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DM Direct Special Report, January 18, 2007, By Scott Schumacher

Consider the following scenario: One night paramedics wheel a man named John K. Spenser into a hospital emergency room where admitting staff work to determine his medical history. Because the facility had not invested in an effective identity matching solution, a query of the hospital database and area medical centers does not correctly identify the patient as John K. Spencer (different spelling). To further complicate matters, because there wasn't a match, the medical staff was not aware of an important medical detail that could mean the difference between life and death: Mr. Spencer has a history of anaphylaxis, a potentially fatal allergic reaction to Penicillin and clot-busting drugs used after heart attacks.

While fictional, the previous example illustrates a potential risk of relying on inadequate data matching technologies for identification purposes. Though such technologies have improved substantially in recent years, many businesses across all industries still rely on inaccurate matching mechanisms, making their customer data integration (CDI) systems prone to serious error. In the case of healthcare, using the wrong technologies can hinder and delay treatment efforts and the ability to comply with state and federal privacy laws. Inadequate data matching methods also jeopardize companies, governments and organizations that must rapidly determine the identities of individuals. For example, the quality of the technology can mean the difference between preventing a terrorist from boarding a jet airliner and allowing one to pass undetected.

http://www.dmreview.com/editorial/newsletter_article.cfm?articleId=1071712