Dear Writer, good evening,

That is my POST on the discussion board. Please see how Cathy reacted 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.

Hello Delgo,

Reading your post has spurred my interest. This is one of the many statistical tests I have never heard of. Currently, I am considering the standard T-test and have been reviewing it since it has been a long while since I have delved into statistics. I do want to make sure that I understand and gain knowledge of this assignment as the exposure will help prepare for future assignments. I am at a point where the basics of the standard T-test and the additional T-test options, that include one-sample t-test, two-sample t-test, and two-sample paired t-test choices (Wadhwa & Marappa-Ganeshan, 2023), These options to choose from are usable with the quantitative choice in comparing my population between those who participate and those who do not participate in an activity over time which is what caught my attention when reading your post. Thank you for your post that caused me to further my interest in other statistical tests.