ISPOR Quantitative Benefit-Risk Assessment Good Practices
This guideline provides best practices for assessing the benefits and risks of health interventions using quantitative methods. It supports structured decision-making by incorporating patient and stakeholder preferences, especially through multi-criteria decision analysis (MCDA) and preference elicitation techniques.
At a glance
Use when
When a structured, transparent evaluation of benefits and risks is needed, especially to inform regulatory or reimbursement decisions involving trade-offs and patient input
Avoid when
When only qualitative assessment is required, or when reliable preference or weighting data are unavailable
Inputs
Clinical outcomes data, risk data, preference weights (e.g., from DCE or swing weighting), MCDA criteria and structure
Outputs
Quantitative benefit-risk profiles, visualizations of trade-offs, weighted scores across criteria, transparent rationale for decisions
How it works
A peer-reviewed report by the ISPOR Task Force (2023) outlining good practices for quantitative benefit-risk assessment. It includes guidance on integrating preference-weighting methods—such as discrete choice experiments (DCE), swing weighting, and the threshold technique—within multi-criteria decision analysis (MCDA) frameworks to support transparent, systematic evaluation of health technologies.
- HTA domains
- Clinical Effectiveness, Patient and Social Aspects, Aspects Beyond HTA
- Categories
- AppraisalEvidence SynthesisTransparency
- Assumptions
- That benefits and risks can be quantified and compared using structured frameworks; that stakeholder preferences can be reliably elicited and integrated; that decision transparency improves accountability
- Strengths
- Promotes transparency, consistency, and stakeholder engagement; supports integration of patient preferences; enhances reproducibility of benefit-risk assessments
- Limitations
- Requires high-quality preference data; complexity may increase implementation burden; methodological choices (e.g., weighting) can influence results
- Also known as
- ISPOR QBR Good Practices, Quantitative Benefit-Risk Guideline
Questions this answers
- › How should quantitative benefit-risk assessments be structured and reported?
- › Which preference elicitation methods are appropriate for benefit-risk trade-offs?
- › How can MCDA be applied to benefit-risk analysis?
- › What are best practices for weighting benefits and risks?
- › How can patient preferences be integrated into benefit-risk assessments?
- › What are the methodological standards for transparency and reproducibility in quantitative benefit-risk analysis?
References & sources
Similar by meaning
- ISPOR Value of Information Analysis (Report 1)
- ISPOR Roadmap for Patient-Preference Studies in Decision Making
- ISPOR Prospective Observational Studies to Assess Comparative Effectiveness Good Research Practices Task Force Report
- ISPOR MCDA Emerging Good Practices (Report 2)
- ISPOR Retrospective Database Analysis Good Research Practices — Part III (Analytic Methods)
Beta record. Based on the original catalogue summary; primary-source enrichment pending.