MAY 29, 2014 10:30 AM PDT

Adding Value in Healthcare Delivery: Uses for Clinical Laboratory Informatics in Decision Support

Speaker
  • Principal Officer, Healthcare Management and Education Services (HMES), Education Editor for Clinical Laboratory Science and Expert Consultant for the US Centers for Disease Control and Preve
    Biography
      Dr. Elizabeth Kenimer Leibach is Principal Officer for Healthcare Management and Education Services (HMES), an interventional healthcare enterprise offering consultation in areas related to clinical laboratory services delivery, clinical and translational research, quality assessment, and education.  Activities include rural health clinic establishment, quality monitoring/evaluation, management of labs and lab networks, and application for grant monies to support the establishment of medical information system networks of health care organizations and providers.  Dr. Kenimer Leibach is actively involved in clinical research and publication in evidence-based laboratory medicine related to informatics and clinical decision support, individual and population-level health record data analysis, and quality metrics for evaluation of medical effectiveness and cost efficiency of laboratory services.  Other healthcare initiatives include development of evidence-based educational materials for consumers, healthcare providers, and health educators concerning major chronic diseases of the US population.  Applied quality theory integrates these efforts in the assessment of clinical laboratory performance measures and determination of the medical effectiveness of clinical laboratory information. Dr. Kenimer Leibach has a baccalaureate degree in Medical Technology (MLSCM), and a Master of Science degree in Cell and Molecular Biology from Georgia Regents University (formerly Medical College of Georgia), a Specialist in Blood Banking (SBBCM), certification through the University of Texas Health Sciences Center in Dallas (Parkland Memorial Hospital) School of Blood Banking Technology, and a Doctor of Education in Adult Education from The University of Georgia.  Dr. Kenimer Leibach also serves as Education Editor for Clinical Laboratory Science and Expert Consultant for the US Centers for Disease Control and Prevention. 

    Abstract

    Clinical laboratory information provides decision support for most healthcare providers and impacts care processes and patient outcomes throughout the entire health services delivery system. Evidence-based practice (EBP) describes systematic, data-derived strategies employed by clinical laboratory practitioners in production, interpretation, and communication of laboratory information. EBP includes health outcomes and diagnostic studies, cost- effectiveness analyses, practice guidelines development, and provider/patient/consumer education systems development. Evidence from analyses of these efforts is then used to measure the quality of and assign value to services delivered. Rapid advancements in technology, communications, and information analytics have intersected producing unprecedented opportunity for measuring healthcare effectiveness and efficiency for providers and individual patient/consumers. These rapid advancements have also contributed to challenging economics and heightened privacy concerns. How EBP strategies can be used to define value (highest quality at lowest cost) for providers and individual patient/consumers will be explored. Personalized healthcare delivery models will be discussed. Learn how the discovery and documentation of evidence-based practices help to promote quality and value in healthcare.

    Learning Objectives:

    At the end of the presentation, participants will be able to:

    1. Define clinical laboratory science (CLS) evidence-based practice (EBP) constructs linking clinical research, quality improvement, and provider/patient/consumer education.

    2. Describe CLS practices supporting evidence-based clinical decision- making in personalized healthcare.

    3. Present EBP models describing the current status of clinical decision support systems and suggesting directions for further development.


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