Application: Analysis of Quantitative and Qualitative Data
Application:
Analysis of Quantitative and Qualitative Data
In order to provide meaningful results, research processes must be carefully selected and appropriate for the data being analyzed. Statistical programs such as SPSS are frequently utilized by researchers to conduct the analysis of large data sets. These data are organized to provide meaningful interpretation and often include descriptive statistics. Qualitative analysis is completed using content analysis, looking for patterns and themes that emerge from the data. Individual experiences described in interviews and focus groups are considered data and are often provided as examples to support the results in the study publication. Whether you will engage in either quantitative or qualitative research, it is likely that you will encounter both types of studies in the literature. As a nursing professional, being able to analyze and interpret both types of research designs will be important to affect nursing practice that promotes positive health outcomes in
quality of care and patient safety.
For Part 1 of this Assignment, you will conduct descriptive statistical analyses using quantitative data. For Part 2 of this Assignment, you will conduct content coding to analyze qualitative data. Please review the Instructions: Quantitative Analysis Assignment and Instructions: Content Coding of Student Pet Peeves in this week’s resources to review how to complete both parts of this Assignment.
Part 1: Quantitative Analyses
Follow the step-by-step instructions provided in the Instructions: Quantitative Analysis Assignment document in this week’s resources on using the Excel program to conduct descriptive analyses of quantitative data.
The Quantitative Data Excel Assignment spreadsheet that you will need is in the resources for this week.
For this Assignment, you will need to describe the findings from your analyses and summarize what they tell you about these patients and the extent of the adverse events they experienced during their hospitalization by completing the Summary Data Analysis Form in this week’s resources.
Part 2: Qualitative Analyses
Follow the step-by-step instructions provided in the Instructions: Content Coding of Student Pet Peeves document in this week’s resources. The document provides detailed instructions on the step-by-step process of conducting the content analysis for this part of the Assignment.
Access the Perceived Pet Peeves Data document located in this week’s resources that includes the narrative descriptions of 10 students about their “pet peeves’ in courses they have taken. (In other words, what are the things that detracted from their learning experiences in these courses)?
The analytic method you will use to analyze the narrative data for this Assignment is called content analysis. It requires you to read each student’s narrative and then code its content using thematic categories on a coding sheet.
Access the Code Sheet: Student Pet Peeve Data document located in this week’s resources to carry out the coding as defined in the instructions.
For the written part of this assignment, you will need to describe the most common types of “pet peeves” that students have about their courses.
submit both part 1 and 2 component
The week 5 assignment includes Part I and Part II.
2018Quantitative_SummaryDataAnalysisForm_Week5.docx
Follow the step-by-step instructions provided in the Instructions. The Quantitative Data Excel Assignment spreadsheet that you will need is in the resources for this week. Do not submit the Excel spreadsheet.
Write the analysis using the guidelines in the AWE. Begin with a brief introduction to the data set. Double space, one inch margins, page numbers, 12 font and Times Roman. The template has been formatted. Note that the summary should be at least 350 words and two to three paragraphs.
Use the Summary Data Analysis Form in this week’s resources to complete the assignment. First include your mean age and percentages you calculated on the first section and underneath write your analysis and then submit. Submit the analysis form and the summary as one file in docx.
Begin with a brief summary of the data set. Write a short paragraph for each variable and include the percentage and then discuss possible additional information needed to decrease the occurrence of adverse patient safety events. What this means is you will include what additional data or information would you like to collect to develop a plan to decrease each of the adverse events. You are not including a plan rather what you need for each variable to better develop the plan to decrease adverse events.
Note: the analysis is based on the summary percentages of the data set for Falls, CAUTI, Medication Errors, MRSA and the mean age.
Assignment 2: Qualitative Analyses.
Complete the Coding Table then underneath the table summarize the findings. Submit coding table and summary as one file as a docx.
Tips for writing up the analysis
Begin with a brief introduction
For the written part of this assignment, you will need to name and describe the most common types of “pet peeves” or the three most common themes that students have about their courses. Briefly include how you determined the most common types of pet peeves based on the content analysis. I suggest a short paragraph for each theme that includes the above. Make sure to clearly identify each theme. End the summary with as brief conclusion.
Use AWE writing expectations: Write in double spacing and use paragraphs, Times Roman, 12 font, indent paragraphs. Include resources to support your points and ideas. Include a reference page if references used in the summary. No more than one-two pages.
See attached form to complete and submit week 5 assignment 2.
2018CodeSheet_PetPeeveData_Week5.doc
Quantitative Analysis of Patient Safety Data Set in Hospital Facilities
Student’s Full Name
Walden University
Course Number, Section, and Title
(Example: NURS 3150 Section 01, Foundations of Nursing Research)
Month, Day, Year
(enter the date submitted to instructor)
Week 5: Quantitative Analysis Assignment
Summary Data Analysis Form
This is the form you need to use to describe the findings (or results) of your quantitative analyses of the patient safety data set. For each finding, you are given specific instructions on how to use the Excel program to analyze the data that will give you the results you need for this Assignment. When you have completed the analyses and described your findings on this form, you then need to submit it using the Week 5 platform for assignments.
Analysis 1:
What is the mean age of patients in the patient safety data set?
__54.8___ years
Analysis 2:
What percentage of patients were reported to have fallen during their hospitalization?
___38__ %
Analysis 3:
What percentage of patients reported catheter-associated urinary tract infections (CAUTIs) during their hospitalization?
___24__ %
Analysis 4:
What percentage of patients reported medication errors during their hospitalization?
__30___ %
Analysis 5:
What percentage of patients reported methicillin-resistant Staphylococcus aureus (MRSA) infections when first admitted to the medical unit?
___14__ %
Data Analysis
Patient safety has always been one of the main concerns of healthcare facilities. Despite the number of stringent safety measures utilized by these facilities, a lot of different risks such as falls, infections, and incorrect medication could worsen the patients’ conditions much further. In this study, these risks are analyzed based from a report of the number of such the occurrences within a major hospital in an urban area. Specifically, these reports focus on two medical units of the same facility. To get a wholistic idea, not only of these risks, but also other factors that are associated with it (i.e., demographic variables), some of the additional data taken and analyzed were; (1) age, (2) number of falls within the hospitalization period, (3) CAUTI cases, (4) treatment associated errors, and (5) the number of MRSA (methicillin-resistant Staphylococcus aureus) infections. Each of these cases would be discussed separately in the succeeding sections.
Age
Upon an analysis of the ages of the population of respondents (n=50), it would show that the mean age (average age) would fall at 54.8 years old. Since this data is taken among patients through random sampling, then this increases the ‘representativity’ of the population towards the general population of the patients within the healthcare facility. Nonetheless, it could be seen that these ages vary greatly (min= 18; max = 93), which also increases the population’s variance CITATION Hay19 \l 13321 (Hayes, 2019). Consequently, a high variance could lessen the predictability of the effects of ‘age’ in assessment based on this variable.
Falls
An analysis of the data set would also show that cases of patients falling is another risk that is yet to be addressed in the hospital setting. Particularly, it was shown that 38% of the said population has experienced ‘during’ the course of their hospitalization. This is significantly higher as compared to the average number of falls within hospital setting, which is “3.3 to 11.5 falls ...
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