The primary interest of the project is to determine changes in medication errors. Statistical tests in research are selected based on the objectives. Statistical. Data evaluating the relationship between variables (causal effects), data changes over time, and hypothesis testing require specific statistical tests. Tests such as ANOVA, t-test, and chi-squares help understand the variables’ changes and their relationships (Rebekah & Ravindran, 2018).
Zheng et al. (2021) note that the BCMA technology targets medication administration errors by confirming all medication administration rights at the dispensing point. The technology may affect other medication errors at dispense and prescription, but the primary interest is medication administration errors. The interest statistical test must be able to test changes in variables of time/ at different times.
The selected statistical test is the ANOVA test. The test helps evaluate the changes in variables concerning each other. They test the significance of results and thus help reject or accept the null or alternate hypothesis. The project aims to determine if barcode medication administration reduces medication administration errors. The statistical cost interest should help determine the relationship between BCMA administration and changes in medication errors. Data before and after BCMA should be compared to determine their similarities and differences.
The ANOVA test will be vital because data will be collected and analyzed at different times. The analysis will help determine the differences in medication (Rebekah & Ravindran, 2018). The ANOVA test is used when testing a hypothesis and evaluating the effectiveness of interventions. The ANOVA will help test the changes in the various variables over time. The changes in the variables, medication error rate, and their relationship to other medication errors will help evaluate the effectiveness of the interventions.
References
Rebekah, G., & Ravindran, V. (2018). Statistical analysis in nursing research. Indian Journal of Continuing Nursing Education, 19(1), 62. https://www.ijcne.org/text.asp?2018/19/1/62/286497
Zheng, W. Y., Lichtner, V., Van Dort, B. A., & Baysari, M. T. (2021). The impact of introducing automated dispensing cabinets, barcode medication administration, and closed-loop electronic medication management systems on work processes and safety of controlled medications in hospitals: A systematic review. Research in Social and Administrative Pharmacy, 17(5), 832-841. https://doi.org/10.1016/j.sapharm.2020.08.001
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