Implementation of an Evidence-Based Barcode Technology and Simulation Education Training to Reduce Medication Error Rate in an Adult Geriatric Psychiatric Unit In Urban Connecticut

Implementation of an Evidence-Based Barcode Technology and Simulation Education Training to Reduce Medication Error Rate in an Adult Geriatric Psychiatric Unit In Urban Connecticut. Review “Lies, Damned Lies and Statistics: Clinical Importance Versus Statistical Significance in Research,” located in topic materials below…

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Paper details

  • Review “Lies, Damned Lies and Statistics: Clinical Importance Versus Statistical Significance in Research,” located in topic materials below:
  • Mellis, C. (2018). Lies, damned lies and statistics: Clinical importance versus statistical significance in research. Paediatric Respiratory Reviews25, 88–93. https://doi.org/10.1016/j.prrv.2017.02.002
  • URL:
  • https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1526054217300088&site=eds-live&scope=site&custid=s8333196&groupid=main&profile=eds1
  • Provide examples of how you addressed feasibility and statistical versus clinical significance in your proposal. For example, why did you select a four-week time frame for your project versus a power analysis? Did you select this because it was feasible? Why or why not and explain.
  • What is the difference between clinical and statistical significance and why are both important to the patient improvement outcomes of your project?
  • My new project topic is below, and please look at my data collection and analysis, and data procedures for changes to help answer the questions. 
  • Implementation of an Evidence-Based Barcode Technology and Simulation Education Training to Reduce Medication Error Rate in an Adult Geriatric Psychiatric Unit In Urban Connecticut

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Solution

Clinical and Statistical Significance

Statistical significance relates to the reliability of the study’s results with measures of statistical significance indicating the probability of the results being due to chance or normal variation (Mellis, 2018). Clinical significance refers to the magnitude of the treatment effect, which determines whether the results are likely to impact on current medical practice. In particular, statistical significance underlines the certainty of an actual relationship between the variables analyzed in the study.

In my DPI, statistical significance should indicate that the change in the medication error rate is due to actual variance between pre-test and post-test results and not by chance. On the other hand, clinical significance provides the subjective interpretation of findings as meaningful to patient improvement outcomes. As such, clinical significance would indicate that the results of the project are crucial to care, and could guide the provision of care to patients.

In my DPI, I addressed statistical significance by upholding a set alpha value of 0.05. Hence a p-value less than 0.05 is statistically significant thereby indicating strong evidence against the null hypothesis, as there is less than a 5% probability the null is correct. I will clinical significance by focusing on the impact the treatment effect would have on patient outcomes.

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The selection of the 4-week time frame was based on feasibility. It is imperative to test the effect of the intervention within a duration that allows an effective measure of the impact. However, prospective power analysis could help determine the sample size where the project would need to measure the effect size through a Cohen’s d measure, with the large effect size for Cohen’s d is 0.80 or higher (Brownlee, 2018). The alpha value would be 0.05 and use a statistical power of 0.8, to find the sample size required to have a high statistical power and attain a significant effect size.

References

  • Brownlee, J. (2018). A Gentle Introduction to Statistical Power and Power Analysis in Python. Retrieved 25 September 2020, from https://machinelearningmastery.com/statistical-power-and-power-analysis-in-python/
  • Mellis, C. (2018). Lies, damned lies and statistics: Clinical importance versus statistical significance in research. Paediatric Respiratory Reviews, 25, 88–93. https://doi.org/10.1016/j.prrv.2017.02.002

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