- HIMSS 2013 Recap
We address a fundamental challenge in data management: the uncertainties and missed opportunities caused by duplicate, possibly similar, and unlinked records in a data population.
While implementing interface engine technology for hospitals in the early 1990’s, we noticed a troubling trend. As application systems became integrated and exchanged data with each other, the problems caused by duplicate and incomplete patient records (previously confined to one system and its MPI) now multiplied and contaminated the data quality of other systems!
There was no easy way to know if a system was supplying data for the exact same patient that was being inquired about. The best-of-breed approach to information technology made an existing quandary worse.
And since this technical issue could impact a patient’s health, we set out to alleviate the problem.
We developed MatchMetrix, a technology platform that invokes probabilistic and other algorithms to identify duplicate and potentially duplicate records within a single data set or across multiple data sets. All records are assigned a unique identifier that serves as an enterprise-wide universal key for accurate identification and efficient data exchange. Duplicate records are merged, related records are linked together, and all of them are indexed into a trusted, consistent, and reliable registry accessible to any authorized application or user.
We continue to develop products and solutions to help manage information with accuracy, reliability, and meaning.
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Geisinger Health System