Advanced Health Technology Economic Evaluation Training Course

Overview

Advanced Health Technology Economic Evaluation Training Course is a one-week advanced course for health economists, HTA analysts, payers, finance specialists, policy analysts, and assessment teams who leave with a Health Technology Economic Evaluation Dossier. Participants connect decision problems, cost-effectiveness and cost-utility analysis, decision-analytic modeling, uncertainty, budget impact, critical appraisal, and decision reporting. Agile Leaders Training Center presents health technology economic evaluation through transparent assumptions, reproducible analysis, and decision-focused evidence.

Who Should Attend

• Economic analysis functions responsible for evaluating costs, outcomes, and value
• Technology assessment functions responsible for evidence synthesis and appraisal
• Payer functions responsible for coverage, reimbursement, and affordability decisions
• Finance functions responsible for resource use, budgets, and financial consequences
• Policy functions responsible for priority setting and decision recommendations

The course assumes participants already work with health evidence, costs, outcomes, or technology decisions and leaves out introductory economics, clinical licensing, and product pricing negotiation.

Departments and Industries

The course supports departments and industries that evaluate health technologies, allocate resources, or prepare evidence for decisions.

• Hospitals, health systems, and payer organizations
• Pharmaceutical, medical-device, and digital-health organizations
• Health technology assessment and evidence-review units
• Healthcare finance, planning, and policy departments
• Research organizations and academic health centers

Learning Objectives

By the end of this course, participants will be able to:

• Analyze decision problems, perspectives, comparators, and time horizons
• Apply cost-effectiveness and cost-utility methods
• Build decision-analytic model structures and parameter registers
• Evaluate deterministic, probabilistic, and structural uncertainty
• Develop budget impact and affordability analyses
• Critically appraise and report economic evidence for decisions

Course Agenda

Day 1: Decision Problem and Evaluation Design

• Health Technology Decision Problem Canvas
• Population, Intervention, Comparator, Outcome Scope Matrix
• Analytical Perspective and Time-Horizon Checklist
• Clinical Pathway and Resource-Use Map
• Economic Evaluation Protocol Template

Day 2: Costs, Outcomes, and Incremental Analysis

• Cost Identification and Measurement Ledger
• Health Outcome and QALY Evidence Map
• Incremental Cost-Effectiveness Calculation Sheet
• Dominance and Extended-Dominance Decision Rules
• Cost-Effectiveness Plane and Frontier

Day 3: Decision-Analytic Modeling

• Decision Tree Structure Diagram
• State-Transition Model Specification
• Model Parameter and Data-Source Register
• Cycle Length, Discounting, and Extrapolation Assumption Log
• Internal Validity and Model Debugging Checklist

Day 4: Uncertainty, Budget Impact, and Reporting

• Deterministic Sensitivity Analysis Tornado Chart
• Probabilistic Sensitivity Analysis Plan
• Cost-Effectiveness Acceptability Curve
• Budget Impact Analysis Population Framework
• CHEERS Reporting and Critical Appraisal Checklist

Day 5: Economic Evaluation Practice

• Exercise: Frame a Health Technology Decision Problem
• Exercise: Calculate Incremental Costs and Outcomes
• Exercise: Test Model and Parameter Uncertainty
• Exercise: Present Budget Impact and Decision Findings
• Capstone Exercise: Health Technology Economic Evaluation Dossier

Practical Exercises

The course uses suggested activities from payer, hospital, pharmaceutical, medical-device, digital-health, research, and policy settings.

• Suggested activity: define a decision problem and align population, comparators, perspective, outcomes, and time horizon.
• Suggested activity: construct an incremental analysis and interpret dominance, ICERs, and the cost-effectiveness plane.
• Suggested activity: test model assumptions with deterministic, probabilistic, and structural uncertainty methods.
• Suggested activity: combine economic results, budget impact, limitations, and decision messages in an appraisal dossier.

FAQs

Who suits advanced health technology economic evaluation training, and what does it assume?

Advanced health technology economic evaluation training suits experienced economic, assessment, payer, finance, policy, and research functions. It assumes familiarity with health evidence, costs, outcomes, or resource-allocation decisions.

How does health technology economic evaluation differ from general healthcare finance training?

Health technology economic evaluation compares technologies through costs, health outcomes, models, uncertainty, and decision rules. General healthcare finance training focuses more broadly on accounting, budgets, revenue, and financial management.

What is the difference between cost-effectiveness and cost-utility analysis?

Cost-effectiveness analysis relates incremental costs to a defined outcome measure. Cost-utility analysis uses a preference-based outcome such as QALYs, allowing comparison across different health technologies and conditions.

Why is uncertainty analysis important in health technology economic evaluation?

Uncertainty analysis shows how parameter values, model structures, evidence choices, and scenarios affect results. It helps decision makers judge robustness and identify where further evidence could change a conclusion.

How does budget impact complement health technology economic evaluation?

Budget impact estimates the financial consequences of adoption for a defined payer population and period. It complements value assessment by addressing affordability and implementation consequences.

Conclusion

The course connects evaluation design, incremental analysis, decision modeling, uncertainty, budget impact, critical appraisal, and reporting. Participants take back a Health Technology Economic Evaluation Dossier. The dossier changes how teams structure assumptions, test evidence, interpret value, assess affordability, and communicate economic findings for decisions.