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Statistical process control for health care / Marilyn K. Hart, Robert F. Hart.
Holman Biotech Commons RA399.A1 H37 2002
Available
- Format:
- Book
- Author/Creator:
- Hart, Marilyn K., 1951-
- Series:
- Duxbury applied series
- Language:
- English
- Subjects (All):
- Medical care--Quality control--Statistical methods.
- Medical care.
- Health facilities--Evaluation--Statistical methods.
- Health facilities.
- Quality Assurance, Health Care.
- Data Interpretation, Statistical.
- Medical care--Quality control.
- Medical Subjects:
- Quality Assurance, Health Care.
- Data Interpretation, Statistical.
- Physical Description:
- ix, 343 pages : illustrations ; 24 cm.
- Place of Publication:
- Australia ; Pacific Grove, CA : Duxbury/Thomson Learning, [2002]
- Summary:
- This book teaches and illustrates the use of SPC (Statistical Process Control) techniques for healthcare professionals. SPC techniques allow these professionals to properly extract information from healthcare data, make intelligent decisions based on statistical data, and know if the data has been presented in an appropriate manner. Using a case study approach, the authors present the theory, computations (hand and computer), and application (case study) for each concept. In recent years, SPC has been proven effective in improving the quality of health care, just as it has in other service industries and in manufacturing.
- Contents:
- Understanding Variation 2
- Process Improvement 4
- Judging Whether a State of Control May Be Inferred 5
- Quality Improvement Tools 6
- Tally Sheet 6
- Pareto Chart 6
- Cause-and-Effect Diagram 7
- Flowchart 8
- Run Chart, Histogram, Probability Plot, and Control Chart 10
- Affinity Diagram 10
- Other Quality Improvement Tools 10
- Types of Data 11
- Chapter 2 Variables Data: Basics of Statistics and Graphs 15
- Population versus Sample 15
- Average 15
- Measures of Variation: Range 16
- Measures of Variation: Standard Deviation 17
- The Normal Distribution 21
- Near-Normal Distributions 22
- Histogram 23
- Probability Plot 27
- Making the Probability Plot 29
- Shape of the Distribution 30
- Chapter 3 The Run Chart for Time-Ordered Variables Data 45
- The Simplest SPC Chart: The Run Chart 45
- Time-Ordered Analysis and Single-Stream Processes 46
- Historical Analyses and Ongoing Process Monitoring: No Standard Given and Standard Given 46
- Use of a Run Chart 47
- The Interrupted Run Chart 50
- Run Charts with Other Types of Data 50
- Chapter 4 Control Chart Theory and the I Chart for Time-Ordered Data 57
- Theory Applicable to All Control Charts 57
- Variables Control Charts 59
- "T-Sigma Limits" versus 3-sigma Limits 59
- Use of the I Chart 61
- The I Chart for Process Improvement 63
- Process Improvement: Test for Results That May Suggest Nonrandom Influence 64
- The I Chart to Judge Whether a State of Control May Be Inferred 70
- Standard Given 70
- The Interrupted I Chart 74
- The I Chart with Other Types of Data 76
- Case Study 4.1 Monitoring Blood Pressure Measurements for an Individual Patient 86
- Chapter 5 The Xbar and s Chart 95
- The Xbar and s Chart with Time-Ordered Data 95
- Calculations for the Xbar and s Chart: 3-Sigma Control Limits and Constant n 96
- Tests for Nonrandom Influence 97
- Standard Given 98
- The Xbar and s Chart with Rational Subgroups 101
- Tests for Lack of Control 108
- How Not to Make Comparisons 108
- Representations of Out-of-Control Conditions 110
- Xbar and s Chart Comparanded to the Analysis of Variance 112
- Case Study 5.1 Turnaround Times for CBCs 122
- Chapter 6 Process Capability 131
- Introduction to Process Capability Estimates 131
- Process Capability from a Straight-Line Probability Plot 134
- Process Capability from a Smooth Curve Probability Plot 137
- Population Distributions and Their Probability Plots 144
- Decreasing Variability 147
- Case Study 6.1 Surgery Time 150
- Chapter 7 Using Attribute Data: The c Chart and the u Chart 157
- Using Attribute Data 157
- The c Chart 158
- The u Chart 161
- Standard Given 166
- Criteria for Evidence of Nonrandom Influence 167
- Case Study 7.1 Decreasing Anesthesia Narcotics Discrepancies 174
- Case Study 7.2 Missing Medications: New Pathway Improvement 178
- Case Study 7.3 Patient Falls 183
- Chapter 8 Using Attribute Data: The p Chart 189
- Attribute Data 189
- The p Chart 190
- Standard Given 192
- Criteria for Evidence of Nonrandom Influence 198
- p Chart Compared to Chi-Square Analysis 198
- Case Study 8.1 C-Sections 214
- Case Study 8.2 Decreasing the Medication Error Rate 229
- Case Study 8.3 Acute Appendicitis: Ultrasound Predictive Errors 233
- Case Study 8.4 Acute Appendicitis: Perforation Rates by Surgeon 238
- Chapter 9 Transformations (An Advanced Topic) 243
- The Need for Transformations 243
- Rare Events 249
- Case Study 9.1 Surgery Times: Transformations 252
- Case Study 9.2 Decreasing the Nosocomial MRSA Infection Rate 259
- Case Study 9.3 Reducing Surgical Site Infections 269
- Case Study 9.4 Surgery Complications with New Cost Savings Pathway 274
- Chapter 10 Guidelines for Making Control Charts Useful 285
- Choice of Control Chart 285
- Miscellaneous Gems 286
- Case Study 10.1 Benchmarking Time to Extubation after CABG Surgery 289
- Appendix 1 Tests for Evidence of Special-Cause Variation 301
- Appendix 2 The Perils of Pooling 311
- Appendix 3 Mathematical Relations of the Variables Control Limit Formulas 329.
- Notes:
- Includes bibliographical references (pages 337-339) and index.
- Local Notes:
- Acquired for the Penn Libraries with assistance from the Anne and Joseph Trachtman Memorial Book Fund.
- ISBN:
- 053437865X
- OCLC:
- 47863208
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