John Wiley & Sons The Health Care Data Guide Cover An Essential text on transforming raw data into concrete health care improvements Now in its second.. Product #: 978-1-119-69013-9 Regular price: $91.50 $91.50 Auf Lager

The Health Care Data Guide

Learning from Data for Improvement

Provost, Lloyd P. / Murray, Sandra K.


2. Auflage August 2022
656 Seiten, Softcover
Wiley & Sons Ltd

ISBN: 978-1-119-69013-9
John Wiley & Sons

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An Essential text on transforming raw data into concrete health care improvements

Now in its second edition, The Health Care Data Guide: Learning from Data for Improvement delivers a practical blueprint for using available data to improve healthcare outcomes. In the book, a team of distinguished authors explores how health care practitioners, researchers, and other professionals can confidently plan and implement health care enhancements and changes, all while ensuring those changes actually constitute an improvement.

This book is the perfect companion resource to The Improvement Guide: A Practical Approach to Enhancing Organizational Peformance, Second Edition, and offers fulsome discussions of how to use data to test, adapt, implement, and scale positive organizational change.

The Health Care Data Guide: Learning from Data for Improvement, Second Edition provides:
* Easy to use strategies for learning more readily from existing health care data
* Clear guidance on the most useful graph for different types of data used in health care
* A step-by-step method for making use of highly aggregated data for improvement
* Examples of using patient-level data in care
* Multiple methods for making use of patient and other feedback data
* A vastly better way to view data for executive leadership
* Solutions for working with rare events data, seasonality and other pesky issues
* Use of improvement methods with epidemic data
* Improvement case studies using data for learning
A must read resource for those committed to improving health care including allied health professionals in all aspects of health care, physicians, managers, health care leaders, and researchers.

Figures, Tables, and Exhibits xiii

Preface xxix

Acknowledgments xxxiii

The Authors xxxv

About the Companion Website xxxvii

Part I Using Data for Improvement 1

Chapter 1 Improvement Methodology 3

Fundamental Questions for Improvement 4

What Are We Trying to Accomplish? 5

How Will We Know that a Change is an Improvement? 7

What Changes Can We Make That Will Result in Improvement? 8

The PDSA Cycle for Improvement 9

Tools and Methods to Support the Model for Improvement 13

Designing PDSA Cycles for Testing Changes 15

Analysis of Data from PDSA Cycles 19

Summary26 Key Terms 26

Chapter 2 Using Data for Improvement 27

What Does the Concept of Data Mean? 27

How are Data Used? 29

Types of Data 36

Using A Family of Measures 43

The Importance of Operational Definitions 47

Data for Different Types of Studies 51

Sampling53 Sampling Strategies 55

What About Sample Size? 58

Stratification of Data 61

What about Case-Mix Adjustment? 63

Transforming Data 65

Analysis and Presentation of Data 68

Summary75 Key Terms 75

Chapter 3 Understanding Variation Using Run Charts 77

Introduction77 What Is a Run Chart? 77

Use of a Run Chart 80

Constructing a Run Chart 80

Examples of Run Charts for Improvement Projects 84

Rules to Aid in Interpreting Run Charts 89

Special Issues in Using Run Charts 97

Stratification with Run Charts 113

Using the Cumulative Sum Statistic with Run Charts 116

Summary120 Key Terms 121

Chapter 4 Learning from Variation in Data 123

The Concept of Variation 123

Introduction to Shewhart Charts 129

Depicting and Interpreting Variation Using Shewhart Charts 135

The Role of Annotation with Shewhart Charts 140

Establishing Limits for Shewhart Charts 141

Revising Limits for Shewhart Charts 145

Stratification with Shewhart Charts 147

Shewhart Charts and Targets, Goals, or Other Specifications 152

Special Cause: Is It Good or Bad? 155

Summary157 Key Terms 158

Chapter 5 Understanding Variation Using Shewhart Charts 159

Selecting the Type of Shewhart Chart 160

Shewhart Charts for Continuous Data 163

I Charts 164

Examples of Shewhart Charts for Individual Measurements 166

Rational Ordering with an I Chart 168

Example of I Chart for Deviations from a Target 170

Xbar S Shewhart Charts 171

Shewhart Charts for Attribute Data 177

Subgroup Size for Attribute Charts 178

The P Chart for Classification Data 180

Examples of P Charts 182

Creation of Funnel Limits for a P Chart 186

Shewhart Charts for Counts of Nonconformities 188

c charts 190

U Chart 192

Creation of Funnel Limits for a U Chart 195

Alternatives for Attribute Charts for Rare Events 197

G Chart for Opportunities Between Rare Events 198

T Chart for Time Between Rare Events 202

Process Capability 206

Process Capability from an I Chart 208

Capability of a Process from Xbar and S Charts 208

Capability of a Process from Attribute Control Charts 210

Capability from a P Chart 210

Capability from a C or U Chart 210

Summary211 Key Terms 212

Appendix 5.1 Calculating Shewhart Limits 213

I Chart (For Individual Values Of Continuous Data) 213

Xbar S Chart (For Continuous Data In Subgroups) 214

P Chart (For Classification Data) 217

c chart (count Of Incidences) 218

U Chart (Incidences Per Area Of Opportunity) 219

G Chart (Cases Between Incidences) 220

T Chart 221

Chapter 6 Additional Tools For Understanding Variation In Data 223

Depicting Variation 223

Additional Tools for Learning from Variation 225

Frequency Plots 225

Frequency Plot Construction 226

Frequency Plots Used with Shewhart Charts 228

Frequency Plots and Stratification 232

Pareto Charts 236

Pareto Chart Construction 238

Pareto Charts Used with Shewhart Charts 239

Pareto Chart and Stratification 244

Scatterplots250 Scatterplot Construction 251

Scatterplots Used with Shewhart Charts 254

Scatterplots and Stratification 258

Radar Charts 260

Constructing a Radar Chart 261

Radar Charts Used with Shewhart Charts 261

Radar Charts and Stratification 263

Summary265 Key Terms 265

Chapter 7 Shewhart Chart Savvy: Dealing with Common Issues 267

Creating Effective Shewhart Charts 267

Tip 1: Type of Data and Subgroup Size 267

Tip 2: Rounding Data 268

Tip 3: Formatting Charts 268

Tip 4. Decisions for Recalculating limits, or Rephasing, on a Shewhart Chart 274

Extending Centerline and Limits Backward 277

Typical Problems with Software for Calculating Shewhart Charts 279

Characteristics to Consider When Purchasing SPC Software 282

Another Caution with I Charts and Chart Selection 285

Guidelines for Shewhart Charts in Research Studies and Publications 287

Use of Shewhart Charts in Research Studies 288

Shewhart Charts in Publications 290

Shewhart's Theory versus Statistical Inference 292

Summary296 Key Terms 296

Part II Advanced Theory and Methods with Data For Improvement 297

Chapter 8 More Shewhart-Type Charts 299

Other Shewhart-Type Charts 301

The NP Chart 301

Xbar Range (Xbar R) Chart 302

Median Chart 304

Attribute Charts with Large Subgroup Sizes (P' and U') 306

Prime Charts (P' and U') 307

Negative Binomial Chart 313

Some Adaptations to Shewhart Charts 316

MA Chart 317

CUSUM Chart 320

Exponentially Weighted Moving Average (EWMA) Chart 328

Standardized Shewhart Charts 331

Multivariate Shewhart-Type Charts 334

Summary338 Key Terms 339

Chapter 9 Special Uses for Shewhart Charts 341

Shewhart Charts with a Changing Centerline 341

Shewhart Charts with a Sloping Centerline 342

Shewhart Charts with Seasonal Effects 344

Adjusting Shewhart Charts for Confounders 349

Transformation of Data with Shewhart Charts 355

Shewhart Charts for Autocorrelated Data 361

Risk-Adjusted or Case-Mix Adjusted Shewhart Charts 366

Comparison Charts 368

Confidence Intervals and Confidence Limits 369

Summary373 Key Terms 373

Chapter 10 Drilling Down Into Aggregate Data for Improvement Ii 375

What are Aggregate Data? 375

What is the Challenge Presented by Aggregate Data? 376

Introduction to the Drill Down Pathway 381

Stratification 381

Sequencing 382 Rational Subgrouping 383

An Illustration of the Drill Down Pathway: Adverse Drug Events384 Drill Down Pathway Step One 385

Drill Down Pathway Step Two 385

Drill Down Pathway Step Three 387

Drill Down Pathway Step Three, Continued 389

Drill Down Pathway Step Four 393

Drill Down Pathway Step Five 397

Drill Down Pathway Step Six 400

Summary400 Key Terms 401

Part III Applications of Shewhart Charts in Health Care 403

Chapter 11 Learning from Individual Patient Data 405

Examples of Shewhart Charts for Individual Patients 407

Example 1: Asthma Patient Use of Shewhart Charts 408

Example 2: Prostate-Specific Antigen (PSA) Screening for Prostate Cancer 409

Example 3: Monitoring Patient Measures in the Hospital 411

Example 4: Bone Density for a Patient Diagnosed with Osteoporosis 412

Example 5: Temperature Readings for a Hospitalized Patient 415

Example 6: Shewhart Charts for Continuous Monitoring of Patients 418

Example 7: Monitoring Weight 420

Example 8: Monitoring Blood Sugar Control for Patients with Diabetes 421

Example 9: Using Shewhart Charts in Pain Management 422


Chapter 12 Learning from Patient Feedback to Improve Care 425

Summarizing Patient Feedback Data 429

Presentation of Patient Satisfaction Data 437

Using Patient Feedback for Improvement 438

The PDSA Cycle for Testing and Implementing Changes 438

Improvement Team Working on Clinic Satisfaction 438

Improvement Team Working on Pain 442

Feedback from Employees 444

Using Patient Satisfaction Data in Planning for Improvement 445

Special Issues with Patient Feedback Data 447

Are There Challenges When Summarizing and Using Patient Satisfaction Survey Data? 447

Does Survey Scale Matter? 449

Summary450 Key Terms 450

Chapter 13 Using Shewhart Charts in Health Care Leadership 451

A Health Care Organization's Vector of Measures 452

Developing a VOM 453

So How do We Best Display a VOM? 461

Administrative Issues with a VOM 464

Some Examples of Measures for Other VOMs 467

Emergency Department 468

Primary Care Center 468

System Flow Measures 469

Health Authority 469

Large Urban Hospital 471

IHI Whole System Measures 471

Summary473 Key Terms 474

Chapter 14 Shewhart Charts for Epidemic Data 475

Shewhart Charts in Epidemiology 476

Development of Shewhart Charts for Epidemic Data 479

c charts (Epoch 1) 479

Charts of Epoch 2 481

Charts for Epoch 3 485

Charts for Epoch 4 486

Some Issues with the Hybrid Chart for COVID-19 Deaths 487

Data Quality 487

Day-of-the-Week Adjustment 487

Application of the Hybrid Charts to Cases, Hospitalizations, and Intensive Care Unit Admissions 489

Summary492 Key Term 492

Chapter 15 Case Studies 493

Case Study A: Improving Access to a Specialty Care Clinic 495

Case Study B: Radiology Improvement Projects 504

Case Study C: Reducing Post-Cabg Infections 514

Case Study D: Drilling Down into Percentage of C-Sections 526

Case Study E: Reducing Length of Stay After Surgery 537

Case Study F: Reducing Hospital admissions 551

Case Study G: Accidental Puncture/Laceration Rate 558

Case Study H: Improving Telemedicine Failed Calls and No Shows 568

Case Study I: Variation in Financial Data 583

Index 595

Shewhart Chart Selection Guide 609
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 cohort of client organizations encompasses the spectrum of health care delivery.