Description

Book Synopsis

Learn how to improve the quality of health care offered by your institution using data you already have

Improving Health Care Quality: Case Studies with JMP teaches readers how to systematically identify problems, collect and interpret data, and solve issues in the real world. Relying on JMP software, the authors walk readers through the process of applying quality improvement techniques to real-life health care problems.

The case studies provided in the book vary significantly and provide a wide-ranging view of the application of quality improvement techniques in the health care field. Studies regarding length of stay of diabetes patients to benchmarking the costs of hip replacement all serve to illuminate and explain the underlying concepts of statistical analysis.

The authors break each case study down into several sections, including:

  • Background and Task
  • Data and Data Management
  • Analysis
  • Summary


  • Table of Contents

    Foreword xv

    Preface xvii

    Acknowledgments xix

    Acronyms and Synonyms xxi

    About the Companion Website xxiii

    1 Introduction 1

    1.1 Key Concepts 1

    1.2 Quality Improvement in Healthcare 1

    1.3 Understanding Variability: The Key to QI 2

    1.4 Quality Improvement Frameworks 3

    1.4.1 Define–Measure–Analyze–Improve–Control (DMAIC) 4

    1.4.2 Plan–Do–Check–Act (PDCA) 4

    1.4.3 Choosing a Framework 5

    1.5 Statistical Tools for Quality Improvement 6

    1.5.1 Data Visualization 8

    1.5.2 Subgrouping Data 8

    1.5.3 Control Charts 9

    1.5.4 The Importance of Assumptions 10

    1.6 Using this Casebook 11

    1.7 Summary 12

    1.7.1 Exercises 13

    1.7.2 Discussion Questions 14

    References 14

    2 Improving Patient Satisfaction 17

    2.1 Key Concepts 17

    2.2 DMAIC 17

    2.3 PDCA 17

    2.4 Background 17

    2.5 The Task 18

    2.6 The Data: ComplaintData.xlsx and PatientFeedback.jmp 18

    2.7 Data Management 19

    2.8 Analysis 20

    2.8.1 Complaint Data 20

    2.8.2 Patient Satisfaction Data 21

    2.9 Summary 26

    2.9.1 Statistical Insights 26

    2.9.2 Implications and Next Steps 27

    2.9.3 Summary of Tools and JMP Features 27

    2.9.4 Exercises 27

    2.9.5 Discussion Questions 28

    Reference 29

    3 Length of Stay and Readmission for Hospitalized Diabetes Patients 31

    3.1 Key Concepts 31

    3.2 DMAIC 31

    3.3 PDCA 31

    3.4 Background 31

    3.5 The Task 32

    3.6 The Data: HospitalReadmission.jmp 32

    3.7 Data Management 32

    3.8 Analysis 32

    3.9 Summary 39

    3.9.1 Statistical Insights 39

    3.9.2 Implications and Next Steps 39

    3.9.3 Summary of Tools and JMP Features 40

    3.9.4 Exercises 40

    3.9.5 Discussion Questions 41

    4 Identify and Communicate Opportunities for Reducing Hospital Length of Stay Using JMP® Dashboards 43

    4.1 Key Concepts 43

    4.2 DMAIC 43

    4.3 PDCA 43

    4.4 Background 43

    4.5 The Task 44

    4.6 The Data: HospitalReadmission.jmp 44

    4.7 Data Management 44

    4.8 Analysis 44

    4.8.1 Creating Dashboards with Combine Windows 44

    4.8.2 Creating Dashboards with Dashboard Builder 45

    4.8.3 Saving and Sharing JMP Dashboards 48

    4.9 Summary 48

    4.9.1 Statistical Insights 48

    4.9.2 Implications and Next Steps 52

    4.9.3 Summary of Tools and JMP Features 52

    4.9.4 Exercises 53

    4.9.5 Discussion Questions 53

    References 53

    5 Variability in the Cost of Hip Replacement 55

    5.1 Key Concepts 55

    5.2 DMAIC 55

    5.3 PDCA 55

    5.4 Background 55

    5.5 The Task 56

    5.6 The Data: SouthernTier_HipReplacement.csv 56

    5.7 Data Management 56

    5.7.1 Initial Data Review 57

    5.7.2 Adjusting JMP Column Properties 58

    5.7.3 Deleting Unneeded Columns 59

    5.7.4 Shortening Character Columns 60

    5.8 Analysis 61

    5.8.1 Descriptive Analysis 62

    5.8.2 Assessing Variability 63

    5.9 Summary 67

    5.9.1 Statistical Insights 67

    5.9.2 Implications and Next Steps 67

    5.9.3 Summary of Tools and JMP Features 68

    5.9.4 Exercises 68

    5.9.5 Discussion Questions 69

    References 70

    6 Benchmarking the Cost of Hip Replacement 71

    6.1 Key Concepts 71

    6.2 DMAIC 71

    6.3 PDCA 71

    6.4 Background 71

    6.5 The Task 72

    6.6 The Data: HipNYSPARCS_SouthernTier.jmp 72

    6.7 Data Management 72

    6.8 Analysis 73

    6.8.1 Descriptive Analysis 73

    6.8.2 Statistical Test of Hypothesis 73

    6.8.3 Confidence Interval for Mean Total Cost 75

    6.9 Summary 75

    6.9.1 Statistical Insights 75

    6.9.2 Implications and Next Steps 76

    6.9.3 Summary of Tools and JMP Features 76

    6.9.4 Exercises 76

    6.9.5 Discussion Questions 77

    References 78

    7 Nursing Survey 79

    7.1 Key Concepts 79

    7.2 DMAIC 79

    7.3 PDCA 79

    7.4 Background 79

    7.5 The Task 80

    7.6 The Data: NursingResearch_Survey_Responses.jmp 80

    7.7 Data Management 81

    7.7.1 Initial Data Review 81

    7.7.2 Recoding the Primary Role Column 83

    7.8 Analysis 85

    7.8.1 Descriptive Analysis 85

    7.8.2 One-Sample Test of Proportion 87

    7.8.3 Test for Difference of Two Proportions 88

    7.9 Summary 90

    7.9.1 Statistical Insights 90

    7.9.2 Implications and Next Steps 90

    7.9.3 Summary of Tools and JMP Features 91

    7.9.4 Exercises 91

    7.9.5 Discussion Questions 92

    References 93

    8 Determining the Sample Size for a Nursing Research Study 95

    8.1 Key Concepts 95

    8.2 DMAIC 95

    8.3 PDCA 95

    8.4 Background 95

    8.5 The Task 96

    8.6 The Data 96

    8.7 Study Design and Data Collection Methodology 96

    8.8 Analysis 97

    8.8.1 Analysis Plan 97

    8.8.2 The Basics of Sample Size Determination 98

    8.8.3 Sample Size Determination for the Bee Sting Study 99

    8.9 Summary 101

    8.9.1 Statistical Insights 101

    8.9.2 Implications and Next Steps 102

    8.9.3 Summary of Tools and JMP Features 103

    8.9.4 Exercises 104

    8.9.5 Discussion Questions 104

    References 105

    9 Mapping California Ambulance Diversion 107

    9.1 Key Concepts 107

    9.2 DMAIC 107

    9.3 PDCA 107

    9.4 Background 107

    9.5 The Task 108

    9.6 The Data: ED_ambulance_diversion_trend.xlsx and CA_healthcare_facility_locations.xlsx 108

    9.7 Data Management 108

    9.7.1 Merging the Data Tables 109

    9.7.2 Reviewing the Merged File 109

    9.7.3 Extracting General Acute Care Hospital Data 112

    9.8 Analysis 112

    9.8.1 Descriptive Analysis 112

    9.8.2 Geographic Distribution of Total Diversion Hours 113

    9.9 Summary 116

    9.9.1 Statistical Insights 116

    9.9.2 Implications and Next Steps 116

    9.9.3 Summary of Tools and JMP Features 117

    9.9.4 Exercises 117

    9.9.5 Discussion Questions 118

    References 118

    10 Monitoring Ambulance Diversion Hours 119

    10.1 Key Concepts 119

    10.2 DMAIC 119

    10.3 PDCA 119

    10.4 Background 119

    10.5 The Task 120

    10.6 The Data: CedarsSinai_Diversion_Hours.jmp 120

    10.7 Data Management 121

    10.8 Analysis 121

    10.8.1 Descriptive Analysis 121

    10.8.2 Control Chart Basics 122

    10.8.3 Ambulance Diversion Process 123

    10.8.4 Setting the Control Limits 123

    10.8.5 Monitoring Ambulance Diversion with IR Charts 126

    10.9 Summary 130

    10.9.1 Statistical Insights 130

    10.9.2 Implications and Next Steps 130

    10.9.3 Summary of Tools and JMP Features 131

    10.9.4 Exercises 131

    10.9.5 Discussion Questions 132

    References 132

    11 Ambulatory Surgery Start Times 133

    11.1 Key Concepts 133

    11.2 DMAIC 133

    11.3 PDCA 133

    11.4 Background 133

    11.5 The Task 134

    11.6 The Data: ASU.jmp 134

    11.7 Data Management 134

    11.8 Analysis 135

    11.8.1 Case 1 Analysis 138

    11.8.2 Case 2 Analysis 140

    11.9 Summary 141

    11.9.1 Statistical Insights 141

    11.9.2 Implications and Next Steps 143

    11.9.3 Summary of Tools and JMP Features 144

    11.9.4 Exercises 144

    11.9.5 Discussion Questions 145

    Reference 145

    12 Pre-Op TJR Process Improvement – Part 1 147

    12.1 Key Concepts 147

    12.2 DMAIC 147

    12.3 PDCA 147

    12.4 Background 147

    12.5 The Task 148

    12.6 The Data: TJR.xlsx 148

    12.7 Data Management 150

    12.8 Analysis 153

    12.9 Summary 159

    12.9.1 Statistical Insights 159

    12.9.2 Implications and Next Steps 161

    12.9.3 Summary of Tools and JMP Features 161

    12.9.4 Exercises 161

    12.9.5 Discussion Questions 162

    Reference 163

    13 Pre-Op TJR Process Improvement – Part 2 165

    13.1 Key Concepts 165

    13.2 DMAIC 165

    13.3 PDCA 165

    13.4 Background 165

    13.5 The Task 166

    13.6 The Data: TJR.jmp 166

    13.7 Data Management 166

    13.8 Analysis 167

    13.9 Summary 173

    13.9.1 Statistical Insights 173

    13.9.2 Implications and Next Steps 174

    13.9.3 Summary of Tools and JMP Features 174

    13.9.4 Exercises 174

    13.9.5 Discussion Questions 175

    References 175

    14 Pre-Op TJR Process Improvement – Part 3 177

    14.1 Key Concepts 177

    14.2 DMAIC 177

    14.3 PDCA 177

    14.4 Background 177

    14.5 The Task 178

    14.6 The Data: TJR.jmp 178

    14.7 Data Management 179

    14.8 Analysis 179

    14.9 Summary 187

    14.9.1 Statistical Insights 187

    14.9.2 Implications and Next Steps 188

    14.9.3 Summary of Tools and JMP Features 190

    14.9.4 Exercises 190

    14.9.5 Discussion Questions 191

    References 191

    Index 193

Improving Health Care Quality

    Product form

    £82.76

    Includes FREE delivery

    RRP £91.95 – you save £9.19 (9%)

    Order before 4pm tomorrow for delivery by Thu 2 Jul 2026.

    A Hardback by Mary Ann Shifflet, Cecilia Martinez, Jane Oppenlander

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Improving Health Care Quality by Mary Ann Shifflet

      Publisher: John Wiley & Sons Inc
      Publication Date: 05/06/2020
      ISBN13: 9781119604617, 978-1119604617
      ISBN10: 1119604613

      Description

      Book Synopsis

      Learn how to improve the quality of health care offered by your institution using data you already have

      Improving Health Care Quality: Case Studies with JMP teaches readers how to systematically identify problems, collect and interpret data, and solve issues in the real world. Relying on JMP software, the authors walk readers through the process of applying quality improvement techniques to real-life health care problems.

      The case studies provided in the book vary significantly and provide a wide-ranging view of the application of quality improvement techniques in the health care field. Studies regarding length of stay of diabetes patients to benchmarking the costs of hip replacement all serve to illuminate and explain the underlying concepts of statistical analysis.

      The authors break each case study down into several sections, including:

      • Background and Task
      • Data and Data Management
      • Analysis
      • Summary


      • Table of Contents

        Foreword xv

        Preface xvii

        Acknowledgments xix

        Acronyms and Synonyms xxi

        About the Companion Website xxiii

        1 Introduction 1

        1.1 Key Concepts 1

        1.2 Quality Improvement in Healthcare 1

        1.3 Understanding Variability: The Key to QI 2

        1.4 Quality Improvement Frameworks 3

        1.4.1 Define–Measure–Analyze–Improve–Control (DMAIC) 4

        1.4.2 Plan–Do–Check–Act (PDCA) 4

        1.4.3 Choosing a Framework 5

        1.5 Statistical Tools for Quality Improvement 6

        1.5.1 Data Visualization 8

        1.5.2 Subgrouping Data 8

        1.5.3 Control Charts 9

        1.5.4 The Importance of Assumptions 10

        1.6 Using this Casebook 11

        1.7 Summary 12

        1.7.1 Exercises 13

        1.7.2 Discussion Questions 14

        References 14

        2 Improving Patient Satisfaction 17

        2.1 Key Concepts 17

        2.2 DMAIC 17

        2.3 PDCA 17

        2.4 Background 17

        2.5 The Task 18

        2.6 The Data: ComplaintData.xlsx and PatientFeedback.jmp 18

        2.7 Data Management 19

        2.8 Analysis 20

        2.8.1 Complaint Data 20

        2.8.2 Patient Satisfaction Data 21

        2.9 Summary 26

        2.9.1 Statistical Insights 26

        2.9.2 Implications and Next Steps 27

        2.9.3 Summary of Tools and JMP Features 27

        2.9.4 Exercises 27

        2.9.5 Discussion Questions 28

        Reference 29

        3 Length of Stay and Readmission for Hospitalized Diabetes Patients 31

        3.1 Key Concepts 31

        3.2 DMAIC 31

        3.3 PDCA 31

        3.4 Background 31

        3.5 The Task 32

        3.6 The Data: HospitalReadmission.jmp 32

        3.7 Data Management 32

        3.8 Analysis 32

        3.9 Summary 39

        3.9.1 Statistical Insights 39

        3.9.2 Implications and Next Steps 39

        3.9.3 Summary of Tools and JMP Features 40

        3.9.4 Exercises 40

        3.9.5 Discussion Questions 41

        4 Identify and Communicate Opportunities for Reducing Hospital Length of Stay Using JMP® Dashboards 43

        4.1 Key Concepts 43

        4.2 DMAIC 43

        4.3 PDCA 43

        4.4 Background 43

        4.5 The Task 44

        4.6 The Data: HospitalReadmission.jmp 44

        4.7 Data Management 44

        4.8 Analysis 44

        4.8.1 Creating Dashboards with Combine Windows 44

        4.8.2 Creating Dashboards with Dashboard Builder 45

        4.8.3 Saving and Sharing JMP Dashboards 48

        4.9 Summary 48

        4.9.1 Statistical Insights 48

        4.9.2 Implications and Next Steps 52

        4.9.3 Summary of Tools and JMP Features 52

        4.9.4 Exercises 53

        4.9.5 Discussion Questions 53

        References 53

        5 Variability in the Cost of Hip Replacement 55

        5.1 Key Concepts 55

        5.2 DMAIC 55

        5.3 PDCA 55

        5.4 Background 55

        5.5 The Task 56

        5.6 The Data: SouthernTier_HipReplacement.csv 56

        5.7 Data Management 56

        5.7.1 Initial Data Review 57

        5.7.2 Adjusting JMP Column Properties 58

        5.7.3 Deleting Unneeded Columns 59

        5.7.4 Shortening Character Columns 60

        5.8 Analysis 61

        5.8.1 Descriptive Analysis 62

        5.8.2 Assessing Variability 63

        5.9 Summary 67

        5.9.1 Statistical Insights 67

        5.9.2 Implications and Next Steps 67

        5.9.3 Summary of Tools and JMP Features 68

        5.9.4 Exercises 68

        5.9.5 Discussion Questions 69

        References 70

        6 Benchmarking the Cost of Hip Replacement 71

        6.1 Key Concepts 71

        6.2 DMAIC 71

        6.3 PDCA 71

        6.4 Background 71

        6.5 The Task 72

        6.6 The Data: HipNYSPARCS_SouthernTier.jmp 72

        6.7 Data Management 72

        6.8 Analysis 73

        6.8.1 Descriptive Analysis 73

        6.8.2 Statistical Test of Hypothesis 73

        6.8.3 Confidence Interval for Mean Total Cost 75

        6.9 Summary 75

        6.9.1 Statistical Insights 75

        6.9.2 Implications and Next Steps 76

        6.9.3 Summary of Tools and JMP Features 76

        6.9.4 Exercises 76

        6.9.5 Discussion Questions 77

        References 78

        7 Nursing Survey 79

        7.1 Key Concepts 79

        7.2 DMAIC 79

        7.3 PDCA 79

        7.4 Background 79

        7.5 The Task 80

        7.6 The Data: NursingResearch_Survey_Responses.jmp 80

        7.7 Data Management 81

        7.7.1 Initial Data Review 81

        7.7.2 Recoding the Primary Role Column 83

        7.8 Analysis 85

        7.8.1 Descriptive Analysis 85

        7.8.2 One-Sample Test of Proportion 87

        7.8.3 Test for Difference of Two Proportions 88

        7.9 Summary 90

        7.9.1 Statistical Insights 90

        7.9.2 Implications and Next Steps 90

        7.9.3 Summary of Tools and JMP Features 91

        7.9.4 Exercises 91

        7.9.5 Discussion Questions 92

        References 93

        8 Determining the Sample Size for a Nursing Research Study 95

        8.1 Key Concepts 95

        8.2 DMAIC 95

        8.3 PDCA 95

        8.4 Background 95

        8.5 The Task 96

        8.6 The Data 96

        8.7 Study Design and Data Collection Methodology 96

        8.8 Analysis 97

        8.8.1 Analysis Plan 97

        8.8.2 The Basics of Sample Size Determination 98

        8.8.3 Sample Size Determination for the Bee Sting Study 99

        8.9 Summary 101

        8.9.1 Statistical Insights 101

        8.9.2 Implications and Next Steps 102

        8.9.3 Summary of Tools and JMP Features 103

        8.9.4 Exercises 104

        8.9.5 Discussion Questions 104

        References 105

        9 Mapping California Ambulance Diversion 107

        9.1 Key Concepts 107

        9.2 DMAIC 107

        9.3 PDCA 107

        9.4 Background 107

        9.5 The Task 108

        9.6 The Data: ED_ambulance_diversion_trend.xlsx and CA_healthcare_facility_locations.xlsx 108

        9.7 Data Management 108

        9.7.1 Merging the Data Tables 109

        9.7.2 Reviewing the Merged File 109

        9.7.3 Extracting General Acute Care Hospital Data 112

        9.8 Analysis 112

        9.8.1 Descriptive Analysis 112

        9.8.2 Geographic Distribution of Total Diversion Hours 113

        9.9 Summary 116

        9.9.1 Statistical Insights 116

        9.9.2 Implications and Next Steps 116

        9.9.3 Summary of Tools and JMP Features 117

        9.9.4 Exercises 117

        9.9.5 Discussion Questions 118

        References 118

        10 Monitoring Ambulance Diversion Hours 119

        10.1 Key Concepts 119

        10.2 DMAIC 119

        10.3 PDCA 119

        10.4 Background 119

        10.5 The Task 120

        10.6 The Data: CedarsSinai_Diversion_Hours.jmp 120

        10.7 Data Management 121

        10.8 Analysis 121

        10.8.1 Descriptive Analysis 121

        10.8.2 Control Chart Basics 122

        10.8.3 Ambulance Diversion Process 123

        10.8.4 Setting the Control Limits 123

        10.8.5 Monitoring Ambulance Diversion with IR Charts 126

        10.9 Summary 130

        10.9.1 Statistical Insights 130

        10.9.2 Implications and Next Steps 130

        10.9.3 Summary of Tools and JMP Features 131

        10.9.4 Exercises 131

        10.9.5 Discussion Questions 132

        References 132

        11 Ambulatory Surgery Start Times 133

        11.1 Key Concepts 133

        11.2 DMAIC 133

        11.3 PDCA 133

        11.4 Background 133

        11.5 The Task 134

        11.6 The Data: ASU.jmp 134

        11.7 Data Management 134

        11.8 Analysis 135

        11.8.1 Case 1 Analysis 138

        11.8.2 Case 2 Analysis 140

        11.9 Summary 141

        11.9.1 Statistical Insights 141

        11.9.2 Implications and Next Steps 143

        11.9.3 Summary of Tools and JMP Features 144

        11.9.4 Exercises 144

        11.9.5 Discussion Questions 145

        Reference 145

        12 Pre-Op TJR Process Improvement – Part 1 147

        12.1 Key Concepts 147

        12.2 DMAIC 147

        12.3 PDCA 147

        12.4 Background 147

        12.5 The Task 148

        12.6 The Data: TJR.xlsx 148

        12.7 Data Management 150

        12.8 Analysis 153

        12.9 Summary 159

        12.9.1 Statistical Insights 159

        12.9.2 Implications and Next Steps 161

        12.9.3 Summary of Tools and JMP Features 161

        12.9.4 Exercises 161

        12.9.5 Discussion Questions 162

        Reference 163

        13 Pre-Op TJR Process Improvement – Part 2 165

        13.1 Key Concepts 165

        13.2 DMAIC 165

        13.3 PDCA 165

        13.4 Background 165

        13.5 The Task 166

        13.6 The Data: TJR.jmp 166

        13.7 Data Management 166

        13.8 Analysis 167

        13.9 Summary 173

        13.9.1 Statistical Insights 173

        13.9.2 Implications and Next Steps 174

        13.9.3 Summary of Tools and JMP Features 174

        13.9.4 Exercises 174

        13.9.5 Discussion Questions 175

        References 175

        14 Pre-Op TJR Process Improvement – Part 3 177

        14.1 Key Concepts 177

        14.2 DMAIC 177

        14.3 PDCA 177

        14.4 Background 177

        14.5 The Task 178

        14.6 The Data: TJR.jmp 178

        14.7 Data Management 179

        14.8 Analysis 179

        14.9 Summary 187

        14.9.1 Statistical Insights 187

        14.9.2 Implications and Next Steps 188

        14.9.3 Summary of Tools and JMP Features 190

        14.9.4 Exercises 190

        14.9.5 Discussion Questions 191

        References 191

        Index 193

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