Challenges in synthesising cost-effectiveness estimates The authors explain why conducting a meta-analysis in cost-effectiveness analyses is challenging due to significant heterogeneity among studies.

Heterogeneity - the main issue

• Variability or differences across studies, populations, methods, interventions, or outcomes in systematic reviews and meta-analyses.
• Meta-analysis: statistical technique used in systematic reviews to combine and analyze results from multiple independent studies.
• When studies are conducted in diverse national or regional contexts, it becomes challenging to combine their results into meaningful pooled numerical estimates.

Key factors

• Population heterogeneity: differences in patient characteristics and populations.
• Intervention and comparator variability: variations in treatments compared across studies.
• Structural and methodological heterogeneity: differences in modeling techniques, time horizons, discount rates, and analytical assumptions.
• Data collection methods: variations in the reliability, frequency, and methods of gathering data.
• Effectiveness evidence: variability in sources and generalisability of clinical effectiveness data.
• Health outcome measurement: inconsistencies in measuring quality-adjusted life years (QALYs) and other health outcomes.
• Cost and resource-use heterogeneity: differences in economic perspectives, cost calculation methods, currencies, and inflation adjustments.

Discount rates - "Costs and health outcomes that are predicted to occur in the future are usually valued less than present costs, and so it is recommended that they be discounted in analysis."