Abstract NS24: Algorithm Development to Improve Transient Ischemic Attack Outcomes
Background and Purpose: Management of care for the patient experiencing a transient ischemic attack (TIA) is inconsistent and compromises patient outcomes. This is due to the absence of a clearly defined protocol for TIA aimed at expediting care to reduce delays in diagnosis and treatment. The purpose of this study was to establish an evidence-based method for early identification, assessment, and consistent treatment of TIA.
Methods: A TIA algorithm was designed and implemented based on translation of current evidence. Effectiveness of the algorithm was determined by comparing two separate groups using secondary data analysis of patients presenting to emergency department triage diagnosed with TIA six months prior to implementation of the algorithm (n= 80) and six months following implementation (n= 67). Patients in the implementation group received the evaluation and treatment outlined in the algorithm as the new standard of care. Primary outcomes were analyzed using a Chi-Square test of independence to evaluate recurrent ischemic events post-index TIA and independent samples t-tests for measuring length of stay (LOS) and total direct costs of care.
Results: Significant reductions in overall direct costs of care [t (121) = 7.23, p = .001, d = 1.20] and LOS [t (142) = 2.40, p = .018, d = 0.40] associated with consistency in diagnostic testing and patient disposition were found. Recurrent TIA [X2 (1, N = 147) = 1.52, p=.22, r2 = 0.01] and stroke [X2 (1, N = 147) = 2.83, p=.093, r2 = 0.02] events post-index TIA were noted within the implementation group. Although not significant in this sample size, the clinical importance of findings demonstrated a 7.2% difference in overall stroke events with no recurrence of TIA as evaluated at 2, 30, 60, and 90-day time intervals.
Conclusions: Findings from this study demonstrated that the use of a TIA algorithm was successful in guiding the interdisciplinary team to impact outcomes for the patient at risk for stroke. Recommendations for further testing of the algorithm in a multi-site cohort study would allow for a larger sample to evaluate this disease specific care model.
Author Disclosures: M. Marshman: None.
- © 2015 by American Heart Association, Inc.