A framework for organizing and selecting quantitative approaches for benefit-harm assessment.

Area of Science:

• Health Services Research
• Clinical Epidemiology
• Decision Science

Background:

• Multiple quantitative methods exist for assessing benefits and harms of health interventions.
• Current understanding of how these benefit-harm assessment approaches differ is limited.
• A clear framework is needed to guide the selection of appropriate quantitative methods.

Purpose of the Study:

• To systematically review existing quantitative approaches for benefit-harm assessment.
• To develop an organizing framework that clarifies differences among these approaches.
• To aid investigators in selecting the most suitable quantitative approach for specific decision-making contexts.

Main Methods:

• Conducted a literature review to identify quantitative benefit-harm assessment approaches.
• Convened a multidisciplinary team (clinicians, epidemiologists, statisticians) to discuss and characterize identified approaches.
• Developed a selection framework based on key characteristics and decision-making context.

Main Results:

• Identified 16 quantitative benefit-harm assessment approaches, categorized by single/multiple outcomes and use of a benefit-harm comparison metric.
• Most approaches use aggregate data and apply to single studies or systematic reviews.
• Few approaches provide measures of uncertainty (4/16) or incorporate patient preferences (9/16); none consider the joint distribution of outcomes.

Conclusions:

• The selection of a benefit-harm assessment approach depends on the research question, goals, data availability, and context.
• Using multiple approaches and comparing results can enhance confidence in findings.
• Further research comparing the relative advantages of different approaches is needed to refine recommendations.