Many systems require that information being imported from various sources about people and/or organizations be uniform and unduplicated. This initiative focuses on developing re-useable solutions for our clients which may build upon third-party products, our own tools, or a combination of the two. Solutions may contain a mixture of strategies to identify potential duplicates at the point of entry into a database, or scanning existing databases for duplicates already contained within them. This topic is relevant to both interactive and batch data entry scenarios.

HLN also provides advice on the conceptualization, development, and deployment of agency-wide de-duplication strategies and architectures.

Article

Arzt, Noam H., Strategies for Person Data Matching and De-duplication, Journal of Healthcare Information Management, 21(3), Summer 2007.

Presentations

Berry, Michael and Noam H. Arzt, RHIO Models and Public Health: How Do You Determine the Best Approach?, American Public Health Association (APHA) 134th Annual Meeting, Boston, MA, November 8, 2006.

Berry, Michael and Andres Blanco, Probabilistic Record Matching and Deduplication Using Open Source Software, 2004 Immunization Registry Conference, Atlanta, GA, October 19, 2004.

Case Study

RI Case Study in Registries for Evaluating Patient Outcomes: A User's Guide, Agency for Healthcare Research and Quality (AHRQ), AHRQ Publication No. 07-EHC001-1 page 76-77, April 2007.