NOV 03, 2016 9:00 AM PDT

KEYNOTE: Big data and the learning healthcare system: practical applications for the clinical laboratory

Speaker
  • Assistant Professor of Pathology Director, Point of Care Testing Associate Director, Chemical Pathology; University of Michigan Hospital
    BIOGRAPHY

Abstract

The aim of the learning healthcare system is to leverage data stored in the electronic health record (EHR) to gain insights into and improve healthcare delivery. Laboratory testing represents the largest source of routinely formatted data in the EHR and is therefore readily accessible for mining. In this presentation I will be describing a variety of practical applications of EHR data analytics relevant to clinical laboratory practice and patient care. These will include automatic generation of institutional reference ranges, synthesis of test panel results with machine learning models, fine-grained characterization of point-of-care instrument accuracy, effects of in-vitro hemolysis on central laboratory testing results, and the use of in-silico simulations to put the findings in context. Taking care to account for implicit confounders present in retrospective studies, a wealth of data exists in the EHR that can be unlocked to aid in day-to-day management of the clinical laboratory as well as guide healthcare policy-making in general.


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NOV 03, 2016 9:00 AM PDT

KEYNOTE: Big data and the learning healthcare system: practical applications for the clinical laboratory


Specialty

Immunity

Cancer

T-Cells

Virology

Health

Antibodies

Clinical Medicine

Immunology

Personalized Medicine

Dna Sequencing

Clinical Diagnostics

Immunotherapy

Cancer Diagnostics

Flow Cytometry

Bioinformatics

Geography

North America50%

Europe50%

Registration Source

Website Visitors100%

Job Title

Student50%

Clinical Laboratory Scientist50%

Organization

Academic Institution50%

Government50%


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