Abstract TP364: Optimization of Data Abstraction and Quality Measure Reporting using EHR

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Background and Purpose: Despite significant investment in EHR’s, most stroke centers continue to populate stroke registries, such as Get with the Guidelines - Stroke using manual abstraction. This is necessary because of a lack of EHR integration and persistence of non-discrete required data elements.Methods: American Heart Association (AHA) identified the need to offer a more interoperable version of Get with the Guidelines - Stroke (GWTG-S) as a strategic priority for 2016. AHA engaged a consultant to work with two pilot hospital locations to optimize stroke data collection in the EHR and allowing for automated data population into GWTG-S. The pilot work included: 1) Analysis of current documentation and abstraction methods to support reporting of performance data; 2) Design and implementation of improvement opportunities for a) Discrete capture of data elements for electronic reporting b) Improving clinical documentation and ordering c) Clinical decision support and d) Data structures and transmission. 3) Proof-of-concept data extract report; 4) ROI analysis for improvement opportunities and 5) Proposed implementation strategies and timelines for improvement opportunities.Results: The pilot sites implemented Epic tools including Orders, Notes, Narrators and Flowsheets to increase the percentage of discrete elements available for uploading into GWTG-S and to populate hospital quality reporting systemsConclusion: The optimization process improved stroke team ability to:1) Decrease manual abstraction, and allow the stroke team to conduct more concurrent review and handle additional patients without additional staff; 2) Quantify data collection; abstraction; and analysis processes for the emergency department team; neurology; interventional team; and stroke unit; 3) Leverage EHR tools for the clinical team to improve utilization; and 4) Demonstrated the critical collaboration between clinical operations and the information technology team.

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