Measuring Quality Improvement in Healthcare A Guide to Statistical Process Control Applications

ISBN-10: 0527762938
ISBN-13: 9780527762933
Edition: N/A
List price: $35.00
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Book details

List price: $35.00
Publisher: ASQ Quality Press
Binding: Paperback
Pages: 194
Size: 7.50" wide x 9.00" long x 0.75" tall
Weight: 1.144
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 Figures
List of Tables
Foreword
Preface
Acknowledgments
Planning Your CQI Journey
What Is Quality?
Who Is Interested in Quality?
A Quality Improvement Road Map
Preparing to Collect Data
Identifying an Opportunity for Improvement
Prioritizing Opportunities
Organizing a Team
Clarifying the Process with Flowcharts
Standardizing the Process
Identifying Key Quality Characteristics
Developing Operational Definitions
Data Collection
Data versus Information
Components of a Data Collection Plan
A Template for Data Collection
Understanding Variation
Depicting Variation
Common versus Special Causes of Variation
Consequences of Not Understanding Variation
Using Run and Control Charts to Analyze Process Variation
Constructing Run Charts
Using Run Charts
Using a Run Chart to Help Improve the Preadmission Testing Process
Why Use Control Charts?
The Elements of a Control Chart
Basic Control Chart Theory
Type I and Type II Errors
Dividing a Control Chart into Zones
Deciding Which Control Chart to Use
Control Chart Case Studies
Applying Statistical Thinking to Healthcare Processes
Case Studies
Analyzing the Net Operating Margin
CBC Laboratory Turnaround Time
Tracking the Success of Physical Therapy
Days to Mail a Patient Invoice
Admission Time into an Intensive Care Unit
Emergency Room Bed Transfer Time
Platelet Counts
Primary Caesarian Sections
Ranking Hospitals on Patient Satisfaction
Patient Falls
Use of Restraints with Psychiatric Patients
Medication Errors
Developing Improvement Strategies
The Type of Variation Determines Your Strategy
Right and Wrong Strategies
Changing a Common-Cause System
Tools to Identify KPVs
Continued Monitoring
How Much Improvement Is Enough?
Using Patient Surveys for CQI
A Self-Test on Survey Research
Function of Patient Surveys in CQI
Reliability and Validity
Why Is Reliability Important?
How Much Reliability Is Enough?
Sampling
Interviewer and Nonresponse Bias
Report Format
Benchmark Data
Evaluating the Effectiveness of Interventions
Summary
Formulas for Calculating Control Limits
The X-R Chart
The XmR Chart
The p-Chart
The c-Chart
The u-Chart
References
Index

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