The Evidence Value Matrix for Diagnostic Imaging.

Area of Science:

• Medical Imaging
• Health Economics
• Health Technology Assessment

Background:

• Evidence and value are critical, independent factors influencing diagnostic imaging adoption.
• Reimbursement decisions by authorities often hinge on insufficient evidence or demonstrated value.
• A clear framework is needed for stakeholders to understand and assess imaging technologies.

Purpose of the Study:

• To propose a two-dimensional matrix for classifying diagnostic imaging devices.
• To categorize imaging based on evidence level and demonstrated value.
• To guide strategies for evidence and value generation.

Main Methods:

• Development of a two-dimensional matrix categorizing imaging into "question marks," "candidates," and "stars."
• Classification based on evidence level (e.g., retrospective studies, randomized controlled trials) and value.
• Illustrative examples demonstrating the matrix's application.

Main Results:

• The matrix categorizes imaging into "question marks" (low value), "candidates" (high value, limited evidence), and "stars" (high value, strong evidence).
• High-evidence/low-value studies are identified as costly and unlikely to influence decision-makers.
• A "success sequence" strategy is proposed for developing technologies from "question marks" to "stars."

Conclusions:

• The proposed matrix provides a sophisticated and objective approach to assessing diagnostic imaging.
• It facilitates the development of targeted evidence and value generation strategies.
• This framework is essential for justifying funding for reimbursement and provider adoption.