How Statistical Data Influences Evidence-Based Practice

Evidence-based practice (EBP) is defined as the conscientious, judicious, and explicit use of current best evidence to make decisions about patient care. EBP incorporates the best available evidence in order to guide nursing care and improve patient outcomes. This will assist health practitioners to address health care questions by using an evaluative and qualitative approach. EBP is a problem-solving approach to clinical practice and involves the search for and critically appraising the most relevant evidence, one\\\\'s clinical experience and the preferences of the patient (Fortunato, Grainger, & Abou-El-Enein, 2018). The process involved in EBP allows the practitioner to assess research, clinical guidelines, and other information resources that are based on high-quality findings and apply the results obtained to improve their practice.
Since EBP heavily relies on research and searching for available evidence to support a hypothetical question in order to solve a current problem, it is vital that one understands and interprets statistical data that is presented in the research articles that they are evaluating. A majority of the articles or evidence that will be used in EBP will contain statistical information that should be interpreted and fully understood in order to justify using the stated approach to change clinical practice within a healthcare facility. Therefore, understanding statistical data will be highly beneficial to the individual conducting the research for EBP. With a proper understanding of statistical data, one is able to assess the quality of the studies and the validity of the conclusions made by the researchers (Castellanos, Castillo, Lukyanenko, & Tremblay, 2017). This is beneficial to EBP because one has to rely solely on the evidence presented by others in order to support their justification or push for a change in policy or practice. As earlier stated, EBP relies on the evidence presented by others. Therefore, it is vital that one can be able to deduce the vital information from the data presented by others in order to make a case for their hypothesis.
Statistical data is secondary data and this makes it cheaper and less time consuming to analyze, and this is beneficial to EBP in that one can use different studies and show how they have used the same approach and proven that it is beneficial to have a particular practice (Wang, Kung, & Byrd, 2018). There are numerous patterns and correlations that one can uncover when they are using statistical data. These patterns can be beneficial to EBP because they can assist to support the decision making of the individual especially in cases where others are questioning their decision making. There are various concepts that are presented by statistical data and understanding these concepts will assist one to understand the findings that one reads in the studies they intend to appraise and use in their evaluation. Using the presented concepts, one can be able to choose and interpret the appropriate tests that that can use for their evaluation findings.
In order to ensure that one has followed the correct EBP process, there is need to them to properly search for evidence that is relevant to their current question. There will be numerous results that they will receive when conducting their search, but they have to drill down to the researches that focus on their particular question. The only way one can determine the relevance of a study to their question is by understanding the data presented in the study and the interpretation made by the researchers. This will ensure that they do not miss some relevant information and they are able to appraise the studies properly. Statistical data influences EBP in that EBP relies heavily on the data presented from the studies selected to support the question being asked.


References
Castellanos, A., Castillo, A., Lukyanenko, R., & Tremblay, M. C. (2017). Understanding Benefits and Limitations of Unstructured Data Collection for Repurposing Organizational Data. Paper presented at the EuroSymposium on Systems Analysis and Design.
Fortunato, A., Grainger, D. W., & Abou-El-Enein, M. (2018). Enhancing patient-level clinical data access to improve trial outcomes, promote evidence-based practice and incentivize therapeutic innovation. Advanced Drug Delivery Reviews.
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.