Improving Healthcare with Control Charts Basic and Advanced SPC Methods and Case Studies

ISBN-10: 0873895622
ISBN-13: 9780873895620
Edition: 2002
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Book details

List price: $44.00
Copyright year: 2002
Publisher: ASQ Quality Press
Binding: Hardcover
Pages: 223
Size: 7.25" wide x 10.50" long x 0.75" tall
Weight: 3.300
Language: English

Emil J. Posavac (Ph.D., University of Illinois, Champaign) is Professor Emeritus of Psychology at Loyola University of Chicago where he served as director of the Applied Social Psychology Graduate Program and chairman of the Psychology Department. He has consulted with a number of public and private organizations. He has published over sixty papers and chapters, edited or co-edited six volumes on program evaluation and applied social psychology, and written numerous evaluation reports for health care and educational institutions. He has written a textbook (with Eugene B. Zechmeister) on statistical analysis based on emerging orientations that emphasize a more complete understanding and presentation of data. In 1990, he was awarded the Myrdal Award by the American Evaluation Association for his contributions to the advancement of program evaluation practice. Since retirement he has taught at the University of Rochester (Simon Graduate School of Business), Rochester Institute of Technology, and Trevecca Nazarene University. He teaches English as a Second Language at his church in Franklin, Tennessee.

List of Exhibits, Tables, and Figures
Acknowledgments
Preface
What Is SPC?
Why Write Another Book on SPC for Healthcare?
The Organization of This Book
Introduction
Why Do Some Healthcare Professionals Find Measuring Quality a Difficult Task?
Who Wants to See Healthcare Quality Measured?
Purchasers of Care
Accreditation Agencies
Governing Bodies
General Public
Providers
Why Are Different Approaches to Measurement Needed?
Using Data for Improvement: Basic SPC Theory and Methods
Basic SPC Concepts and the Run Chart
A Simple Process Improvement Plan
Before and After Measures
Types of Variation
The Run Chart
What Is a Run Chart?
What Is a "Run"?
What Are the Tests for a Special Cause?
Case Study: Reducing Delays from Abnormal Mammogram to Biopsy
Control Chart Theory Simplified
Control Charts versus Run Charts
Basic Elements
Detecting Special Causes
Should the Tests for a Special Cause Ever Be Modified?
How Many Subgroups Are Required for a Control Chart?
Choosing the Appropriate Control Chart
Identifying the Type of Data
Deciding on the Best Chart
Case Study: Reducing Readmissions for Congestive Heart Failure
Advanced SPC Theory and Methods
Drilling Down into Aggregated Data
The Challenge
Create the Appropriate Control Chart at the Aggregate Level
Response to Special Cause Variation
Response to Common Cause Variation
Stratify All Organizational Units on the Same Control Chart
Rational Ordering
Rational Subgrouping
Respond Appropriately to the Observed Variation
Create a Separate Control Chart for Each Organizational Unit
Stratify on Other Process Variables
Case Study: Reducing C-Section Rates
Case Study: Cycle Times for Laboratory Analysis in the Emergency Department
Issues with Control Charts
Determining the Number of Subgroups
Trial Limits
The Capability of a Process
Histograms
Capability Ratios
Probability Plots
Control Charts
Graphical Guidelines for Constructing Control Charts
Displaying the Raw Data
Chart Titles
I-Charts
Zones versus No Zones
Using the X-Bar and S-Chart in Place of the X-bar and R-Chart
About the X-Bar and S-Chart
Case Study: Improving the Post-Operative Care of Heart Surgery Patients
Autocorrelated Data
Limitations of Attribute Charts
Assumption of Equal Probability
Using I-Charts in Place of Attribute Charts
Case Study: Neonatal Autopsies
Skewness
Subgroups Sizes for P-Charts
Case Study: An HMO Evaluates Its Providers for CAGB Surgery
Case Study: Code Blues in the ICU
Monitoring "Rare Events"
Case Study: Evaluating a Bowel Surgery Pathway
Obtaining Meaningful Data
General Principles of Measurement
Types of Measures
Domains of Quality
Outcome versus Process Measures
Continuous Measures versus Count Measures
Sampling Methods
Stratified Random Sampling
Rational Sampling
Guidelines for Developing Indicators
Benchmarking
What Is Benchmarking?
Identifying the "Best"
Benefits of Benchmarking
Setting Goals and Targets
Comparison Data
Measuring Goal Achievement
Special Applications of SPC Theory and Methods
Using Patient Feedback for Quality Improvement
Patient Satisfaction versus Functional Assessment
Uses of Patient Satisfaction Data
Identifying Important Issues
Measuring the Current Level of Satisfaction
Assessing the Effect of Interventions
Setting Goals
Qualitative versus Quantitative Data
Case Study: Improving Nursing Care among Inpatients
Case Study: Improving Satisfaction with Physicians in an Outpatient Setting
Governance and Monitoring Quality
Organiaztional Structure
Role of Governance with Respect to Quality
Conducting Productive Meetings
Developing a Balanced Scorecard
Concepts
Development Guidelines
Displaying and Reviewing Scorecard Data
Dashboard Displayed in Tabular Format
Dashboard Displayed in Control Chart Format
Historical Charts
Multi-Charting
Six Sigma
What Is Six Sigma?
Six Sigma As a Statistic
Six Sigma As a Program
Origin of the Six Sigma Program
How Does Six Sigma Differ from SPC?
Effectiveness in Healthcare
Setting Specification Limits
Hospital Organization versus Industry
Improving Profitability
SPC versus Six Sigma
The Use of Run and Control Charts in the Improvement of Clinical Practice
Evaluating Baseline Performance
Displaying the Data Graphically
Cholesterol Management
The Use of Warfarin for Anticoagulation
Diabetic Patient with Hypertension
The Use of Control Charts in Clinical Medicine
Summary
SPC Software and the Formulas for Calculating Control Limits
References
About the Authors
Index

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