NR 528 Assignment: Literature Matrix Table Synthesis, Assignments of Health sciences

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Literature Matrix Table Synthesis

Chamberlain Nursing University

NR528 - Leading and Managing Evidence-Based

Change in Nursing.

In order to safeguard patient safety, nurses work to reduce the risk of falls and the harm they might cause. For the elderly population, fall-related injuries are a major health concern. Therefore, by determining fall risk factors and creating patient-specific fall prevention measures, nurses significantly improve patient safety. These fall prevention strategies aid in lowering the risk of falls and preventing injuries associated with them. Unfortunately, falls are the most prevalent cause of nonfatal injuries and the main cause of injury mortality in people aged 65 and over (Quigley et al., 2017). According to the literature matrix research, some authors have similar ideas about fall prevention strategies, while others take a different approach. The majority of the research points to common predictors and characteristics that increase a patient's risk of falling. Age, sex, care dependency, prior fall history, use of sedative and/or psychotropic medicines, and surgery are the most frequent predictors of fall risk, according to Bernet el at. (2022). Singh & Anwar (2018) suggest that awareness of prior activities should be taken into account in determining the risk for falling as well. Hou et al. (2017) and Jones et al. (2020) recommend that the accuracy and validity of the current screening tools be examined, and that staff members be given training on these fall risk assessment tools. Post training, the nursing led mobility program, in which the nurses had the ability to issue orders for activity levels and physical therapy evaluation post assessment, was launched by Jones et al. (2020), as part of a quality improvement project. Studies by other authors demonstrate various fall prevention strategies. According to Hogan et al., the application of Continuous Virtual Monitoring (CVM) in conjunction with common fall precautions showed a decrease in fall rates (2021). In order to assess and anticipate falls, Liu and Lim (2021) developed an algorithm that was integrated into the Electronic Medical Record (EMR). This system had increased accuracy the closer the assessment date got to the actual fall date. The authors of Kiyoshi-Teo et al. (2019) and Bargmann & Brundrett (2021) suggest a different method for preventing falls, in which

References Bargmann, A. L., & Brundrett, S. M. (2020). Implementation of a Multicomponent Fall Prevention Program: Contracting with Patients for Fall Safety. Military medicine, 185(Suppl 2), 28–34. https://doi.org/10.1093/milmed/usz Bernet, Everink, I. H., Schols, J. M. G., Halfens, R. J., Richter, D., & Hahn, S. (2022 ). Hospital performance comparison of inpatient fall rates; the impact of risk adjusting for patient-related factors: a multicentre cross-sectional survey. BMC Health Services Research, 22(1), 225–225. Hogan Quigley, Renz, S. M., & Bradway, C. (2021 ). Fall Prevention and Injury Reduction Utilizing Virtual Sitters in Hospitalized Patients: A Literature Review. Computers, Informatics, Nursing, 39(12), 929–934. https://doi.org/10.1097/CIN. Hou, W. H., Kang, C. M., Ho, M. H., Kuo, J. M., Chen, H. L., & Chang, W. Y. (2017 ). Evaluation of an inpatient fall risk screening tool to identify the most critical fall risk factors in inpatients. Journal of clinical nursing, 26(5-6), 698–706. https://doi-org.chamberlainuniversity.idm.oclc.org/10.1111/jocn. Jones, R. A., Merkle, S., Ruvalcaba, L., Ashton, P., Bailey, C., & Lopez, M. (2020). Nurse-Led Mobility Program: Driving a Culture of Early Mobilization in Medical-Surgical Nursing. Journal of nursing care quality, 35(1), 20–26. Kiyoshi-Teo, H., Northrup-Snyder, K., Cohen, D. J., Dieckmann, N., Stoyles, S., Winters-Stone, K., & Eckstrom, E. (2019). Older hospital inpatients' fall risk factors, perceptions, and daily activities to prevent falling. Geriatric nursing (New York, N.Y.), 40(3), 290–295. https://doi- org.chamberlainuniversity.idm.oclc.org/10.1016/j.gerinurse.2018.11. Liu, C., Hu, Y. & Lin, Y. (2021 ). A Machine Learning–Based Fall Risk Assessment Model for Inpatients. CIN: Computers, Informatics, Nursing, 39 (8), 450-459. doi: 10.1097/CIN.0000000000000727. Quigley, P., Neily, J., Watson, M., Wright, M., & Strobel, K., (2017). The Online Journal of Issues in Nursing-a scholarly Journal of the American Nurses Association. Measuring Fall Program Outcomes. Singh, Edwards, C., & Anwar, A. (2018 ). One-Year Mortality Rates Before and After Implementing Quality-Improvement Initiatives to Prevent Inpatient Falls (2012−2016). Geriatrics (Basel), 3(1), 9–. https://doi.org/10.3390/geriatrics