Stroke is the fifth leading cause of death and the number one cause of long-term disability. Seventy-five percent of annual stroke victims are older than 65. Post-stroke depression (PSD) is a common consequence of stroke, with the estimated prevalence ranging from 25% to 79%. Although several studies have investigated the impact of pharmacological interventions on PSD, there is a significant gap in knowledge regarding the efficacy of nonpharmacological measures for treatment of PSD. The purpose of the current integrative literature review was to synthesize the state of knowledge on selected nonpharmacological treatments for PSD and present findings regarding the efficacy of investigated treatments. Twenty-one studies published from 1992-2016 were identified and synthesized. Results indicated that studies demonstrating improvement in depressive symptoms included ecosystem-focused therapy, life review therapy, problem solving therapy, meridian acupressure, repetitive transcranial magnetic stimulation, music therapy, exercise, light therapy, motivational interviewing, and robotic-assisted neurorehabilitation. [Res Gerontol Nurs. 2017; 10(4):182-195.].

BACKGROUND: The incidence rate of stroke in hospitalized patients ranges between 2% and 17% of all strokes—a higher rate than in the community. Delays in recognition and management of stroke in hospitalized patients lead to worse outcomes. At our hospital, the existing in-hospital stroke (IHS) code showed low usage and effectiveness. In a quality improvement (QI) project, we aimed to improve the identification of and the quality of care for inpatient strokes. METHODS: A nurse-driven IHS protocol was implemented, which alerted a specialized stroke team and cleared the computed tomography (CT) scanner. The protocol focused on prioritizing staff education, simplifying the process, empowering staff to activate an IHS code, ensuring adequate support and teamwork, identifying well-defined quality metrics (eg, time to CT and documentation tool use), and providing feedback communication. We analyzed 2 years of postimplementation IHS data for impact on stroke detection and outcomes. RESULTS: In the 2 years post QI, there was a more than 10-fold increase in IHS (pre-QI, n = 8; first year post QI, n = 94; second year post QI, n = 123). In the post-QI cohort, after excluding patients with missing information (n = 26), 69 cases had new stroke diagnoses (63 ischemic, 6 hemorrhagic), and 148 were stroke mimics. The mean (SD) time from IHS to CT was 18.7 (7.0) minutes. Of the 63 new ischemic stroke cases, 25 (39.7%) were treated with thrombolytic therapy and/or mechanical thrombectomy. CONCLUSION: The new IHS protocol has led to a marked increase in cases identified, rapid evaluation, and high utilization rate of acute stroke therapies.

Background and Purpose: Literature suggests that recognition and management of stroke of hospitalized patients is difficult, and the morbidity and mortality rates of in-patient strokes exceed those of out of hospital stroke. Timely treatment is an important factor for a favorable prognosis for hospitalized patients suspected of having a stroke. A new protocol for in-patient stroke was implemented as a quality improvement project at our comprehensive stroke center starting January 2017. Methods: The new protocol included focused nursing education, replacement of 2-step activation process with 1-step process whereby the bedside nurse activates ‘Code Stroke’ using same criteria as used by EMS and ED triage nurses. Code Stroke activates a specialized stroke team (neurologist, ICU physicians, ICU nurses, pharmacy) and clears the CT scanner. Accurate documentation was encouraged and template notes were provided. Expectations were put forth regarding the relevant quality metrics. Feedback was provided in real-time as well as in writing, to participating care team. This analysis was done utilizing data from a prospectively maintained database of inpatient stroke, feedback communications, and chart review. The following metrics were used to examine the performance of the new process: rate of stroke symptoms identification, errors in paging, errors in documentation, time to CT, and outcome of code activation. Results: In the 6 months prior to the new protocol, a ‘Code Stroke’ was activated 5 times, only one was a true stroke and was treated with thrombectomy. In the 6 months after the new protocol, ‘Code Stroke’ was activated 46 times, with 15 confirmed strokes (14 ischemic, 1 hemorrhagic). A change in care occurred for 13 patients, including IV alteplase (n=2), thrombectomy (n=1), change in medical management (n=9), and decompressive hemicraniectomy (n=1). Mean time for Code Stroke to CT was 26 minutes despite errors in pages (wrong call back number, incorrect code designation). Conclusion: Our new process increases detection and treatment of in-patient strokes. Elements of success include system-wide organization, simplifying the process, mirroring ED process, and availability of stroke response team.