Getting to 100%: Using Big Data to Match Patients Precisely and Cost-Effectively
For health systems and health information exchanges, the average rate of identity duplication is 10%, and the known cost to reconcile a single pair of duplicate records approaches $1,000. These organizations must identify and index patients whose information comes from an increasing number of sources that identify patients inconsistently.
Current Master Patient Indexing (MPI) solutions, however, are very costly and require extensive implementation times.
Join Brian Wikle of 4medica as he and his data management experts preview a revolutionary Big Data eMPI that is scalable, cost-effective and manageable.
Massachusetts Health Data Consortium
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For more information,please contact Arleen Colettiby email or at 781.419.7818
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