Data collection, integration and normalization presented to DIMACS Gil Delgado October 17, 2002

Discussion Challenges and barriers as well as processes and methods for collection, integration, and harmonization of clinical data. Clinical Data as a resource for Disease Surveillance, BioTerrorism detection, and Adverse Events Reporting.

Agenda Challenges and Barriers Overview of clinical data collection, integration and harmonization Processes Methods Demonstration of Health Data System

Challenges and Barriers Social, Political, and Ethical HIPAA Incentives Resources Available Infrastructure Vocabularies and Codes Appropriate Filtering

Collection, Integration and Harmonization Overview Enterprise Application Integration Interface Engines HL7 Enterprise Master Patient Indexing De-Identification Vocabulary Harmonization Standard vs. Proprietary Mapping

Processes and Methods Rational’s Unified Process (RUP) Message-based Processing Error Reporting Change Management Patient Matching Vocabulary Mapping Quality Assurance Performance Metrics and Management

Deployment Architecture

Commercial Research Architecture

Public Health Surveillance Architecture

Demo Health Data System

Appendix The following three slides present “more details” about the data that Emergint provides for research. These slides discuss the value of the data, from how it is collected, what is collected, how it is harmonized, and how it is made available.

Appendix: Value Creation Emergint captures the same data directly used in the delivery of clinical care, rather then secondary data derived from clinical care, such as claims data and chart abstraction Patient data are multi-encounter and longitudinal, de-identified in compliance with HIPAA, continually updated and linked across multiple inpatient and outpatient providers

Appendix: Value Creation (con’t.) Data consists of demographic (age, sex, weight, etc.), diagnosis, procedures and results (laboratory results, medications, transcriptions including history and physical and discharge summary) Data are electronically captured and maintained in original terminology and transported in a common format (XML) to retain maximum data integrity

Appendix: Value Creation (con’t.) Data are comparable across sources or original terminology by enhancing data with standards-based concepts for indexing and retrieving data Common search tools and customized report formatting provide electronic access to the data