Value-based laboratory medicine: from concept to practice

作者
Mario Plebani
标识
DOI:10.1515/cbr-2026-0004
摘要

Abstract Laboratory medicine plays a pivotal role in modern healthcare, yet a substantial gap persists between the clinical impact of laboratory information and its visibility within healthcare systems. Over recent decades, advances in analytical quality and the introduction of innovative biomarkers have significantly enhanced clinical decision-making. The concept of value in healthcare, defined by Michael Porter as the ratio between clinical outcomes and costs, provides a compelling framework to address this gap. Translating this paradigm into laboratory medicine – value-based laboratory medicine (VBLM) – requires a shift from volume-driven activity to outcome-oriented practice. However, the relationship between laboratory testing and clinical outcomes remains insufficiently documented, reflecting a traditional focus on process indicators rather than outcome-based measures. This paper summarizes the key messages delivered during the “Roman Lecturer Awards” and proposes a structured approach to operationalize VBLM. Advancing VBLM from theory to practice requires coordinated actions, including: prioritizing high-value interventions and outcome-based indicators; reshaping organizational structures to foster integration and collaboration; developing practical tools such as the value-based score; promoting global dissemination and engagement; and establishing strategic partnerships across stakeholders. In particular, the value-based score is presented as a pragmatic tool to assess and benchmark laboratory performance across five domains: traceability in the total testing process, automation and digitalization, quality of laboratory information, clinical interaction, and innovation. Preliminary results from a multicenter European pilot study support its feasibility and potential for widespread implementation. In conclusion, VBLM represents a paradigm shift requiring an architectural redesign of laboratory medicine, centered on appropriateness, quality across the total testing process, and enhanced interpretation of laboratory data.

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