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Abstract Details
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Activity Number:
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424
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #301585 |
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Title:
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The Valence Bond - A Bayesian Approach To Patient Linking
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Author(s):
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Brandon Barber*+ and Bart Phillips
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Companies:
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Valence Health
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Address:
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600 W Jackson Blvd, Ste. #800, Chicago, IL, 60611,
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Keywords:
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Linking Algorithm ;
Bayes ;
Member Identification ;
Clinical Integration
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Abstract:
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As US healthcare increasingly stresses data sharing and interoperability, the need to accurately and efficiently link patients from disparate data sources will intensify. Use of social security numbers as means of medical identification, however, is a dwindling trend and without an unambiguous patient identifier, challenges will abound regarding patient linkage. We propose that a patient identification system reliant on common claim-driven information and independent of SSN will meet our needs to link records over sources such as laboratory, hospital, and practice management systems. Our Bayesian approach to probabilistic linking matches claim lines based on a user-defined degree of certainty and a minimum amount of blocking for computation practicability. We support our method through a series of posterior distribution analyses based on potential user-defined degrees of certainty.
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