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The Efficacy of Central Venous Catheters

Introduction

The significance of Central Venous Catheters (CVC) in providing patients with an opportunity to receive the necessary nutrition after a complicated surgery can hardly be underrated (Stanley, ‎Veith, ‎& Wakefield, 2014). However, traditionally, the PICC tools are preferred to the rest of the options. However, studies show that PICC cannot be deemed as efficient as they expose patients to even greater risks, including the threat of a thrombosis (Martin, Fanaroff, & Walsh, 2014). Therefore, a detailed overview of the tools above needs to be carried out to determine their efficacy and suggest tools for the further improvement of the nursing services.

Matrix

Data Review

The application of Central Venous Catheters (CVC) is typically viewed as the primary tool for addressing the problem in question. However, the fact that the Peripherally Inserted Central Catheters (PICC) has recently been considered an option needs to be brought up.

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The data located in the course of the analysis, however, has shown that the application of PICC is fraught with numerous challenges. Particularly, the possible complexities emerging as a result of the surgery need to be brought up as the essential roadblocks on the way to promoting innovation in the designated area.

It should be borne in mind that, due to the possible flaws of the PICC system, it is often dismissed as a tool that lacks credibility. Moreover, most of the arguments against the use of PICC in addressing cardiovascular disorders (CVD) boil down to the need for testing the approach before it is considered a trustworthy tool. Herein the significance of a detailed study on the subject matter lies. The location of the methods that will allow for the best application of the PICC tool, as well as a detailed assessment of the advantages and disadvantages thereof, is a crucial step in improving the services provided to patients with nutrition issues (Kelly, 2014).

Data Type

When considering the data type, one must admit that the use of both qualitative and quantitative information is crucial to the veracity of the research outcomes and the usability thereof. Particularly qualitative information should be used to identify the avenues that can be taken to improve the current services for the patients with nutrition issues. Similarly, the identification of the primary characteristics of both approaches, i.e., the PICC and its current alternative, needs to be conducted with the help of qualitative analysis (Sandrucci & Mussa, 2012).

The comparison of the two strategies, in its turn, will need to be carried out based on the quantitative data retrieved in the course of the research. It is essential to quantify the information obtained in the process so that the efficacy of PICC and its alternative could be identified. Further comparison, therefore, will become possible once numerical data is introduced. Particularly, a statistical test will have to be adopted.

Data Analysis Process

As has been stressed above, the analysis of the opportunities that the PICC framework provides will have to be completed with the help of statistical analysis. Particularly, one will have to consider ANOVA is one of the most appropriate options for comparing the available variables and evaluating their effect on each other. Seeing that the efficacy of the tools used in the course of the corresponding treatment can be viewed from several perspectives and is affected by more than one factor, it will be necessary to adopt a two-way ANOVA test. By definition, the above tool will help measure the variance between the variables and, therefore, confirm if they have a reciprocal effect on each other. The qualitative analysis process, in its turn, will have to be carried out with the help of an elaborate coding technique. A set of codes will be designed so that the information retrieved could be assessed correspondingly (Vogt, Gardner, & Haeffele, 2014).

Data Integration Plan

The data can be incorporated into the research with the help of the IBM statistical tools. The project will benefit significantly from the use of an efficient tool for statistical data analysis, which the IBM software can be defined as. Often credited for the wide array of tools for quantitative data analysis that it has to offer, the specified inventory is likely to have a great influence on the credibility and trustworthiness of the research outcomes.

Conclusion

It is expected that the plan provided above will allow for a major improvement of the nursing strategies applied to the management of nutrition-issues-related disorders, in general, and the administration of the CV procedure, in particular. There is no need to stress that, when considering the surgeries related to CVC, one makes the patient’s life hinge on the strategy adopted by the nurse. Herein lies the significance of identifying the pros and cons of the currently adopted approaches in the specified environment. Particularly, the usage of PICC should be considered closed as a possible improvement of the nursing services provided to patients with CVC.

The matrix charted above shows quite clearly that the application of PICC has its problems, as well as a rather impressive potential in terms of improving the patient’s recovery rates and increasing the overall chances for the success of the surgery. Therefore, a more detailed analysis of the options that the adoption of PICC opens in front of a patient needs to be conducted.

Reference List

Kelly, M. (2014). Nutrition in critical illness, an issue of critical nursing clinics. New York, NY: Elsevier Health Sciences.

Martin, R. J., Fanaroff, A. A., & Walsh, M. C. (2014). Fanaroff and Martin’s neonatal-perinatal medicine: Diseases of the fetus and infant. New York, NY: Elsevier Health Sciences.

Sandrucci, S., & Mussa, B. (2012). Peripherally inserted Central Venous Catheters. New York, NY: Springer.

Stanley, ‎J. C., Veith, F., ‎& Wakefield, T. W. (2014). Current therapy in vascular and endovascular surgery. New York, NY: Elsevier Health Sciences.

Vogt, P. V., Gardner, L. M., & Haeffele, E. R. (2014). Selecting the right analyses for your data: quantitative, qualitative, and mixed methods. New York, NY: Guilford Publications.