MCDA Tool Examples MCDA A Guide through the

MCDA Tool & Examples MCDA: A Guide through the Application of Different Methods for Assessment and Prioritization of Rare Disease Health Technologies August 28, 2018 Vladimir Zah, DPhil, ACIM, CPIAPD ZRx Outcomes Research Inc. , Canada

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MCDA Tool & Examples • Multiple-criteria decision analysis (MCDA) comprises a set of methods that explicitly considers multiple criteria in decision-making environments. • Formally structuring complex problems appropriately and considering multiple criteria explicitly is expected to lead to more informed and transparent decisions. • MCDA methods are increasing in popularity however existing instruments do not reflect local decision making needs. 3

SECTION 1 Rare Diseases – Why MCDA?

What are the limitations of current approaches to healthcare resource allocation vs. utilization of transparent MCDA process • In case of Rare Diseases, health technologies have to charge premium pricing to recuperate R&D expenses and make profit on a very limited number of patients. • During the period of 2013 -2017, 60% of the Breakthrough therapies are indicated for Rare Diseases. If all were reimbursed, health insurance funds for drugs would quickly go bankrupt. Solution: Transparent health needs prioritization / assessment, which can be achieved through MCDA. 5 * Lanthier M, insights into Rare Disease Drug Approval: Trends and Recent Developments, NORD Rare Diseases & Orphan Products Breakthrough Summit, Oct 17, 2017

MCDA Approaches / Methodologies / Frameworks • EVIDEM (Evidence and Value: Impact on DEcision. Making) Framework is a public framework that assesses the value of treatments based on a set of predefined criteria. Using multi-criteria decision analysis (MCDA), each criterion obtains a specific weight that enables calculation of an aggregate rating score for each treatment • LSE (London School of Economics) – is also based on a set of predefined criteria • Pw. C (Price Waterhouse Coopers) • … + Other frameworks exist Stakeholders are in charge! (need training) Health Economists “standardize” framework for decision making process. 6 Ref: www. evidem. org

SECTION 2 Steps Necessary to Build MCDA

MCDA Tool & Examples • 4 Steps necessary to build proper MCDA: 1) Deliberation – what is the expected from an analysis, which criteria will be used for benchmarking / comparison, what are valid comparators (alternatives) for the analysis 2) MCDA - inter-criteria comparison: What is the weight of each criteria – direct comparison between two criteria using Visual Analogue Scale (VAS) to establish weights of each criteria 3) MCDA – alternatives comparison: Evaluate health technologies against criteria 4) MCDA – results: Establish ranking among alternatives 8

BACKGROUND COMPLETED

SECTION 3 MCDA Tool

MCDA Tool & Examples

SECTION 4 Steps necessary to create a valid MCDA criteria through deliberation and descriptions thereof

MCDA Tool & Examples Criteria Definition and Description 13

MCDA Tool & Examples Criteria Definition and Description 14

50% MCDA INTRO & STEPS COMPLETED

SECTION 5 MORE DELIBERATION: How to provide inter-criteria weights and select appropriate alternatives

MCDA Tool & Examples Inter-Criteria Weights – Trade-off between 2 criteria • . 17

MCDA Tool & Examples Alternatives added for comparison • . 18

Assigning value to each RD technology based on Criteria

50% DELIBERATION COMPLETED

SECTION 5 RESULTS: Apply each MCDA ranking method and it’s applicability in decision-making: Hurwitz, SLAM, MAVT and AHP.

MCDA Tool & Examples 22 Results methodology decision

MCDA Tool & Examples RESULTS OPTIONS 23

MCDA Tool & Examples Hurwicz Method (Min/Max) 24

MCDA Tool & Examples Simple Linear Adaptive Model 25

MCDA Tool & Examples Simple Linear Adaptive Model 26

MCDA Tool & Examples Multi-Attribute Value Theory g Swin hts Weig MOVE TO ADJUST RESPONSE 27

MCDA Tool & Examples Multi-Attribute Value Theory 28

MCDA Tool & Examples Multi-Attribute Value Theory 29

MCDA Tool & Examples Analytic Hierarchy Process 30

90% Hurwitz, SLAM, MAVT and AHP MCDA Results COMPLETED

Lessons learned - Robust MCDA : 1) Deliberate on criteria 2) Psychometric testing of criteria description of outmost importance 3) Results method selection important: from simplest to more advanced (different results) 4) Polling stakeholder responses together and merging them together using median before calculating results gives robust results 5) Re-assess on an annual basis 6) Keep it simple…

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