Week 5: Quantitative Analysis Assignment Codebook: Quantitative Patient Safety Data Column Variable Name A ID B C AGE GENDER D UNIT Description Unique patient identification number Age of patient in years Sex of patient Inpatient hospital unit Primary diagnosis of patient when admitted to medical unit E DX F FALLS G CAUTI H RXERR I MRSA Reported fall during hospitalization Reported catheter-associated urinary tract infection Reported medication error during hospitalization Reported methicillin-resistant Staphylococcus aureus (MRSA) infection 2016 Laureate Education, Inc. Response Categories 1 = female; 2 = male 1 = medical unit 1 2 = medical unit 2 1 = congestive heart failure 2 = pneumonia 3 = chronic obstructive pulmonary disease 4 = diabetes 5 = R/O myocardial infarction 6 = other 0 = no fall 1 = fell 0 = no CAUTI 1 = CAUTI 0 = no medication error 1 = medication error 0 = no MRSA 1 = MRSA infection Page 1 of 1 Week 5: Qualitative Analysis Assignment Instructions: Content Coding of Student Pet Peeves Content coding is one way to identify the themes or patterns found in the narrative text of qualitative research studies. The qualitative research assignment for Week 5 requires you to content code the narrative pet peeves of 10 nursing and social work students taking courses in a \"brick and mortar\" university. These students were asked to anonymously describe the problems (or \"pet peeves\") they experienced in previous courses that detracted from their learning experience. To complete this assignment, you need the three documents: the student narrative text on pet peeves, the code scheme, and the code sheet. Below is a description of each of these documents. Student Narrative Text on Course Pet Peeves (Page 3): You will see the narrative text written by each of the 10 students in this document. Each student has a unique identification (ID) number. For example, 001 is the ID number of the first student and 010 is number for the last student. Some students only wrote about one pet peeve, whereas others listed up to two or more pet peeves. If a student listed two or more pet peeves, a \"vertical bar\" | is used to separate each them. Take a look at the student whose ID number is 002. This student's first pet peeve about course readings is separated from the second one by a vertical bar ( | ). Coding Scheme: Student Pet Peeve Data (Page 4): A code scheme has unique numbers linked to different types of content or themes found in narrative text. For this assignment, you will see a unique number for each different type of pet peeve. For example, a pet peeve on not being able to locate required readings is assigned the number \"01\". Sometimes the content of narrative text cannot be categorized, because it is unclear or doesn't make sense. For this assignment, this type of narrative text is given the code number \"99\". If narrative text is not a pet peeve, it is given the code number \"97\". Code Sheet: Student Pet Peeve Data (Page 5): This is the form that you use to enter the code scheme number for each pet peeve in a student's narrative text. The first column of the code sheet lists the student's unique ID number. The next column (Code 1) is used to write the number from the code scheme that best describes the content of the first pet peeve listed by the student. The second column (Code 2) is for the second pet peeve, and the third column (Code 3) is for the last one. 2016 Laureate Education, Inc. Page 1 of 5 Example Here is an example of how to code the narrative text on course pet peeves. In this example, the student described the following pet peeves in courses she had taken in the past: 186 Assignments that are just \"busy work\" with no perceived value. | Lack of feedback. ID First, the number \"186\" is the unique ID number for this student. When you code this student's pet peeves, you need to write them on the line for this ID number. Codes Next you will see a vertical bar | in the narrative text on page 3 which means there are more than one pet peeve listed by the student. Code Sheet Example (Refer to Coding Scheme page 5) The first pet peeve is about assignments that are considered to be \"busy work\". When you review the code scheme for student pet peeves, it looks like the number \"08\" (Assignments not geared to learning [e.g., busy work]) best describes this student's pet peeve. You then enter the number \"08\" into the second column (Code 1) of the code sheet (see below). In the next pet peeve, the student writes about \"lack of feedback\". While her response is not very specific, it is most likely to related to code number \"13\" (Assignments returned without comments or feedback). You then enter \"13\" in the third column of the code sheet. Because this student did not list a third pet peeve, you then leave the fourth column (Code 3) blank. Code Sheet: Student Pet Peeve Data ID # Code 1 Code 2 186 08 13 Code 3 You are now ready to start content coding the narrative text of pet peeves for the 10 students in this assignment on page 3. When you are finished, you need to submit your completed code sheet on page 7 to the submission link in Week 5. 2016 Laureate Education, Inc. Page 2 of 5 Week 5: Qualitative Analysis Assignment Student Narrative Text on Course Pet Peeves 001 Professors who \"don't allow\" students to disagree with their opinions. | Professors who grade based on the placement of commas and the number of spaces typed between words rather than on the ideas and thoughts developed. Professors who give me reason to feel about 2 inches tall when I give an incorrect answer to a question. | 002 Ridiculous amounts of reading to be done in a short period of time. | Not having an opportunity to discuss different viewpoints or different facets of a topic-issue. 003 I get frustrated with instructors that behave as though we have nothing else going on in our lives except their class and their assignments. 004 I don't like to read material that doesn't have a practical benefit. I want to leave here with a marketable skill, not a head filled with historical facts or scientific jargon. 005 Students who use the classroom to show how smart they are and to build themselves up. | Those who rattle their candy and gum wrappers or chip bags. 006 When required readings are not available. | When instructors put-down students. | When assignments are too difficult. 007 Professor who believe their view is the only one acceptable. | Disorganized classes. | Dry readings. | 008 Professors who are condescending toward students. Test questions that come out of the blue. 009 People make noise - opening snacks, chewing loud (pretzels). When people monopolize class. 010 Allowing personal bias to dictate evaluations of students work. (e.g., If you disagree, then you're wrong.) | When expectations for grades are unclear. 2016 Laureate Education, Inc. | Page 3 of 5 Week 5: Qualitative Analysis Assignment Coding Scheme: Student Pet Peeve Data Course Requirements 01 = Can't locate required readings 02 = Unclear expectations of students 03 = Unrealistic expectations of students (e.g., too many readings, assignments too difficult) 04 = Working in groups (e.g., too much, meaningless) 05 = Course doesn't follow syllabus Course Content 06 = Content of required readings (e.g., irrelevant, inappropriate, boring, dry) 07 = No clinical, policy or real-life application of course content 08 = Assignments not geared to learning (e.g., busy work) 09 = Too little time spent on the most important topics Teacher - Student Relationship 10 = Teacher doesn't encourage students to voice opinions that are different from their own 11 = Teacher talks down to students (e.g., condescending, makes students feel stupid) 12 = Teacher has low expectations of students (e.g., intelligence, experience, ability to complete assignments) Teaching Behavior 13 = Assignments returned without comments or feedback (e.g., papers) 14 = Personality of teacher (e.g., opinionated, egotistical, arrogant, thinks their approach is the only way) 15 = Unfair or inappropriate grading (e.g., papers, exams, final grades) 16 = Poor facilitator of class discussions Student Behavior 17 = Students who monopolize class time 18 = Irrelevant comments or discussions by other students (e.g., personal stories) 19 = Limited or no development of peer relationships with classmates 20 = Overbearing, intimidating, and/or opinionated students 21 = Students making noises in class (e.g., rattling papers, unwrapping food) 98 = Other: Student's written response not a pet peeve or doesn't fit coding scheme 99 = Unable to decipher meaning of student response 2016 Laureate Education, Inc. Page 4 of 5 Week 5: Qualitative Analysis Assignment Code Sheet: Student Pet Peeve Data Qualitative Analyses: 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 the thematic categories on page 4 (Coding Scheme: Student Pet Peeve Data). Once you have completed the coding, you will need to describe the most common types of \"pet peeves\" that students have about their courses. ID # CODE 1 CODE 2 CODE 3 001 002 003 004 005 006 007 008 009 010 After you complete the code sheet, summarize the major themes or most common pet peeves described by the 10 students in their previous courses: 2016 Laureate Education, Inc. Page 5 of 5 Week 5: Qualitative Analysis Assignment Student Narrative Text on Course Pet Peeves 001 Professors who \"don't allow\" students to disagree with their opinions. | Professors who grade based on the placement of commas and the number of spaces typed between words rather than on the ideas and thoughts developed. Professors who give me reason to feel about 2 inches tall when I give an incorrect answer to a question. 002 Ridiculous amounts of reading to be done in a short period of time. | Not having an opportunity to discuss different viewpoints or different facets of a topic-issue. 003 I get frustrated with instructors that behave as though we have nothing else going on in our lives except their class and their assignments. 004 I don't like to read material that doesn't have a practical benefit. I want to leave here with a marketable skill, not a head filled with historical facts or scientific jargon. 005 Students who use the classroom to show how smart they are and to build themselves up. | Those who rattle their candy and gum wrapper or chip bag. 006 When required readings are not available. | When instructors put-down students. | When assignments are too difficult. 007 Professor who believe their view is the only one acceptable. | Disorganized classes. | Dry readings. 008 Professors who are condescending toward students. | Test questions that come out of the blue. 009 People make noise - opening snacks, chewing loud (pretzels). When people monopolize class. 010 Allowing personal bias to dictate evaluations of students work. (i.e. if you disagree then you're wrong.) | When expectations are unclear for grades. | | 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? _____ years Instructions: a) Open up your patient safety data set using the Microsoft Excel program. b) At the top of your screen, click on \"Formulas.\" c) Highlight Column B, starting at line 2 and ending at line 52. d) Click on \"Autosum,\" and then click on \"Average.\" e) You will find the mean age of patients in the data set on line 52 for Column B. Analysis 2: What percentage of patients were reported to have fallen during their hospitalization? _____ % Instructions: a) Open up your patient safety data set using the Microsoft Excel program. b) At the top of your screen, click on \"Formulas.\" c) Highlight Column G, starting at line 2 and ending at line 52. d) Click on \"Sum.\" e) The number of patients in the data set who had reported falls during their hospitalization is now given on line 52 for Column G. f) To calculate the percentage of patients who fell during their hospitalization, divide the number of falls by the total number of patients in the data set (n = 50). Analysis 3: What percentage of patients reported catheter-associated urinary tract infections (CAUTIs) during their hospitalization? _____ % Instructions: a) Open up your patient safety data set using the Microsoft Excel program. b) At the top of your screen, click on \"Formulas.\" c) Highlight Column H, starting at line 2 and ending at line 52. 2016 Laureate Education, Inc. Page 1 of 2 d) Click on \"Sum.\" e) The number of patients in the data set who reported CAUTIs during their hospitalization is now given on line 52 for Column H. f) To calculate the percentage of patients with CAUTIs during their hospitalization, divide the number of CAUTIs by the total number of patients in the data set (n = 50). Analysis 4: What percentage of patients reported medication errors during their hospitalization? _____ % Instructions: a) Open up your patient safety data set using the Microsoft Excel program. b) At the top of your screen, click on \"Formulas.\" c) Highlight Column I, starting at line 2 and ending at line 52. d) Click on \"Sum.\" e) The number of patients in the data set who reported medication errors during their hospitalization is now given on line 52 for Column I. f) To calculate the percentage of patients with reported medication errors during their hospitalization, divide the number of errors by the total number of patients in the data set (n = 50). Analysis 5: What percentage of patients reported methicillin-resistant Staphylococcus aureus (MRSA) infections when first admitted to the medical unit? _____ % Instructions: a) Open up your patient safety data set using the Microsoft Excel program. b) At the top of your screen, click on \"Formulas.\" c) Highlight Column J, starting at line 2 and ending at line 52. d) Click on \"Sum.\" e) The number of patients in the data set who reported MRSA infections at the beginning of their hospitalization is now given on line 52 for Column J. f) To calculate the percentage of patients with MRSA, divide the number of errors by the total number of patients in the data set (n = 50). Summarize the findings from your analyses about these patient safety events that occurred in 1 month on the two medical units at this major urban hospital. What additional information would you need to help develop a plan to decrease the occurrence of these events? (Follow AWE level 2000/3000 writing expectations.) 2016 Laureate Education, Inc. Page 2 of 2 Week 5: Qualitative Analysis Assignment Code Sheet: Student Pet Peeve Data ID # CODE 1 CODE 2 CODE 3 001 002 003 004 005 006 007 008 009 010 After you complete the code sheet, summarize the major themes or most common pet peeves described by the ten students in their previous courses: ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ 2016 Laureate Education, Inc. Page 1 of 1 Week 5: Quantitative Analysis Assignment Instructions: Quantitative Analysis Assignment For the Week 5 quantitative analysis assignment, you will need to conduct basic descriptive analyses about the frequency of patient safety incidents during one month on two medical units in a major urban teaching hospital. To complete this assignment, you will need the following three documents: (a) Excel Spreadsheet: Quantitative Patient Safety Data, (b) Codebook: Quantitative Patient Safety Data, and (c) Summary Data Analysis Form. Below is a description of each of these documents: (a) Excel Spreadsheet: Quantitative Patient Safety Data: The quantitative data for this assignment has been entered into an Excel spreadsheet which can be accessed using the Excel software that is part of the Microsoft Office suite of applications. This type of spreadsheet is called a rectangular file because it is arranged in columns and rows. Each column is a different variable in the data set. For example, Column A (ID) is the identification number variable for patients, and Column B (AGE) is the variable on patient age in years. Each row has data (or information) for each individual patient for each of the variables in the columns. To clarify this, look at the date set for this assignment. You will see that the patient in row 2 has an ID number 001 (Column A) and is 22 years old (Column B). The patient in row 44 has an ID number 43 is 75 years old. (b) Codebook: Quantitative Patient Safety Data: A codebook is used in quantitative research to define the variables (or columns) in a data set and the response categories for each of these variable. Looking at the codebook for this assignment, you will see that the second column in the codebook is the name of variables in the data set. Usually the variable names are abbreviated (e.g., DX stands for primary diagnosis upon admission). Next to each variable name is its description and its response categories. As an example, look at the variable called FALLS. Next to this variable is its description which is defined as whether or not a patient had an accidental fall during the hospitalization. The response categories for the variable FALLS is either \"0\" which means the patient did not fall or \"1\" which means the patient did fall. To further clarify this, take a look at Column G on your Excel spreadsheet which is labelled as FALLS. The term \"falls\" can mean many different things, such as a person accidentally falling at home or a waterfall (e.g., Snoqualmie Falls). The codebook for a quantitative data set gives the specific definition of a variable. In this assignment, the variable FALLS means a patient fall that is reported during a hospitalization. Now look at the numbers in the column underneath FALLS. You will only see the numbers \"0\" or 1 \"1\". In the codebook, these are the response categories for the variable FALLS with 0 = no fall and 1 = fall occurred. Now that you know about the rows and columns of a rectangular data set, you are ready to conduct some basic analyses that summarize (or aggregate) information about the 50 patients in the patient safety data. (c) Summary Data Analysis Form: This form provides guidelines on how to conduct the required quantitative analyses for this assignment and how to report your findings. When you complete your analyses, you need to submit this completed form using the Week 5 platform for submitting assignments. 2 Week 5: Qualitative Analysis Assignment Student Narrative Text on Course Pet Peeves 001 Professors who \"don't allow\" students to disagree with their opinions. | Professors who grade based on the placement of commas and the number of spaces typed between words rather than on the ideas and thoughts developed. Professors who give me reason to feel about 2 inches tall when I give an incorrect answer to a question. 002 Ridiculous amounts of reading to be done in a short period of time. | Not having an opportunity to discuss different viewpoints or different facets of a topic-issue. 003 I get frustrated with instructors that behave as though we have nothing else going on in our lives except their class and their assignments. 004 I don't like to read material that doesn't have a practical benefit. I want to leave here with a marketable skill, not a head filled with historical facts or scientific jargon. 005 Students who use the classroom to show how smart they are and to build themselves up. | Those who rattle their candy and gum wrapper or chip bag. 006 When required readings are not available. | When instructors put-down students. | When assignments are too difficult. 007 Professor who believe their view is the only one acceptable. | Disorganized classes. | Dry readings. 008 Professors who are condescending toward students. | Test questions that come out of the blue. 009 People make noise - opening snacks, chewing loud (pretzels). When people monopolize class. 010 Allowing personal bias to dictate evaluations of students work. (i.e. if you disagree then you're wrong.) | When expectations are unclear for grades. | |