title: Challenges and Solutions in Optimizing Execution Performance of a Clinical Decision Support-Based Quality Measurement (CDS-QM) Framework.
abstract: Given the close relationship between clinical decision support (CDS) and quality measurement (QM), it has been proposed that a standards-based CDS Web service could be leveraged to enable QM. Benefits of such a CDS-QM framework include semantic consistency and implementation efficiency. However, earlier research has identified execution performance as a critical barrier when CDS-QM is applied to large populations. Here, we describe challenges encountered and solutions devised to optimize CDS-QM execution performance. Through these optimizations, the CDS-QM execution time was optimized approximately three orders of magnitude, such that approximately 370,000 patient records can now be evaluated for 22 quality measure groups in less than 5 hours (approximately 2 milliseconds per measure group per patient). Several key optimization methods were identified, with the most impact achieved through population-based retrieval of relevant data, multi-step data staging, and parallel processing. These optimizations have enabled CDS-QM to be operationally deployed at an enterprise level.
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: Tyler J
authors.initials: TJ
authors.lastname: Tippetts
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: Phillip B
authors.initials: PB
authors.lastname: Warner
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: Polina V
authors.initials: PV
authors.lastname: Kukhareva
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: David E
authors.initials: DE
authors.lastname: Shields
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: Catherine J
authors.initials: CJ
authors.lastname: Staes
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
authors.forename: Kensaku
authors.initials: K
authors.lastname: Kawamoto
mesh_terms: D020000:Decision Support Systems, Clinical; D006801:Humans; D013997:Time Factors