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Kaiser Permanente EMRLD

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  1. From the RIMBAA 201105 Minutes Orlando minutes:
  2. Kaiser Permanente, a preliminary trial of using RIMBAA (Java SIG) to aggregate data from Epic and NHIN data sources.
    • Using MySQL and the original version of the JAVA SIG API, and also developing a Clinical Data Extraction Framework (CDEF) to extract data from Epic without having to go through Clarity (Epics relational projection), Pradeep and his group at Kaiser Permanente created a system that can capture data in real time as it is being entered into Epic, and persist it in a pure RIM database (MySQL). They have a web interface that can show the data minutes later. So far this demo project us capturing Demographic data but it will be part of a wider effort to capture all clinical data.
    • Pradeep Chowdhury from Kaiser Permanente on the EMRLD apprach for a RIMBAA data integration layer for Kaiser Permanente (see for his slides):
      • EMRLD stands for an approach for handling the data of a large enterprise.
        • E is extract. In our example them means from Epic, Pharmacy, ATD, CDA (from VA etc), Clincal devices, and various other sources. The data is extracted from all of these proprietary or native systems.
        • M is for Merge. The data is compared using mappings to standard terminology such as SNOMED so things which may appear to be different can be discovered to be the same (Warfarin and Coumadin).
        • R is for RIMify. Once we have the merged data, they are placed into a CDA like format (uses the CDA MIF file).
        • L is for Load, the data is then loaded into a pure RIM database.
        • D is for Deploy. Once we have all the data in a single RIM based persitence layer, we can use the data for many use cases. Quality reporting, decision support, research, creating new CDAs and many other things one would want pooled data for.
      • The project was built upon the HL7 Java SIG API. It sits on top of a MySQL database. The data extraction was custom built to extract data from Epic.
    • This pilot system is not in production and we hope to find funding and come back and report later on a production version.