4281.0 Data Mining Technologies and Applications

Tuesday, November 9, 2010: 2:30 PM - 4:00 PM
Data mining, which is defined as the extraction of hidden predictive information from large databases, is a powerful technology with great potential to help public health. This session will focus on the application of data mining and public health to effectively lead to better problem discovery and solution development. Presentations will examine the utilization of electronic health records and population health, and how patterns and associations within the data contained within those records provide opportunities to effectively survey and manage the public health of various communities. On presentation will focus on the techniques of data mining, such as data analysis, preference modeling, simulation and visualization will also be explored and its relationship to the identification of preventable hospital admissions and the subsequent reduction of costs. By identifying significant patterns within the data that lead to a greater understanding of public health issues, such as chronic disease management, facilitate better patient-centered communication by focusing on the core issues relevant to that individualís health. One such presentation will identify how using this type of decision-tree classification provides a better mechanism for this type of patient-centered communication.
Session Objectives: 1. Describe the tools and techinques of data mining and its relationship to public health 2. Demonstrate how the use of data mining can effectively assit in public health management 3. Explain how the use of decision-tree classification in data mining faciltites patient-centered communication
Aneel Advani, MD, MPH

IHS iCare System: An EHR for Population Health in a NationwideHealth System
Aneel Advani, MD, MPH, Howard Hays, MD, MSPH, Bill Williams, Cynthia Gebremariam, RN and Theresa Cullen, MD, MS
Assessing Patient-Centered Communication Using Decision Tree Classification
Yoon-Ho Seol, PhD, Genny Carrillo-Zuniga, MD, MPH, ScD and Miguel A. Zuniga, MD, DrPH

See individual abstracts for presenting author's disclosure statement and author's information.

Organized by: Health Informatics Information Technology

CE Credits: Medical (CME), Health Education (CHES), Nursing (CNE), Public Health (CPH)