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Assessing Adherence to Updated Inpatient Code Stroke Protocol via Code Stroke Times
Abstract
Problem & Purpose: At a community hospital in Baltimore, it was found that the inpatient code stroke (CS) protocol was not consistently and promptly enacted upon presentation of stroke signs and symptoms on the med-surg and cardiac units. The average time from the last known normal (LKN) to CS was 154 min (no benchmark), from CS to imaging was 15.4 min (benchmark <20 min), and from CS to intervention was 55 min (benchmark <30 min). After conducting stakeholder interviews and chart reviews, it was identified that the inpatient CS protocol was not followed regularly, used medical jargon, and had steps lacking directional flow. This impacted both staff and inpatients who experience stroke symptoms, as delays in identification delay treatment. The purpose of this quality improvement (QI) initiative was to assess adherence to a revised, evidence-based, inpatient CS protocol assessed by code stroke times. With information collected from existing evidence, it was found that revising inpatient CS protocols improves code stroke times. Methods: The revised protocol was developed by the project lead. Then, education was provided to staff, the protocol was posted, and data collection began. Meetings, educational handouts, unit champions, and quality monitoring were strategies used to refine new practices. Staff education and CS data were entered into REDCap using surveys and CS documentation. Results: Staff rated familiarity increased from 71.4% to 90.7% after education. Neurological assessment completion went from 85% to 84% after implementation. Time from LKN changed from 154 min to 110 min and code stroke activation to CT image from 15.4 min to 15.6 min. No stroke interventions were done during the project period. Conclusions: The protocol revision was a cost-effective solution for improving staff familiarity with CS protocol and improving time from LKN to CS activation. Various extraneous factors impacted code stroke times and can be evaluated further in future QI projects to improve code stroke times and outcomes.Identifier to cite or link to this item
http://hdl.handle.net/10713/22876Collections
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