Week 8 Discussion EBP Project Evaluation

Week 8 Discussion EBP Project Evaluation

Please note that the approved subject is Covid 19 has infested a facility in california called Kingstong Healthcare. We have been educating the staff on stopping the spread , Vaccines, dealing with Covid vaccine side effects. Week 8 Discussion EBP Project Evaluation

Statistical and Clinical Significance in EBP Projects

That the results of a research study or evidence-based practice (EBP) project are statistically significant or not is usually a question of tremendous concern for researchers and scholars. In nursing practice, however, the concern is even greater as to whether the statistically significant results of the project are also clinically significant. Statistical significance and clinical significance are not synonymous or interchangeable. However, they are not mutually exclusive either. Each can exist on their own but the two often also coexist in the same set of study or project results. This paper compares the two in the context of the EBP Covid-19 prevention project at the Kingston Healthcare facility in California.

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            Statistically significant results in a project or research study are results that have been produced by the actual interventions and manipulation of the independent variable. They are results that have actually come about from the study events alone. This means that the results are not due to chance and can be reproduced and replicated by someone else under the same set of circumstances (Ranganathan et al., 2015; Mariani & Pêgo-Fernandes, 2014). The p-value in statistics is what represents statistical significance. For instance, a p-value of 0.05 is interpreted that the likelihood of the results of a project being due to chance is only 5%. Some of the factors that facilitate statistical significance include the robustness of methodology, the size of the sample, and general internal validity of the research or project. If a project were to be influenced by confounding variables, the likelihood of the results being statistically significant will be drastically reduced. The performance of a study or project whose results end up not being statistically significant is both a waste of resources and time. This is the reason why there should be meticulous and proper planning before commencement of any change project initiative. Week 8 Discussion EBP Project Evaluation

Then there is clinical significance. Results of a study or project may be statistically significant but fail to be clinically significant. That means that their translation into actual clinical practice is impractical and unrealistic. Clinically significant results refer to research or project results that can be applied into clinical practice and produce better patient outcomes (Ranganathan et al., 2015; Mariani & Pêgo-Fernandes, 2014). In other words, project results that are clinically significant increase the body of knowledge of EBP. The results that are both statistically and clinically significant provide the scholarly evidence for efficacy of interventions that is needed to consider them EBP. When performing clinical inquiry using the PICOT model, all the scholarly peer-reviewed studies with evidence that will be selected will have two properties. Their results will first have to be statistically significant to begin with. That way, we will know that the evidence is not fallacious and produced by chance. Secondly, the findings must additionally be applicable to clinical practice and produce better patient outcomes. In other words, the evidence or study findings must also be clinically significant. This is how EBP knowledge is built. I can use clinical significance to support positive outcomes in my project by incorporating clinically significant results into daily practice. This will be done in the structures, processes, and outcomes.

References

Mariani, A.W. & Pêgo-Fernandes, P.M. (2014). Statistical significance and clinical significance. Sao Paulo Medical Journal, 132(2). http://dx.doi.org/10.1590/1516-3180.2014.1322817

Ranganathan, P., & Pramesh, C.S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in Clinical Research, 6(3), 169-170. https://doi.org/10.4103/2229-3485.159943

Covid-19 at Kingston Healthcare in California: Dependent and Independent Variables in the Evaluation of the EBP Project 

The evaluation of the EBP project at the Kingston healthcare in California will be pegged on some measurable outcomes as the benchmarks. These outcomes include the rate of Covid-19 infections post-implementation compared to re-implementation, the total mortality rate post-implementation versus pre-implementation, as well as the total number of those vaccinated against Covid-19 at the end of the implementation period of the evidence-based practice interventions. As in any research undertaking with measurable goals in mind or clear hypotheses to be tested, there are always dependent and independent variables that can be pointed out. The independent variable is usually unchanging and constant throughout the whole research or project process. However, the dependent variable will invariably change according to how the independent variable is manipulated. In a research or project situation that has both the independent and dependent variables, there are also confounding variables that are present and that must be excluded for the results obtained to be properly attributed to only the effects of the manipulation of the independent variable. Controlling confounding variables confers to the project or study statistical significance (Ranganathan et al., 2015). What this means is that the results in that project are not due to chance but due to the manipulation of the independent variable.

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Independent and Dependent Variables to be Collected and Why

In the evaluation of the evidence-based practice (EBP) project at Kingston Healthcare for reducing Covid-19 infections, the independent and dependent variables that need to be collected or considered are quite clear. More importantly, they are domiciled within the evidence-based interventions applied and the measurable outcomes used to evaluate success or failure. But before explicitly stating the variables, it is important to make clear the reasons as to why the variables need to be collected or determined. Collecting the variables will enable the proponents of the research to make sense of the data that is collected during the project. This is because there is usually a relationship between the independent and the dependent variable. It is this relationship that may provide an answer to the success or failure of the project.

The independent variable in this project is the bundled intervention that is used to prevent Covid-19 infections. The bundle is nurse-led and consists of advice on the importance of wearing face masks, keeping physical distance, getting vaccinated, and regularly washing hands. It is these that may be manipulated by the researcher to determine the effect of on the expression of the dependent variable. In our context, the dependent variable is represented by the outcomes are the determinant of actual success or failure. The relationship that exists between the interventions as the independent variable and the outcomes as the dependent variable is that interventions and their efficacy will determine if outcomes are favorable or not. Also, confounding variables are bound to affect the expression of the outcomes and must be controlled (Yegidis et al., 2018). In this case, these confounders include availability of the Covid-19 vaccines for everyone, nurse shortage, and scarcity of PPEs amongst others. For instance, if fewer doses of the Pfizer BioNTech and Moderna vaccines than expected are availed at Kingston Healthcare, the independent variable will have been inadvertently manipulated by a confounding variable. The result will be a change in the expression of the measurable outcomes (a lower number of those vaccinated against Covid-19 post-implementation).    Week 8 Discussion EBP Project Evaluation

References

Ranganathan, P., & Pramesh, C.S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in Clinical Research, 6(3), 169-170. https://doi.org/10.4103/2229-3485.159943

Yegidis, B.L., Weinbach, R.W., & Myers, L.L. (2018). Research methods for social workers, 8th ed. Pearson.

 

Topic 8 DQ 1

Based on how you will evaluate your EBP project, which independent and dependent variables do you need to collect? Why?

Topic 8 DQ 2

Not all EBP projects result in statistically significant results. Define clinical significance, and explain the difference between clinical and statistical significance. How can you use clinical significance to support positive outcomes in your project? Week 8 Discussion EBP Project Evaluation