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AMIA Jt Summits Transl Sci Proc. 2015 Mar 25;2015:127-31. eCollection 2015.

A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform.

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Vanderbilt University, Nashville, TN.
Northwestern University, Chicago, IL.
Mayo Clinic, Rochester, MN.
NorthShore University HealthSystem, Evanston, IL.


Electronic clinical quality measures (eCQMs) based on the Quality Data Model (QDM) cannot currently be executed against non-standardized electronic health record (EHR) data. To address this gap, we prototyped an implementation of a QDM-based eCQM using KNIME, an open-source platform comprising a wide array of computational workflow tools that are collectively capable of executing QDM-based logic, while also giving users the flexibility to customize mappings from site-specific EHR data. To prototype this capability, we implemented eCQM CMS30 (titled: Statin Prescribed at Discharge) using KNIME. The implementation contains value set modules with connections to the National Library of Medicine's Value Set Authority Center, QDM Data Elements that can query a local EHR database, and logical and temporal operators. We successfully executed the KNIME implementation of CMS30 using data from the Vanderbilt University and Northwestern University EHR systems.


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