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9780873895620

Improving Healthcare With Control Charts: Basic and Advanced Spc Methods and Case Studies

by
  • ISBN13:

    9780873895620

  • ISBN10:

    0873895622

  • Edition: 1st
  • Format: Paperback
  • Copyright: 2002-09-01
  • Publisher: ASQ QUALITY PRESS

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Supplemental Materials

What is included with this book?

Author Biography

Raymond G. Carey, Ph.D., is Principal of R.G. Carey and Associates (Park Ridge, IL) He is an expert in statistical process control and survey research methods in healthcare

Table of Contents

List of Exhibits, Tables, and Figures
xi
Acknowledgments xv
Preface xvii
What Is SPC? xviii
Why Write Another Book on SPC for Healthcare? xviii
The Organization of This Book xx
Introduction xxiii
Why Do Some Healthcare Professionals Find Measuring Quality a Difficult Task? xxiii
Who Wants to See Healthcare Quality Measured? xxiv
Purchasers of Care xxiv
Accreditation Agencies xxv
Governing Bodies xxvi
General Public xxvi
Providers xxvii
Why Are Different Approaches to Measurement Needed? xxviii
Part I Using Data for Improvement: Basic SPC Theory and Methods
Basic SPC Concepts and the Run Chart
3(10)
A Simple Process Improvement Plan
3(2)
Before and After Measures
5(2)
Types of Variation
7(1)
The Run Chart
8(5)
What Is a Run Chart?
9(1)
What Is a Run``?
9(1)
What Are the Tests for a Special Cause?
9(1)
Case Study: Reducing Delays from Abnormal Mammogram to Biopsy
10(3)
Control Chart Theory Simplified
13(16)
Control Charts versus Run Charts
13(1)
Basic Elements
14(2)
Detecting Special Causes
16(3)
Should the Tests for a Special Cause Ever Be Modified?
18(1)
How Many Subgroups Are Required for a Control Chart?
19(1)
Choosing the Appropriate Control Chart
19(5)
Identifying the Type of Data
19(2)
Deciding on the Best Chart
21(3)
Case Study: Reducing Readmissions for Congestive Heart Failure
24(5)
Part II: Advanced SPC Theory and Methods
Drilling Down into Aggregated Data
29(24)
The Challenge
29(1)
Step 1. Create the Appropriate Control Chart at the Aggregate Level
30(1)
Response to Special Cause Variation
30(1)
Response to Common Cause Variation
30(1)
Step 2. Stratify All Organizational Units on the Same Control Chart
31(1)
Rational Ordering
31(1)
Rational Subgrouping
31(1)
Respond Appropriately to the Observed Variation
32(1)
Step 3. Create a Separate Control Chart for Each Organizational Unit
32(1)
Step 4. Stratify on Other Process Variables
32(2)
Case Study: Reducing C-Section Rates
34(6)
Case Study: Cycle Times for Laboratory Analysis in the Emergency Department
40(13)
Issues with Control Charts
53(18)
Determining the Number of Subgroups
53(1)
Trial Limits
54(1)
The Capability of a Process
54(2)
Histograms
54(1)
Capability Ratios
54(1)
Probability Plots
55(1)
Control Charts
55(1)
Graphical Guidelines for Constructing Control Charts
56(3)
Displaying the Raw Data
56(1)
Chart Titles
57(1)
I-Charts
58(1)
Zones versus No Zones
59(1)
Using the X-Bar and S-Chart in Place of the X-bar and R-Chart
59(3)
About the X-Bar and S-Chart
60(2)
Case Study: Improving the Post-Operative Care of Heart Surgery Patients
62(9)
Autocorrelated Data
68(3)
Limitations of Attribute Charts
71(24)
Assumption of Equal Probability
71(1)
Using I-Charts in Place of Attribute Charts
72(1)
Case Study: Neonatal Autopsies
72(2)
Skewness
74(1)
Subgroups Sizes for P-Charts
74(1)
Case Study: An HMO Evaluates Its Providers for CAGB Surgery
75(7)
Case Study: Code Blues in the ICU
82(6)
Monitoring ``Rare Events''
88(1)
Case Study: Evaluating a Bowel Surgery Pathway
89(6)
Obtaining Meaningful Data
95(16)
General Principles of Measurement
95(1)
Types of Measures
96(2)
Domains of Quality
96(1)
Outcome versus Process Measures
96(2)
Continuous Measures versus Count Measures
98(1)
Sampling Methods
98(2)
Stratified Random Sampling
99(1)
Rational Sampling
99(1)
Guidelines for Developing Indicators
100(1)
Benchmarking
101(2)
What Is Benchmarking?
102(1)
Identifying the ``Best''
102(1)
Benefits of Benchmarking
103(1)
Setting Goals and Targets
103(8)
Comparison Data
104(1)
Measuring Goal Achievement
105(6)
Part III: Special Applications of SPC Theory and Methods
Using Patient Feedback for Quality Improvement
111(20)
Patient Satisfaction versus Functional Assessment
112(1)
Uses of Patient Satisfaction Data
113(1)
Identifying Important Issues
113(1)
Measuring the Current Level of Satisfaction
113(1)
Assessing the Effect of Interventions
113(1)
Setting Goals
114(1)
Qualitative versus Quantitative Data
114(1)
Case Study: Improving Nursing Care among Inpatients
114(8)
Case Study: Improving Satisfaction with Physicians in an Outpatient Setting
122(9)
Governance and Monitoring Quality
131(20)
Organizational Structure
132(1)
Role of Governance with Respect to Quality
133(1)
Conducting Productive Meetings
134(1)
Developing a Balanced Scorecard
135(2)
Concepts
135(1)
Development Guidelines
135(2)
Displaying and Reviewing Scorecard Data
137(14)
Dashboard Displayed in Tabular Format
137(1)
Dashboard Displayed in Control Chart Format
138(8)
Historical Charts
146(2)
Multi-Charting
148(3)
Six Sigma
151(8)
What Is Six Sigma?
151(2)
Six Sigma As a Statistic
152(1)
Six Sigma As a Program
152(1)
Origin of the Six Sigma Program
153(1)
How Does Six Sigma Differ from SPC?
154(1)
Effectiveness in Healthcare
155(4)
Setting Specification Limits
155(1)
Hospital Organization versus Industry
156(1)
Improving Profitability
157(1)
SPC versus Six Sigma
157(2)
The Use of Run and Control Charts in the Improvement of Clinical Practice
159(26)
Larry V. Staker
Evaluating Baseline Performance
159(5)
Displaying the Data Graphically
164(4)
Case Study #1: Cholesterol Management
168(4)
Case Study #2: The Use of Warfarin for Anticoagulation
172(6)
Case Study #3: Diabetic Patient with Hypertension
178(3)
The Use of Control Charts in Clinical Medicine
181(1)
Summary
182(3)
Appendix SPC Software and the Formulas for Calculating Control Limits 185(2)
References 187(3)
About the Authors 190(1)
Index 191

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