Expanding Quantitative Methods of Value Assessment: Multi-Criteria Decision Analysis

Cost-effectiveness analysis (CEA) and cost-utility analysis (CUA) have become the de facto approaches for assessing the value of healthcare interventions and informing healthcare decision-making. However, they are not without their flaws. For example, standard CUA estimates the incremental cost-per-quality-adjusted life year (QALY) which is prohibited under the Inflation Reduction Act (IRA) as QALYs have been argued to be discriminative against elderly, disabled or terminally ill individuals who have a lower maximum utility and thus reduced capacity to benefit from new interventions.1 Further information on the implications of the IRA can be in a separate commentary found here (‘The IRA is Law – Now What?’). The development of the Generalised Risk-Adjusted Cost-Effectiveness (GRACE) Framework aims to address the purported shortcomings of standard CEA by incorporating the concept of diminishing marginal utility with respect to health into CEA and reflecting varying willingness-to-pay thresholds by disease severity. Our detailed commentary on the GRACE framework can be found in a separate write-up here (‘Analytical Methods & Technical Topics’).2 However, beyond the above criticism, it has been argued that only a fraction of the value an intervention provides can be captured in the incremental cost-per-QALY metric. New methods, such as Extended CEA and Distributional CEA, have been proposed to account for benefits such as financial risk protection and equity within CEA.3, 4 Nevertheless, incorporating novel elements of value like those presented in the ISPOR value flower (e.g. real option value, value of hope) and accounting for disparate preferences across stakeholders (patients, providers, payers, etc.) within the healthcare system in CEA remains challenging.

Multi-Criteria Decision Analysis

Phelps et al. (2019) have proposed using Multi-Criteria Decision Analysis (MCDA) as a supplement to CEA for evaluating healthcare interventions.5 At this year’s ISPOR International, there were multiple sessions involving discussion on the use of MCDA in healthcare decision-making.6, 7 By eliciting the preferences of decision makers, MCDA can theoretically better capture the value associated with each alternative intervention that may be difficult to reflect through CEA. The goal of MCDA is not to replace the role of CEA in healthcare decision-making but to expand the value assessment framework and present stakeholders with additional evidence of value for relevant healthcare interventions together with findings from the CEA. A typical MCDA usually includes the following steps:

MCDA steps figure

A simplified example of MCDA is presented in Table 1.

Table 1. Example of MCDA

Criterion Weight Score of Drug A Score of Drug B
Cost of therapy 0.5 100 50
Administration route 0.3 60 70
Number of pills 0.2 80 80
Total 1.0 84=(100*0.5+60*0.3+80*0.2) 62=(50*0.5+70*0.3+80*0.2)

In this example, the results suggest that Drug A is the optimal choice since it has a higher weighted sum compared with Drug B. Note that methods for conducting an MCDA are not limited to the example presented above, and there are many weighting and scoring methods available. This diversity in methods and the user complexities associated with them lead to challenges in the adoption of MCDA. ISPOR’s Emerging Good Practices Task Force has published a report on good practices for conducting MCDA and provided guidance for choosing the appropriate MCDA methods, in an effort to improve MCDA’s usability.8, 9 Overall, MCDA represents a promising methodology to account for additional elements of value that may not be captured by traditional CEA, but we are yet to see an emerging dominant method or use case, despite guidance from ISPOR. With increasing use, the appropriate application of this methodology may become clearer.


  1. Meena Seshamani. Medicare Drug Price Negotiation Program: Initial Memorandum, Implementation of Sections 1191 – 1198 of the Social Security Act for Initial Price Applicability Year 2026, and Solicitation of Comments. 2023. Available here. Last accessed: June 2023.
  2. Lakdawalla, DN; Phelps, CE. Health Technology Assessment With Diminishing Returns to Health: The Generalized Risk-Adjusted Cost-Effectiveness (GRACE) Approach. Value in Health. 2021;24(2):244-249.
  3. Verguet, S; Kim, JJ; Jamison, DT. Extended Cost-Effectiveness Analysis for Health Policy Assessment: A Tutorial. Pharmacoeconomics. 2016;34(9):913-923.
  4. Cookson, R; Mirelman, AJ; Griffin, S et al. Using Cost-Effectiveness Analysis to Address Health Equity Concerns. Value Health. 2017;20(2):206-212.
  5. Phelps, CE; Madhavan, G. Valuing Health: Evolution, Revolution, Resistance, and Reform. Value Health. 2019;22(5):505-510.
  6. Workshop WS206: Is There Room for Patient-Centered Value Assessment in Medicare Negotiation and State Prescription Drug Affordability Board Processes? ISPOR International Congress, Boston, 2023.
  7. Short Course Session: A Health Economics Approach to US Value Assessment Frameworks. ISPOR International Congress, Boston, 2023. 2023.
  8. Marsh, K; M, IJ; Thokala, P et al. Multiple Criteria Decision Analysis for Health Care Decision Making–Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force. Value Health. 2016;19(2):125-137.
  9. Phelps, CE. Expanding Use of Multi-Criteria Decision Analysis for Health Technology Assessment. 2019. Available here. Last accessed: June 2023.

If you would like any further information on the themes presented above, please do not hesitate to contact Connor Davies, Senior Analyst (LinkedIn) and Alex Porteous, Consultant (LinkedIn). Connor Davies and Alex Porteous are employees at Costello Medical. The views/opinions expressed are their own and do not necessarily reflect those of Costello Medical’s clients/affiliated partners.