NHS FPX 4000 Assessment 2 Applying Research Skills
NHS FPX 4000 Assessment 2 Applying Research Skills Name Capella university NHS FPX 4000 Developing a Health Care Perspective Prof. Name Date Applying Library Research Skills Medication errors are significant healthcare problems that severely affect patients and healthcare organizations. Medication errors are preventable events impacting patient safety due to the healthcare workforce’s wrong or inappropriate medication administration (Tariq & Scherbak, 2023). Medication errors can be due to wrong medication, wrong administration, or wrong patient, ultimately causing patient health complications and reduced patient safety. In America, medication errors account for 50,000 to 100,000 mortalities every year, making it the third major cause of death, showing its grave relevance to professional practice (Dehvan et al., 2021). In my nursing practices, I encountered several medication errors personally and watched my colleagues experience them. One particular medication error that I experienced was due to the wrong administration of a drug. The physician prescribed metoprolol on a paper-based prescription to treat a patient with high blood pressure. However, I administered metoclopramide due to juggling multiple tasks and needing a better understanding of hand-written prescriptions. This led to the onset of muscle stiffness and involuntary movements of the face and tongue in patients depicting tardive dyskinesia, a potential side effect of metoclopramide. I quickly called the physician and told them about the patient’s condition and the medication I administered, revealing that I made a medication error and appropriate measures were taken immediately to improve the patient’s health condition. Delving into research-based studies and applying research skills to healthcare practices to prevent such medication errors is vital. This assessment will discuss evidence-based review articles highlighting patient safety by minimizing medication errors through effective interventions. Identifying Academic Peer-Reviewed Journal Articles To conduct thorough research on medication errors and ways to prevent them, I used several databases such as Capella University Library, Google Scholar, CINAHL, PubMed, and ScienceDirect. Using filters and advanced search options, I used multiple keywords to gather a pool of evidence-based and peer-reviewed journal articles. The keywords mainly used were “medication errors,” “adverse drug events,” “medication reconciliation,” “safe medication administration,” and “patient safety.” From a plethora of research, I identified four academic peer-reviewed journal articles specifically relevant to medication errors and their prevention. Assessing Credibility and Relevance of Information Sources To evaluate the authenticity and relevance of research-based resources, I applied the CRAAP criteria. The CRAAP criteria is an evidence-based tool to evaluate the credibility and relevancy of research articles. It stands for Currency, Relevance, Accuracy, Authority, and Purpose. It allows researchers to apply authentic studies on a problem under study (Muis et al., 2022). The selected articles are up to date and published within the last five years. Moreover, the peer-reviewed journal articles are relevant as they contain information and research on medication errors, particularly prevention methods. Furthermore, the research-based resources provide accurate conclusions. Additionally, the authors provide valuable knowledge on medication errors with medical background and expertise. Lastly, these articles aim to decrease medication errors while enhancing patient safety (Muis et al., 2022). Annotated Bibliography Roumeliotis, N., Sniderman, J., Adams-Webber, T., Addo, N., Anand, V., Rochon, P., Taddio, A., & Parshuram, C. (2019). Effect of electronic prescribing strategies on medication error and harm in hospital: A systematic review and meta-analysis. Journal of General Internal Medicine, 34(10), 2210–2223. https://doi.org/10.1007/s11606-019-05236-8 This review article analyzes the impact of electronic prescribing strategies such as Clinical Decision Support Systems (CDDS) and Computerized Physician Order Entry (CPOE). The authors reviewed e-prescribing interventions systematically and evaluated their impact on medication errors and patient health outcomes. Various databases, including MEDLINE, CENTRAL, CINAHL, and EMBASE, were searched, and data were extracted using CPOE and CDDS. The results showed that e-prescribing strategies diminished medication errors and dosing errors. The rationale for including this article is based on the results that align with our goals of reducing medication errors in healthcare systems. Considering the results, healthcare organizations can implement the e-prescribing strategy to prevent drug errors due to dosing or prescription. Owens, K., Palmore, M., Penoyer, D., & Viers, P. (2020). The effect of implementing bar-code medication administration in an emergency department on medication administration errors and nursing satisfaction. Journal of Emergency Nursing, 46(6), 884–891. https://doi.org/10.1016/j.jen.2020.07.004 NHS FPX 4000 Assessment 2 Applying Research Skills This journal article aims to find the efficacy of Barcode Medication Administration technology (BCMA) on administration errors of medicines and nursing satisfaction. The researchers conducted a before- and after study in a local healthcare emergency department. The medication error rates were directly observed pre-and post-implementation of BCMA technology. Likewise, nursing satisfaction was assessed via a survey before and one month after BCMA integration. The results found that medication administration errors were reduced from 2.96% to 0.76%, enhancing nursing job satisfaction. The rationale for choosing this article is that it highlights the importance of integrating BCMA into healthcare systems to prevent medication administration errors by nurses, ultimately enhancing job satisfaction among nurses. Rozenblum, R., Rodriguez-Monguio, R., Volk, L. A., Forsythe, K. J., Myers, S., McGurrin, M., Williams, D. H., Bates, D. W., Schiff, G., & Seoane-Vazquez, E. (2020). Using a machine learning system to identify and prevent medication prescribing errors: A clinical and cost analysis evaluation. The Joint Commission Journal on Quality and Patient Safety, 46(1), 3–10. https://doi.org/10.1016/j.jcjq.2019.09.008 In this journal article, the authors researched utilizing a machine learning system to find and avoid medication prescribing errors. Moreover, the article aims to evaluate clinical practices and cost repercussions after using this technology-based system. The authors used MedAware, which worked on algorithms developed for identifying and preventing errors. The software showed 79.7 % of chart-reviewed alerts, of which 45% were clinically significant and prevented the onset of medication errors. The costs declined due to preventing medication errors, which were more significant than $60 per drug alert. This showed that machine learning systems have fruitful results in obtaining clinically valid medication error notifications, which traditional clinical decision support systems often miss. The reason to selected this article is because this strategy can identify medication errors beforehand and prevent them from taking place. Ultimately,