.g.
  PBAC, MSAC).

• Affordability concerns captured by Budget Impact Analysis.

• Methodological rigour matters, but the economic way of thinking—explicit comparison, transparency, opportunity cost—remains the essential contribution to decision-making.