Keynote Speaker

Population Health Informatics and Visualization: Challenges and Opportunities
Hadi Kharrazi, MD, PhD, MHI


Abstract:
Population Health Informatics (PHI) is growing field of informatics shaping around the requirements of healthcare providers to improve the health of their patient populations under the guidance of value-based programs. PHI analytics – rooted in the traditional risk stratification of patients conducted by insurers using insurance claims – is now widely adopted by healthcare providers; however, the complexity of using electronic health record (EHR) data instead of insurance claims has turned the PHI analytic into a difficult task to comprehend.

This presentation will provide an overview of population health, and how informatics is changing it. The presentation will also describe various data types/sources used by PHI analytic and discuss data quality challenges of using them. The presentation will then focus on the challenges and opportunities of using various visualizing techniques in easing the comprehension of PHI analytic results given the various data types used to conduct them. Finally, the presentation will offer the audience to join and contribute to a working manuscript on PHI and visualization.

Bio:
Dr. Hadi Kharrazi is a core faculty of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health with a joint appointment at the Johns Hopkins School of Medicine. He is the research director of the Johns Hopkins Center for Population Health IT (CPHIT) and serves on multiple national advisory boards and steering committees including: the Public Health Informatics Working Group Executive Committee of the American Medical Informatics Association (PHI‐WG AMIA), the Steering Committee of the Academy Health’s Health IT Interest Group (AH‐HIT IG), and the DHHS ONC’s Measurement Community of Practice.

Dr. Kharrazi's primary research interest is in population health informatics (PopHI). His research focuses on the use of new data sources such as EHRs (electronic health records), and advanced informatics/predictive methods such as deep learning in identifying high risk subpopulations. Results of his research are often used in operational settings to better align clinical and social interventions and improve population outcomes while containing cost. He is currently the [co‐] principal investigator of a number of federal and state grants with special focus on population/clinical health IT including:
  • DHHS ONC award to develop a national population health IT curriculum and training program for incumbent health professionals;
  • ACTION‐II AHRQ contract to evaluate population health and care coordination items of stages 3 of EHR ‘Meaningful Use’ measures of CMS in hospital settings;
  • AHRQ grant to develop and evaluate a 30‐day hospital readmission prediction model based on real‐time health information exchange data in Maryland;
  • VHA‐funded contract to develop a comprehensive data‐driven population health framework that would provide policy makers with spatiotemporal BMI trajectories; and,
  • project funded by Maryland’s Department of Health and Mental Hygiene to develop and pilot advanced population health metrics based on state‐wide hospital discharge data