A stroke is an acute cerebrovascular ischemic event likened to “Brain attack” that occurs when blood flow to an area of the brain is stopped either by obstruction or bursting of an artery causing brain cells to die from lack of oxygen (National Institute of Health [NIH], 2018). The term in-hospital stroke is used when patients who are hospitalized for different reasons suffer a stroke in the healthcare setting. Benjamin et al. (2017) noted that In-Hospital Ischemic Stroke is rapidly becoming a national concern in the United States. The disease currently accounts for 140,000 or 1 out of 20 deaths within the US, an equivalent of one stroke every 40 seconds.
Additionally, every 4 minutes someone dies of a stroke and over 795,000 strokes cases are occurring in the United States of America every year (Center for Disease Control and Prevention [CDC], 2017; Benjamin et al. (2017). In the U.S Stroke is the 5th prominent disorder leading to numerous death cases and severe disability in adults. According to CDC, stroke costs the United States around $34 billion every year (CDC 2017). In Miami-Dade County, the rate of stroke-related deaths from 2014 to 2016 for all adults aged thirty-five and older were 72.22 per every 100,000 (CDC stroke statistics 2017). With an estimation of 30,000 to 70,000 cases of in-hospital strokes in America annually, the lifespan direct and indirect costs of these ailments would be around $5 to $11 billion (Siegler & Martin-Schild 2015). At a major medical center current In-Hospital stroke assessment of Glascow Coma scales and extremity strength is not up to standards of care (American Stroke Association[ASA], 2017; CDC,2017; Shane.S, Personal Interview, May 21, 2018; The Joint Commission[TJC],2018). Therefore, a better evaluation measure was needed to be implemented to address this problem.
The National Institutes of Health Stroke Scale (NIHSS) is a measurable examination of stroke-related nervous conditions that are commonly used by many hospitals and clinical centers to evaluate stroke. The NIHSS encompasses fundamental facets of the neural investigation (Ballard et al. 2015). The NIHSS model has a verified inter-rater dependability and a prognostic legitimacy for stroke consequence. The NIHSS is widely applied in the analysis of initial and final neural disorder in severe stroke trials (Katzan et al. 2014). The CDC (2017) agrees that NIHSS is a well-acknowledged, valid and reliable scale. However, one common shortcoming associated with the NIHSS is the duration required to complete the analysis. Studies have shown that the completion of NIHSS takes 10 minutes through telemedicine compared to 7 minutes through direct-in-person completion. As a result, a modified NIHSS (mNIHSS) was developed to decreases redundancy and discount the less active and unreliable items (Ghandehari, 2013; Kwaha & Diong, 2014; McArthur, Fan, Pei, & Quinn, 2014;Wahlgren et al. 2016), When testing the validity of the mNIHSS against the previously developed NIHSS, Meyer and Lynden’s Study ( as Cited in Ghandehari, 2013) found that components of stroke scale improved reliability from 56 to 71%, while the items with low reliability decreased from 12% to 5% when using mNIHSS vs NIHSS. Additionally, the mNIHSS showed bedside reliability in both clinical trials, with telemedicine and record abstraction (Ebinger et al., 2014; Jeyaseelan, Vargo, & Chae, 2015). Therefore, According to Cumbler et al. (2014), improved reliability of mNIHSS advocates the transition from the original NHISS.
Cumbler et al. (2014) assert that in-hospital stroke patients still encounter diagnosis delays, as the nursing assessments may not be sensitive enough to detect in-hospital stroke, may be done too far apart, and providers may be lacking knowledge, this will in turn prevent early identification of stroke. (Benjamin et al., 2017; Berkhemer et al., 2015; CDC, 2017; Cumbler, 2015;2012; NIH, 2018; Saltman et al., 2015)
Project Site and Reason for Change
At a major medical center In-Hospital stroke Mortality is 5.13% exceeding the top 10% national average of 3.45%. Additionally, Length of stay is 10.69 days vs 5.03 days in top 10% hospitals. thus, stroke assessment policies not up to current TJC or ASA Standards, and No formal education in place for nurses. Additionally, the lack of an appropriate scale for evaluation has made it difficult for nurses to assess for and recognize an in-hospital stroke effectively. (American Stroke Association [ASA],2017; CDC,2017; Shane.S, Personal Interview, May 21, 2018).
Program
The purpose of this quality improvement initiative is to promote early identification of strokes within an in-hospital setting. Furthermore, the program is focused on evaluating the effectiveness of an evidence-based stroke education program and mNIHSS implementation in improving knowledge, compliance and assessment competency of nurses in stroke assessments of adult stroke patients admitted to the hospital at high risk of stroke progression, recurrent stroke, and complications.
Evaluation and Action Plan
Initially, on August 1st we began development and adaptation of mNIHSS into electronic health records(EHR). from current GCS and motor movement in collaboration with IT and the Organizational Learning department which took 4 days
. Secondly, video content was developed by the project director with assistance from Stroke and Neurological Surgery Divisions, Nursing Professional Practice, and the Organizational Learning department. The educational video entailed two providers demonstrating how to perform an assessment using the mNIHSS correctly which took approximately 5 days to shoot from august 13th, the cost incurred was be negligible as the time was donated with the video department and physician for video. Additionally, all other costs of project amounted to the total of 110 dollars for all materials. Next, the educational session started on august 27th and finished in 5 days. During which, an adapted Survey from the best EBP guidelines was provided by either the program director or a stroke nurse educator to the nurses before the educational session to verify current knowledge of stroke and mNIHSS. After education, a post-education survey with the same questions as the pre-survey was given to participants and data Stored in Qualtrics. Simultaneously, the skills check-off adapted from the mNIHSS was provided pre-education and was also given post-education, in which participants needed to achieve 100 percent competency with utilization, Participants who failed to obtain 100 percent in skills check-off after education session were given one chance to repeat the check-off and a second failure required them to repeat the educational session, all participants failed to achieve 100 percent after education. But, participants improved substantially from pre-education session. At follow up, all participants achieved 100 percent skills check, and all data was collected in Qualtrics.
Data Analysis was ran in SPSS for Knowledge for the pre-education survey and post- education survey with a paired T- Test. Additionally, one way Repeated Measures ANOVA was ran for the pre, post and follow-up skills competency with utilization. After, Chart Review Started on September 3rd for completion of mNIHSS for six weeks by the project Director to monitor for compliance and utilization of mNIHSS within hospital EHR that meets the Joint Commission standards (TJC) was done. Then, Train the trainer class took place both during In- hospital training with a stroke educator. As well as, train-the-trainer on October 15 with skills check-off. Additionally, the creation of CBL on online learning software for staff took place on Oct 22 in collaboration with the Quality department, Stroke and Neurological Surgery Divisions, Nursing Professional Practice, and Organizational Learning department to contribute to long-term sustainability through continuing education regarding stroke assessment. As well as, the use of the mNIHSS for stroke evaluation for current nurses and new hires.
Results and Limitations
During the period of analysis knowledge of Stroke and mNIHSS among nurses showed a significant difference in scores pre-education survey and post-education survey t(29 )=-9.592, p<0.001, which shows an improved knowledge after education (see Figure 1). Additionally, on competency with utilization of mNIHSS a repeated measures ANOVA with a Greenhouse-Geisser correction revealed that the pretest, posttest and follow up mean test scores differed significantly, (F(1.316,38.154) = 240.229, p = 0.0005). Post hoc tests with Bonferroni correction showed that test scores increased significantly between pretest (M =53.13, SD = 13.74) and posttest (M = 84.70, SD = 6.32) by an average of 31.57 (p =0.001). Mean test scores also increased significantly by 15.30 between posttest and follow up (M= 100.00, SD = 0.00), (p < 0.001), which shows improved competency with utilization of mNIHSS (see Figure 2). Lastly, Compliance and Completion of mNIHSS in EHR
Was reported as 90% during first 2 weeks due to systems error and inability for final score to be calculated. However, overall 100% compliance was achieved by Oct 15, 2018(see Figure 3).
One limitation of project is the number of nurses involved, in a major-medical center 30 nurses are no enough to make assumptions of the data and the future implications it has. Also, timeline also does not allow one to say compliance with completion of scale in EHR will remain at an all-time 100% and deviations may occur. Additionally, the short timeline cannot foresee whether this quality improvement initiative will promote early identification of strokes within an in-hospital setting. And thus, any assumptions are purely based on data obtained from timeframe of project.
Lessons Learned/Nursing Implications
The mNIHSS is anticipated to improve patient care significantly. Nurses will be better placed to understand if the symptom being presented by the patients warrants further investigation because of enhanced assessment capabilities. Also, the mNIHSS enables the nurses to predict the clinical outcomes, a factor which is critical in the general management of the patients. The ability of nurses to predict clinical outcomes will ultimately promote early identification of strokes within an in-hospital setting and attainment of better results for the patients.
Following implementation, nurses need to be aware of usefulness of tool and responsibilities of frequent accurate assessment of stroke patients, continuum of documentation and the importance of reporting accurate data for further in-hospital stroke evaluation. The