Abstract

Background: Stroke program development and expansion requires excellent patient care and continued quality improvement via ongoing data collection. Substantial time and effort are required to identify patient records and manually assess metrics within charts. While real-time assessment of this data is ideal, achieving this is challenging. Purpose: We sought to create a real-time, electronic medical record (EMR) derived patient tracking list to improve accuracy, efficiency, and timeliness of stroke patient data collection. Methods: Ischemic stroke patient identification was optimized utilizing current patient lists, which over capture, and applying filters based on EMR entries applicable to stroke patients. Patient capture was reviewed to ensure adequate sensitivity and specificity. Subsequently, key stroke quality data points were identified. Custom columns were created to pull data from across the EMR into a central list. Column data was validated to ensure accuracy and confirm improved efficiency via timed chart reviews. A Mann-Whitney test was used to compare means pre and post-review. Of note, different reviewers performed pre and post reviews. Results: A stroke tracking list was successfully implemented. Chart review in the previous process averaged 173.2 seconds (STD 40.6) vs. 121.3 seconds (STD 17.8) in the new process (p<0.05). Patient identification times were not compared, though identifying charts in the old workflow ranged from 12 to 15 minutes per chart. Conclusions: Creation of a central tracking list within the electronic medical record is feasible and can improve patient identification, coordination of critical data sharing, and data collection efficiency. Utilization decreased data collection times and prompted creation of similar tracking lists for other core measure data. While sample sizes were small and pre and post reviewers were different, this work demonstrates feasibility and early foundational work.

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