EMR Focused on Clinical Care - How to Deal with Information Overload
Please register for EMR Focused on Clinical Care - How to Deal with Information Overload on May 3, 2018 2:00 PM CDT at:
The quantity of information encountered in a hospital equipped with a comprehensive electronic health record (EHR) can quickly overwhelm the processing abilities of bedside providers. This is particularly true in the moments of stress and time pressure frequently encountered in the ICU setting.
Ambient and warning response evaluation (AWARE) is a data integration and decision support platform for intensive care, designed by health care providers, for health care providers to increase the efficiency and accuracy of data assimilation and communication with goal to improve patient outcomes. AWARE is tested and validated to increase stress free compliance with best clinical practice in Mayo Clinic Rochester ICUs. AWARE is successfully implemented in Mayo Clinic Arizona and Florida ICUs as well as in Lawrence General Hospital, Massachusetts.
Learning Objective 1: Identify major problems with current EMR interfaces
Learning Objective 2: Define patient centered user interfaces
Learning Objective 3: Summarize methods for EMR interfaces evaluation
Vitaly Herasevich, MD, PhD
Associate Professor of Anesthesiology and Medicine, Dept. of Anesthesiology and Perioperative Medicine, Division of Critical Care, Mayo Clinic
Dr. Herasevich has been involved in medical informatics for over 20 years, with a specific concentration on applied clinical informatics in critical care and the science of health care delivery. Today, he codirects the Clinical Informatics in Intensive Care Program at Mayo Clinic.
He was born in Belarus, where he earned his M.D. and Ph.D. degrees, and joined the Mayo Clinic in 2006. Later he finished MSc in clinical research at Mayo Clinic and became Certified Professional in Healthcare Management Systems (CPHIMS).
He is interested in studying and developing clinical syndromic surveillance alerting systems, clinical data visualization, and complex large data warehousing for health care predictive and prescriptive analytics as well as outcome reporting
After registering, you will receive a confirmation email containing information about joining the webinar.
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