Abstract 55: Improved Efficiency, Analysis And Reporting Of Stroke Data By Automating Manual Data Extraction With Stroke Specific Data Fields Built In The Electronic Health Record

Abstract

Data collection and analysis is essential for stroke center certification, registries and as a public responsibility. When large amounts of data need to be extracted, manual data collection is extremely time consuming. The existing challenge for stroke centers is leveraging technology for efficient data collection and analysis. The purpose of this project was to improve efficiency, analysis and reporting of stroke data by automating manual data extraction with stroke specific data fields built in the electronic health record. The data collected would create individual patient summaries, data reports and a stroke dashboard. The method chosen to accomplish this was by using data moved through an EPIC Clarity Database, our Enterprise Data Warehouse Suite of products, Subject Area Mart (SAM) and Instant Data Entry Application (IDEA app) and 5 SSRS Reports. Use of the innovative IDEA app allows for updating data behind the scenes. This 8-month collaborative project included IT support from a project manager, quality analyst, Power BI developer and SAM/data layer developer. This project resulted in over 250 discrete data points and 25 separate dashboard tabs, including volume, demographics, stroke metrics and outcomes. System-wide stroke data over a 10-month period included an overall volume of 2,814 patients, with 280 receiving tPA or thrombectomy. The option to run individual patient summaries and 5 different auditing reports was included. Estimated staff time savings is over 50 hours per month. In conclusion we have demonstrated it is possible to pull discrete data points from the electronic health record to be used in a dashboard, patient summaries and stroke data reports. The biggest challenge was dividing the large scope of work into manageable stages. A next step is to pull in EMS data through health data exchange. Streamlining data collection and analysis efficiency is essential for the future of a stroke center of excellence.