Abstract
Background: University of Iowa Hospitals and Clinics (UIHC) participates in American Heart Association’s Get with the Guidelines® - Stroke (GWTG) registry to help drive quality improvement. As the only Comprehensive Stroke Center in Iowa, UIHC discharges many stroke patients and experiences exponential stroke patient growth each year. Due to ever-growing patient volumes and limited staff resources, UIHC identified a need to be able to abstract more quickly and efficiently to assess patient level clinical quality and adherence to evidence-based stroke guidelines. Purpose: UIHC engaged their Information Technology (IT) Department to assist in developing a process to expedite the process and reduce the workload associated with collecting stroke data for quality improvement, with the aim of collecting data as close as possible to the episode of care. Methods: UIHC pioneered the connection between GWTG - Stroke and Epic, their electronic medical record, via a re-abstraction tool embedded in Epic. The IT team worked closely with the stroke coordinator and quality improvement team to identify efficient workflows and time saving strategies. Gaps in discrete data collection were identified and collaboration between interdisciplinary care teams commenced to standardize processes for improved charting. Results: Historically, a self-reported average of 30 minutes was spent on each patient chart in GWTG. As of August 2019, that time declined to an average of 10 minutes per chart, representing a 66% reduction in manual labor required. Prior to project implantation, lag time from patient discharge to data abstraction averaged 4 weeks. After implementing the tool, quality data is abstracted and chart review to compare the stroke care episode against current guidelines occurs while the patient is still an inpatient. Conclusions: Investing in and fostering collaboration between IT, stroke, and quality departments at UIHC led to substantial, sustainable reduction in manual work required to collect stroke quality data. Hospitals should explore their ability to create an EMR based re-abstraction tool to not only save time but improve the quality and timeliness of data collection.
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