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A Role for Decision Analysis in PHIAC?. Mark Sculpher Centre for Health Economics University of York. Rationale for decision analysis Contrasting paradigms. Measurement Testing hypotheses about individual endpoints (parameters) Relatively few parameters of interest
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A Role for Decision Analysis in PHIAC? Mark Sculpher Centre for Health Economics University of York
Rationale for decision analysisContrasting paradigms • Measurement • Testing hypotheses about individual endpoints (parameters) • Relatively few parameters of interest • Primary role for trials and other primary data collection • Focus on parameter uncertainty • Decision making • What do we do now based on all sources of current knowledge? • Decision making involves synthesis • Decisions cannot be avoided • A decision is always taken under conditions of uncertainty • Can be based on implicit or explicit analysis
Outcome 1 Outcome 1 Outcome 2 Outcome 2 Outcome 1 Outcome 2 Key elements of decision analysis Expected value ValueA1 p1 (p1 x ValueA1) + (p2 x ValueA2) Option A ValueA2 p2 p3 ValueB1 Population Option B (p3 x ValueB1) + (p4 x ValueB2) ValueB2 p4 p5 ValueC1 Option C (p5 x ValueC1) + (p6 x ValueC2) ValueC2 p6
Key features of decision analysis • Quantitative • Explicit • Accepts role of judgements/assumptions • Helps to understand implications of uncertainty
Example – lead poisoning in children Brown MJ. Medical Decision Making 2002; 22: 482.
Key role for sensitivity analysis Brown MJ. Medical Decision Making 2002; 22: 482.
What would decision analysis require of PHIAC? • Absolute clarity about the appropriate population and relevant options (i.e. the ‘decision question’) • Clear view about objectives • Health gain • Issue of equity • Appropriateness of expected value maximisation • Appropriate synthesis for all parameters • Dealing with heterogeneity • Random effects • Increase options • Sub-groups • Not just trial evidence • Dealing with ‘no evidence’ • Role for explicit opinion and judgement