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The Importance of Decision Analytic Modelling in Evaluating Health Care Interventions

The Importance of Decision Analytic Modelling in Evaluating Health Care Interventions. Mark Sculpher Professor of Health Economics Centre for Health Economics University of York, UK. Generic measures of health; QALYs. Objective function. Decision problem.

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The Importance of Decision Analytic Modelling in Evaluating Health Care Interventions

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  1. The Importance of Decision Analytic Modelling in Evaluating Health Care Interventions Mark Sculpher Professor of Health Economics Centre for Health Economics University of York, UK

  2. Generic measures of health; QALYs Objective function Decision problem Clarity about population; full specification of options Appropriate time horizon Time over which options might differ Inclusion of all relevant evidence Evidence base Context Relevant to specific decision maker(s) Uncertainty Quantify decision uncertainty; feed in research prioritisation The requirements of economic evaluation for decision making

  3. Is trial-based economic evaluation the answer?What is trial-based economic evaluation? • Health care facilities • Unit costs (prices) of • resources • Single RCT • Patient level data on: • Resource use • Health-related events • Sample of public • ? Utility data to value • health events • Cost-effectiveness analysis • Costs & effects averaged across trial sample • Time horizon = trial follow-up • External data for valuation only

  4. Follow-up often < time horizon Time horizon Comparison Trials compare selected options not all strategies Evidence base Typically there are other trials and sources Trials undertaken in multiple locations Context Partial comparison and evidence means uncertainty not appropriately quantified Uncertainty (A selection of) problems with trial-based economic evaluation Sculpher et al. Whither trial-based economic evaluation for health care decision making? Health Economics 2006;15:677-687.

  5. Systematic review • Meta-analysis • Mixed treatment comparisons • Differing endpoints and follow-up • Patient-level and summary data Evidence synthesis • Structure reflecting disease • Incorporation of evidence on range • of parameters • Facilitates extrapolation and • separation of baseline and treatment • effects • Probabilistic methods Decision analysis What is the appropriate framework for economic evaluation?

  6. Case study – Glycoprotein IIb/IIIa antagonists in acute coronary syndrome GPA as part of initial medical management [7 trials] Strategy 1: Strategy 2: GPA in patients with planned percutaneous coronary interventions (PCIs) [1 trial] Strategy 3: GPA as adjunct to PCI [10 trials] Strategy 4: No use of GPA Palmer et al. Management of non-ST-elevation acute coronary syndromes: how cost-effective are glycoprotein IIb/IIIa antagonists in the UK National Health Service? International Journal of Cardiology 2005;100:229-240.

  7. Limitations with GPA trials Trial characteristic Partial comparison Non-UK case-mix and clinical practice No resource use data Short-term time horizon Modelling method Pooled relative risks from trials applied to common baseline risks UK-specific baseline risks from observational study. Relationship between baseline risks & treatment effect explored with meta-regression Resource use data from UK observational study attached to clinical events Extrapolation from 6 months based on Markov model populated from UK observational study

  8. Decision uncertainty ICER: £5,738 per QALY 94% at £30,000 100.00% 90.00% Strategy 1 80.00% 70.00% 60.00% Probability Cost-Effective (%) 50.00% 40.00% 30.00% Strategy 4 20.00% 10.00% 0.00% 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 100000 Maximum willingness to pay for an additional QALY (£)

  9. Using uncertainty • Relevance of conventional inference? • What do we put in its place? • Leave error probabilities to the decision maker • When is it no longer efficient to further information? • What if the decision maker has no control of research?

  10. Summary • Economic evaluation studies exist to inform decision making • Rarely will trial-based studies be sufficient for this purpose • Synthesis and models should be seen as the standard framework for economic evaluation

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