The nih 2018 report shows that in the united state of

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In-hospital stroke is a significant challenge in the healthcare sector. The NIH, 2018 report shows that in the United State of America (U.S.A), approximately 7% of reported strokes affect hospitalized patient every year. National Institute of Health (2018) further indicated that 6 to 15 percent of strokes occur in hospitalized patients. Nationally approximately 33,000 to 75,000 patients are likely to suffer from the stroke while in hospital. There is a significant need for detection of in-Hospital strokes, the most used approach at improvement in early stroke detection is either via a team approach towards assessment of stroke with specialized staff, or by implementation of an educational program which helps disseminate tools to improve stroke assessment in patients. There have been several scale evaluation tools developed for stroke evaluations in the literature. However, their use varies depending on the prevailing situation. For example, the NIH Stroke Scale Booklet has been used in cases of acute diseases. A different standard, the Stroke Specific Quality of Life Measure has equally been adopted but it is based on the functional assessment. The type of scale used is based on various based on clinical situations and therefore has not consistent to one particular scale ( Harrison, McArthur, & Quinn, 2013; the internet stroke center, n.d). Berkhemer et al. (2015) have affirmed that there are quality gaps which hinder the diagnostic process for in-hospital stroke. In particular, it includes increased difficulty in early detection of stroke symptoms. Goyal et al also noted, the delay between the symptom recognition and symptom onset by health professionals may affect the diagnosis process of stroke (Goyal et al. 2014). Although, the nursing assessments may not be sensitive enough to detect in-hospital stroke (Cumbler, 2012). Furthermore, assessments may be done too far apart deterring the early identification of the stroke (Cumbler et al. 2012. In-hospital stroke prediction models are
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  • Summer '16
  • Me
  • NIH, Transient ischemic attack, in-hospital stroke

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