NOV 12, 2015 06:00 AM PST
Laboratory Medicine: What should we be measuring?
Presented at the Clinical Diagnostics and Research Virtual Event
2 18 1023

Speakers:
  • Associate Professor of Pathology (Clinical), Medical Director of Informatics, ARUP Laboratories, University of Utah, Department of Pathology
    Biography
      Dr. Jackson directs the Informatics Department at ARUP, including ARUP Consult®, decision support, product management, informatics software development, and ATOP® consulting. He is also the medical director for Referral Testing and an associate professor of pathology at the University of Utah. He received his BA in mathematics, his MS in medical informatics, and his MD from the University of Utah, and completed a clinical pathology residency at Dartmouth-Hitchcock Medical Center. Prior to his employment at ARUP, Dr. Jackson was a staff clinical pathologist and informaticist at Dartmouth-Hitchcock Medical Center, a product manager for a Belgium-based medical software firm, and a National Library of Medicine informatics fellow at the University of Utah. Dr. Jackson's research interests include economic analysis of diagnostic testing and physician utilization of laboratory tests. He is certified in clinical pathology by the American Board of Pathology.

    Abstract:
    As hospitals and healthcare systems move toward value-based care, new management systems are needed to measure and improve clinical processes.  This presents both an opportunity and a challenge for laboratories to move beyond internally-facing perspectives and become better integrated into improving clinical care.  The categories of an ideal measurement system would include cost, patient benefit, and performance quality.  Each of these should be assessed at multiple layers of granularity, from executive summary down to individual item.

    Learning Objectives:
    • Identify measures of cost, patient benefit and quality that can together create a comprehensive view of clinical laboratory performance
    • Identify which of these measures are feasible today versus requiring future research.

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