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The Pathologist / Issues / 2026 / March / Valuebased Healthcare The Vision
Bioinformatics Laboratory management Clinical care Precision medicine Profession Screening and monitoring Opinion and Personal Narratives Professional Development Career Pathways

Value-based Healthcare: The Vision

Founding members of the Santa Fe Project discuss the role of pathology in improving population-level health

By Helen Bristow 03/17/2026 Discussion 9 min read
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Objective:

To discuss the evolution of the Santa Fe Project and the Clinical Lab 2.0 movement in enhancing the role of pathology in population health and value-based healthcare, particularly in response to current healthcare challenges.

Key Findings:
  • The clinical laboratory sector played a crucial role during the COVID-19 pandemic, reinforcing the need for value-based healthcare and highlighting the importance of timely diagnostics.
  • The traditional fee-for-service model in laboratory medicine is flawed and needs disruption to realize its full potential, particularly in light of recent healthcare demands.
  • Proactive risk detection is essential for value-based care, allowing for early prevention and better patient outcomes, which is increasingly critical in managing chronic diseases.
Interpretation:

Value-based care in laboratory medicine focuses on proactive risk management and continuous feedback loops to improve patient care, emphasizing the importance of early intervention rather than merely increasing test volume.

Limitations:
  • The article does not provide specific quantitative data on the impact of the proposed changes.
  • Engagement strategies with policymakers and other stakeholders may vary in effectiveness across different regions.
  • Potential resistance from established healthcare systems to adopt new models of care is not addressed.
Conclusion:

The Santa Fe Project advocates for a transformative approach to laboratory medicine that emphasizes proactive risk management and the strategic value of diagnostics in healthcare delivery.

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.

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About the Author(s)

Helen Bristow

Combining my dual backgrounds in science and communications to bring you compelling content in your speciality.

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