EXPLAIN WHETHER YOU WOULD SELECT A QUALITATIVE OR QUANTITATIVE DESIGN TO COLLECT DATA AND EVELUATE THE EFFECTIVENESS OF YOUR EVIDENCE-BASED PRACTICE PROJECT PROPOSAL NUR 590
EXPLAIN WHETHER YOU WOULD SELECT A QUALITATIVE OR QUANTITATIVE DESIGN TO COLLECT DATA AND EVELUATE THE EFFECTIVENESS OF YOUR EVIDENCE-BASED PRACTICE PROJECT PROPOSAL NUR 590
Explain whether you would select a qualitative or quantitative design to collect data and evaluate the effectiveness of your evidence-based practice project proposal. Identify which data collection tool you would specifically use and explain why this design is best for your evidence-based practice project proposal.
My PICOT: In patients with a central line (P), does use of a central line care bundle (I), when compared to no use of a central line care bundle (C), lead to lower central line associated blood infection (CLABSI) rates (O), over the course of three months (T)?
Careful identification of study intentions and meaningful data collection is an essential piece in the evidence-based practice study design process. Though daunting, statistics “play a key role in health and human related research… statistical analysis assists in arriving at right conclusions which then promotes generalization or application of findings to the whole population of interest in the study,” (Rebekah & Ravindran, 2021, p 62). My PICOT intervention aims to reduce the rate of CLABSI occurrence over the course of three months. This quantitative evaluation leads me to design a quantitative evidence-based practice study that considers the numbers and rates of CLABSI occurrence and whether or not implementing a standard bundle will effectively reduce these. Additionally, statistical analysis is essential to give meaning and a story behind a great deal of numbers, with ultimate positive impact on patient popultaion outcomes (Rebekah & Ravindran, 2021). Inferential statistics allow for statistical analysis of data collected to then draw conclusions from specific interventions or scenarios.
My PICOT data collection does not require an intermediate or advanced statistical software. Instead, I would use an Excel document to collect information on a randomized control trial approach to patient information, whether or not the intervention of a central line care bundle was implemented or not, and if CLABSI rates were seen to be decreased compared to those without use of a central line care bundle. This would need to be done with access to patient health records in EPIC, to review documentation as well as nurse interventions actually being performed with this patient group. Using basic excel formulas, analysis is able to be performed on this somewhat simple comparison (Rebekah & Ravindran, 2021). I anticipate the largest challenge will be identifying those who will participate in the study, and if it can be done in a randomized fashion.
References
Rebekah, G. & Ravindran, V. (2021). Statistical analysis in nursing research. Indian Journal of Continuing Nursing Education, 19(1), p 62-69.
In the evidence based research project I am proposing, observing the effect that education has on physical health changes such as weight loss in order to decrease obesity rates may be best suited in a quantitative research design. This is because collecting body measurements would include physical number categorizing as well as identifying nutritional amounts in meals could be an important factor in evaluating if certain types of educational content are more effective than others (Metzgar & Nickols-Richardson, 2016). In order to collect quantitative data for the research project, the best data collection tool I believe would provide sufficient data for evidence based practice would be through survey. Surveys would be the most realistic option as my project setting would be set within the education department working with outpatient and public avenues (Lallukka, Pietilaeinen, Jaeppinen, Laaksonen, Lahti & Rahkonen, 2020). Controlled environments would cost too much resources to sustain and surveys that would include questions about changes in measurements what what type of foods being consumed within the time frame would provide data that can show direct correlation with less cost making them more efficient. However I would only distribute surveys for evaluation for those who have actively been contacted to participate in the project instead of using national surveys or general public ones.
References:
Lallukka, T., Pietilaeinen, O., Jaeppinen, S., Laaksonen, M., Lahti, J., & Rahkonen, O. (2020). Factors associated with health survey response among young employees: a register-based study using online, mailed and telephone interview data collection methods. BMC PUBLIC HEALTH, 20(1). https://doi-org.lopes.idm.oclc.org/10.1186/s12889-020-8241-8
Metzgar, C. J., & Nickols-Richardson, S. M. (2016). Effects of nutrition education on weight gain prevention: a randomized controlled trial. Nutrition Journal, 15, 1–13. https://doi-org.lopes.idm.oclc.org/10.1186/s12937-016-0150-4
My PICOT: In patients with a central line (P), does use of a central line care bundle (I), when compared to no use of a central line care bundle (C), lead to lower central line associated blood infection (CLABSI) rates (O), over the course of three months (T)?
Careful identification of study intentions and meaningful data collection is an essential piece in the evidence-based practice study design process. Though daunting, statistics “play a key role in health and human related research… statistical analysis assists in arriving at right conclusions which then promotes generalization or application of findings to the whole population of interest in the study,” (Rebekah & Ravindran, 2021, p 62). My PICOT intervention aims to reduce the rate of CLABSI occurrence over the course of three months. This quantitative evaluation leads me to design a quantitative evidence-based practice study that considers the numbers and rates of CLABSI occurrence and whether or not implementing a standard bundle will effectively reduce these. Additionally, statistical analysis is essential to give meaning and a story behind a great deal of numbers, with ultimate positive impact on patient popultaion outcomes (Rebekah & Ravindran, 2021). Inferential statistics allow for statistical analysis of data collected to then draw conclusions from specific interventions or scenarios.
My PICOT data collection does not require an intermediate or advanced statistical software. Instead, I would use an Excel document to collect information on a randomized control trial approach to patient information, whether or not the intervention of a central line care bundle was implemented or not, and if CLABSI rates were seen to be decreased compared to those without use of a central line care bundle. This would need to be done with access to patient health records in EPIC, to review documentation as well as nurse interventions actually being performed with this patient group. Using basic excel formulas, analysis is able to be performed on this somewhat simple comparison (Rebekah & Ravindran, 2021). I anticipate the largest challenge will be identifying those who will participate in the study, and if it can be done in a randomized fashion.
References
Rebekah, G. & Ravindran, V. (2021). Statistical analysis in nursing research. Indian Journal of Continuing Nursing Education, 19(1), p 62-69.
