Quality healthcare and research initiatives would benefit from the ability to efficiently extract patient journeys from electronic medical records (EMRs) across the healthcare system. While the move toward digitizing patient data in the form of EMRs has improved data access for clinicians and patients alike, current system design, data silos and conflicting entries increase the cost of data acquisition and limit the analytics needed to improve patient care and conduct research. As a result of these challenges, organizations typically rely on painstaking manual data curation, consuming highly valuable skilled clinician time.
Join this webinar to learn how artificial intelligence (AI) technology is ideally suited for the time-consuming, redundant function of data abstraction, putting the data within easy reach of healthcare professionals for clinical decisions, administrative staff for operational efficiencies, and researchers to leverage real-world patient data.
Andrew Shin, MD, Clinical Professor, Division of Cardiology, Stanford University; Executive Medical Director of Innovations & Clinical Effectiveness, Stanford Children’s Health
Andrew Shin, MD, is a Clinical Professor in the Division of Cardiology at Stanford University and the Executive Medical Director of Innovations & Clinical Effectiveness for Stanford Children’s Health. His research has leveraged microsystems, improvement science and high reliability to better understand the intersection between the quality and efficiency of healthcare delivery. As the Medical Director for Systems Design for Utilization Research for Stanford (SURF MEDICINE), Dr. Shin translates his research to continuously improve the value of healthcare utilizing high-throughput advanced analytics such as machine learning and artificial intelligence. He completed his pediatric residency, along with a dual fellowship in pediatric cardiology and pediatric critical care at Boston Children’s Hospital. Dr. Shin is the Medical Director of Quality and Outcomes for the Betty Irene Moore Heart Center and serves as a board member for Pediatric Congenital Heart Association, Carta Healthcare and as liaison for the American Heart Association’s Leadership Committee of the Council on Quality of Care and Outcomes Research.Message Presenter
Matt Hollingsworth, MS, MBA, Chief Executive Officer, Carta Healthcare
Matt Hollingsworth is the CEO and co-founder of Carta Healthcare, provider of AI-powered clinical data abstraction technology and services. Matt holds an MBA from Stanford University and studied high-energy physics, performing his research at CERN (European Organization for Nuclear Research) as part of the team that discovered the Higgs boson. Prior to CERN, Matt co-founded a technology start-up, Global Dressage Analytics and provided technical leadership for another start-up, Deepfield, which provides telecom analytics. He also proposed, won and managed projects for the Department of Defense and managed projects for various Internet of Things (IoT) applications at Samsung.Message Presenter
Who Should Attend?
This webinar is suitable for managers, leads and other relevant job titles in the following departments:
- Quality Director
- Chief Information Officer (CIO)
- Clinical Effectiveness Titles from Academic Medical Centers (AMCs)
- General Researchers
What You Will Learn
Join this webinar to learn about how artificial intelligence (AI) technology is ideally suited for the time-consuming, redundant function of data abstraction, putting the data within easy reach of healthcare professionals for clinical decisions, administrative staff for operational efficiencies, and researchers to leverage real-world patient data.
Founded in 2017, Carta Healthcare’s mission is to harness the value of clinical data to improve patient care. Through its industry-leading, AI-driven technology, Carta Healthcare supports the healthcare data registry market by transforming the previously manual clinical data abstraction process. Carta’s technology allows healthcare organizations to collect, analyze, and act on their data, creating a quality, trustworthy dataset whose value fuels data-driven decisions that ultimately improve care delivery. For more information, visit www.carta.healthcare or contact us at [email protected].