A folay catheter can be described as a thin, sterile, and partially flexible tube that is inserted in the urinary tract to assist in the collection of urine from the bladder (Vlock, 2014). This function is considered vital in body operations as the lack of removal of urine from the body has potentially devastating effects, such as kidney failure, that occurs as a result of the urine retracting back to the kidney hence making it highly susceptible to causing damage.
As a result, the use of catheter is considered significant, especially for patients who have undergone surgery around prostate glands, or genital area. This is because the patients’ urinal tract has not returned to its normal operations hence requiring additional support in the form of a catheter (Vlock, 2014). The folay catheter also referred to as an indwelling catheter is one that resides in the bladder. The general practitioner or the nurse inserts this through the urethra to the bladder.
However, in some instances, complications arise from the use of a folay catheter. According to Resnick and Thompson (2012), the use of an indwelling catheter is recognized as one of the most common causes of healthcare associated Urinary Tract Infections (UTI). In addition, its use has been associated with the development of other complications, such as urethra damage, bladder stones, and allergic reactions owing to the material used in the catheter, amongst others (Meisenheimer, 2014).
For this reason, a clinical analysis study is essential in a bid to understand complications associated from the use of a folay catheter. In this case, the following data analysis techniques will be adapted:
Sequential Analysis
According to Meinert (2012) this concept explains data analysis in the context of how data is analyzed based on its accumulation levels. In this case, once sufficient data has been collected, the availability of compelling statistical data stops the process. In addition, this technique accounts for a constant probability in the course of the study.
Use of Hierarchical Models
In this case, the application of these models involves a natural framework that provides for the combination of information from other clinical trials conducted. This technique is considered to be more comprehensive and reliable than compared to Meta analysis in that it is not necessary to apply magnitudes as unit measures of observation (Berthold and Hand, 2013). This method provides a foundation for the undertaking of longitudinal studies. As a result it this concept can allow for random assignment of patients to different treatments which are assessed in due course.
Bayenesian Analysis
This technique involves the application of a subjective element. In this case, it focuses on establishing the value of an unknown parameter, value q, which is used to measure experimental treatment effects (Tang and Tu, 2013).
Following my discussions with my mentor with regards to the different data analysis methods identified above, a conclusive decision was made to apply sequential analysis in the study involving consequential impact of folay catheters on surgery patients. In this case, the application of statistical analysis will provide for the allowance of data to accurate over an undefined period until when the data is deemed satisfactory. This allows the use of emerging information to be adopted in the study and stoppage of this process when satisfactory results for clear treatment are obtained.
In light of this information, it is clear there is an unprecedented need for research to be carried out in the determination of possible solutions that exist in addressing complications resulting from the use of folay catheters among surgery patients (Vlock, 2014). In this case, I plan to apply the findings in the context of research conducted through the application of relevant findings with those of previous studies carried out on the issue. As such, expert opinion will provide for the ascertainment of the underlying theory adopted in the course of the study, hence lead to substantive results that will enhance understanding of the issue under focus.
References
Berthold, M., & Hand, D. J. (2013). Intelligent data analysis: An introduction. Berlin: Springer.
Meinert, C. L. (2012). Clinical trials: Design, conduct, and analysis. New York: Oxford University Press.
Meisenheimer, C. G. (2014). Improving quality: A guide to effective programs. Rockville: Aspen.
Resnick, M. I., & Thompson, I. M. (2012). Advanced therapy of prostate disease. Hamilton.: B.C. Decker.
Tang, W., & Tu, X. M. (2013). Modern clinical trial analysis. New York; Springer Publishers
Vlok, M. E. (2014). Manual of nursing. Cape Town: Juta.
