Abstract TP34: Cerebrovascular Nursing Voice Is Critical, Information-Technology Listened, And Posterior Stroke Signs And Care Documentation Improved

• Published in: Stroke (1970) Vol. 53; no. Suppl_1; p. ATP34
• Main Authors: Ayanbadejo, Michael O, Dodda, Nick, Babu, Krishnan, Guterman, Lee, Stoll, Nancy M, Foley, Alexandria, Scarpello, Shannon
• Format: Journal Article
• Language: English
• Published: Lippincott Williams & Wilkins 01-02-2022
• ISSN: 0039-2499; 1524-4628
• DOI: 10.1161/str.53.suppl_1.TP34

IntroductionThe impact of EMR workflow template on the capture of signs of posterior circulation stroke is not well understood. The previous Stroke Unit’s EMR-workflow template at Catholic Health System had no protocol in gauging stroke clinician input in EMR-workflow sheet. In November 2020, a new EMR workflow template with protocol in gauging stroke clinician input in EMR-workflow sheet replaced the old one. We conducted a pilot study to determine the ability of the new EMR stroke template capturing signs of posterior stroke. In parallel, elbow support education and training using the new-EMR template was provided to stroke clinicians. MethodsWe conducted a retrospective chart review and a comparative analysis of patients with a CT/MRI diagnosis of posterior circulation strokes captured with the old-EMR (stroke nurses not involved in design) vs the new-EMR (stroke nurses involved) to see what EMR captured vision and balance problems. From the old EMR, we randomly selected 24 charts from June 2020 to October 2020. From the new EMR, we randomly selected 24 charts from December 2020 to April 2021 (We allowed elbow support and a learning curve of 4 weeks for the new EMR) at our comprehensive stroke center. An audit pass or fail based was assigned on the ability of the EMRs to capture vision and balance symptoms prior and after patient received stroke care. Age, sex, visual and balance symptoms of patients were documented. Data was stored in Excel and analysis was performed with Statistical Package for the Social Sciences (SPSS) version 23 for descriptive and inferential statistics. ResultApproximately 56.3% (n=27) were male. Patients’ ages ranged between 18-95 years with the mean age of 66.5 years (95% CI [61.9, 71.1]).Old-EMR stroke template captured visual 62.5% (n=15) and balance 4.2% (n=1) symptoms out of 24 charts reviewed. New-EMR template captured vision 91.6% (n=22) and balance 75% (n=18) as posterior stroke symptoms out of 24 chart reviewed. New EMR stroke template differed from old by audit pass rate (75% vs 4.2%, p < 0.00001). ConclusionThis study might suggest a relationship between nursing inputs in stroke EMR workflow design and improve documentation. We propose to carry out our study on a larger number of patients to further understand the relationships.