The Health Care Data Guide : Learning from Data for Improvement.

Format:

Book

Author/Creator:

Provost, Lloyd P.

Contributor:

Murray, Sandra.

Language:

English

Subjects (All):

Medical care--Quality control--Statistical methods.

Medical care -- Quality control -- Statistical methods.

Medical care--Quality control--Data processing.

Medical care -- Quality control -- Data processing.

Physical Description:

1 online resource (481 pages)

Edition:

1st ed.

Place of Publication:

Hoboken : John Wiley & Sons, Incorporated, 2011.

Summary:

Lloyd P. Provost is a cofounder of Associates in Process Improvement, the developers of the Model for Improvement roadmap and the Quality as a Business Strategy template for focusing organizations on improvement. Lloyd is a senior fellow at the Institute for Healthcare Improvement, where he supports the use of data for learning in programs. Sandra K. Murray is a principal in Corporate Transformation Concepts, an independent consulting firm. She is faculty for the Institute for Healthcare Improvement's year-long Improvement Advisor Professional Development Program and their Breakthrough Series College. Sandra has taught numerous programs through the National Association for Healthcare Quality. Her active cohort of client organizations encompasses the spectrum of health care delivery.

Contents:

Intro

The Health Care Data Guide: Learning from Data for Improvement

Contents

Figures, Tables, and Exhibits

Preface

The Authors

Part I: Using Data for Improvement

Chapter 1: Improvement Methodology

Fundamental Questions for Improvement

What Are We Trying to Accomplish?

How Will We Know That a Change Is an Improvement?

What Changes Can We Make That Will Result in Improvement?

The PDSA Cycle for Improvement

Tools and Methods to Support the Model for Improvement

Analysis of Data from PDSA Cycles

Chapter 2: Using Data for Improvement

What Does the Concept of Data Mean?

How Are Data Used?

Types of Data

The Importance of Operational Definitions

Data for Different Types of Studies

Use of Sampling

What About Sample Size?

Stratification of Data

What About Risk or Case-Mix Adjustment?

Transforming Data

Analysis and Presentation of Data

Using a Family of Measures

Chapter 3: Understanding Variation Using Run Charts

Introduction

What Is a Run Chart?

Use of a Run Chart

Constructing a Run Chart

Examples of Run Charts for Improvement Projects

Probability-Based Tests to Aid in Interpreting Run Charts

Special Issues in Using Run Charts

Stratification with Run Charts

Using the Cumulative Sum Statistic with Run Charts

Chapter 4: Learning from Variation in Data

The Concept of Variation

Depicting Variation

Introduction to Shewhart Charts

Interpretation of a Shewhart Chart

Establishing and Revising Limits for Shewhart Charts

When Do We Revise Limits?

Stratification with Shewhart Charts

Rational Subgrouping

Shewhart Charts with Targets, Goals, or Other Specifications

Special Cause: Is It Good or Bad?

Other Tools for Learning from Variation

Chapter 5: Understanding Variation Using Shewhart Charts.

Selecting the Type of Shewhart Chart

Shewhart Charts for Continuous Data

I Charts

Examples of Shewhart Charts for Individual Measurements

Rational Ordering with an Individual Chart

Effect of the Distribution of the Measurements

Example of Individual Chart for Deviations from a Target

X and S Shewhart Charts

Shewhart Charts for Attribute Data

The P Chart for Classification Data

C and U Charts for Counts of Nonconformities

Process Capability

Process Capability from an I Chart

Capability of a Process from X and S Chart (or R chart)

Capability of a Process from Attribute Control Charts

Capability from a P Chart

Capability from a C or U Chart

Appendix 5.1: Calculating Shewhart Limits

I Chart

X and S Charts

X and S Control Chart Calculation Form

P Chart

P Chart Calculation Form: Constant Subgroup Size

P Chart Calculation Form: Variable Subgroup Size

C Chart

U Chart

Chapter 6: Shewhart Chart Savvy: Dealing with Some Issues

Designing Effective Shewhart Charts

Tip 1: Type of Data and Subgroup Size

Tip 2: Rounding Data

Tip 3: Formatting Charts

Typical Problems with Software for Calculating Shewhart Charts

Characteristics to Consider When Purchasing SPC Software

Some Cautions When Using I Charts

Part II: Advanced Theory and Methods with Data

Chapter 7: More Shewhart-Type Charts

Other Shewhart-Type Charts

NP Chart

X and Range (R) Chart

Median Chart

Shewhart Charts for Rare Events

G Chart for Opportunities Between Rare Events

T Chart for Time Between Rare Events

Some Alternatives to Shewhart-Type Charts

Moving Average Chart

Cumulative Sum (CUSUM) Chart

Exponentially Weighted Moving Average (EWMA)

Standardized Shewhart Charts

Multivariate Shewhart-Type Charts

Chapter 8: Special Uses for Shewhart Charts.

Shewhart Charts with a Changing Center Line

Shewhart Charts with a Sloping Center Line

Shewhart Charts with Seasonal Effects

Transformation of Data with Shewhart Charts

Shewhart Charts for Autocorrelated Data

Shewhart Charts for Attribute Data with Large Subgroup Sizes (Over-Dispersion)

Prime Charts (p&amp

#8242

and U&amp

)

Comparison Charts

Confidence Intervals and Confidence Limits

Shewhart Charts for Case-Mix Adjustment

Chapter 9: Drilling Down into Aggregate Data for Improvement

What Are Aggregate Data?

What Is the Challenge Presented by Aggregate Data?

Introduction to the Drill Down Pathway

Stratification

Sequencing

An Illustration of the Drill Down Pathway: Adverse Drug Events (ADES)

Drill Down Pathway Step One

Drill Down Pathway Step Two

Drill Down Pathway Step Three

Drill Down Pathway Step Four

Drill Down Pathway Step Five

Drill Down Pathway Step Six

Part III: Applications of Shewhart Charts in Health Care

Chapter 10: Learning from Individual Patient Data

Examples of Shewhart Charts for Individual Patients

Example 1: Temperature Readings for a Hospitalized Patient

Example 2: Bone Density for a Patient Diagnosed with Osteoporosis

Example 3: PSA Screening for Prostate Cancer

Example 4: Shewhart Charts for Continuous Monitoring of Patients

Example 5: Asthma Patient Use of Shewhart Charts

Example 6: Monitoring Weight

Example 7: Monitoring Blood Sugar Control for Patients with Diabetes

Example 8: Monitoring Patient Measures in the Hospital

Example 9: Using Shewhart Charts in Pain Management

Chapter 11: Learning from Patient Feedback to Improve Care

Patient Surveys

Summarizing Patient Feedback Data

Presentation of Patient Satisfaction Data

Using Patient Feedback for Improvement.

The Plan-Do-Study-Act Cycles (PDSA) Cycle for Testing and Implementing Changes

Using Patient Satisfaction Data in Planning for Improvement

Special Issues with Patient Feedback Data

Are There Challenges When Summarizing and Using Patient Satisfaction Survey Data?

Does Survey Scale Matter?

Chapter 12: Using Shewhart Charts in Health Care Leadership

A Health Care Organization's Vector of Measures

Developing a Vector of Measures

Displaying and Learning from a Vector of Measures

So How Do We Best Display a Vector of Measures?

Administrative Issues with Vector of Measures

Some Examples of Other Vectors of Measures

Emergency Department:

Primary Care Center

Health Authority

Large Urban Hospital

Part IV: Case Studies

Chapter 13: Case Studies Using Shewhart Charts

Case Study A: Improving Access to a Specialty Care Clinic

Case Study B: Radiology Improvement Projects

Case Study C: Reducing Post-CABG Infections

Case Study D: Drilling Down into Percentage of C-Sections

Case Study E: Accidental Puncture/Laceration Rate

Case Study F: Reducing Hospital Readmissions

Case Study G: Variation in Financial Data

Index

Shewhart Chart Selection Guide.

Notes:

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Provost, Lloyd P. The Health Care Data Guide

ISBN:

9781118086117

OCLC:

757394212