Dear Writer, good morning,

That is my POST on the discussion board. Please see how Kelly react to the POST and kindly respond to her comments or feedback. Thank you

Identifying an Appropriate Statistical Test for the Evidence-Based Practice (EBP) Project ProposalReason for Selecting Percentage Change Analysis

The percentage change analysis would be appropriate for the quantitative design (pre and post-intervention medical records audit) selected to evaluate the outcomes of the proposed intervention. This test will involve evaluating the differences in percentage in key metrics including medication errors, accurate dosing, and route selection before and after implementing the proposed pharmacologic treatment mechanism. Considering the simplicity of data interpretation and effectiveness in presenting the evidence that facilitates understanding, this method best suits the current project. Particularly, this method will allow directly comparing outcomes for pre and post-implementation of the intervention without any complex statistical measurement (Jain et al., 2019). For instance, to understand the changes in medication errors (ME) the following formula can be applied - ME = {(Errors After - Errors Before) / Errors Before} X 100. This formula can also be used to measure the other outcome metrics such as dosing accuracy and route selection accuracy.

Information Provided by the Test

The selected statistical test will provide insights into the impact of the intervention within the designated timeframe. This test will provide a quantitative measure of the improvements, stagnation, or failure of the new mechanism enabling the researcher to gauge its effectiveness in achieving the objectives of the intervention (Bronson et al., 2019). For instance, a lower percentage of medication errors will indicate improvement in patient safety practices. The information obtained from the evaluation of the data can be effectively communicated to stakeholders for further optimization of the procedures (Jain et al., 2019). Therefore, this test will not only help identify the improvements that the new intervention offers, but also enable working collaboratively towards lowering risks and improving the accuracy of medication prescription and administration.

References

Bronson, B. D., Alam, A., & Schwartz, J. E. (2019). The impact of integrated psychiatric care on hospital medicine length of stay: a pre-post intervention design with a simultaneous usual care comparison.Psychosomatics,60(6), 582-590.

Jain, M. K., Rich, N. E., Ahn, C., Turner, B. J., Sanders, J. M., Adamson, B., ... & Singal, A. G. (2019). Evaluation of a multifaceted intervention to reduce health disparities in hepatitis C screening: a prepost analysis.Hepatology,70(1), 40-50.

Delgo, I really enjoyed reading your post. I was not familiar with percentage change analysis before reading your post and appreciate that you explained it so well. You taught me a lot!While I decided to go with a paired t-test for my project, I also believe that this analysis would be useful in measuring the outcome metrics. I plan to remember this statistical method for possible future projects and perhaps as an additional measurement in my project. Thank you and best of luck!