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<p>Figures, Tables, and Exhibits xiii</p> <p>Preface xxix</p> <p>Acknowledgments xxxiii</p> <p>The Authors xxxv</p> <p>About the Companion Website xxxvii</p> <p><b>Part I Using Data for Improvement 1</b></p> <p><b>Chapter 1 Improvement Methodology 3</b></p> <p>Fundamental Questions for Improvement 4</p> <p>What Are We Trying to Accomplish? 5</p> <p>How Will We Know that a Change is an Improvement? 7</p> <p>What Changes Can We Make That Will Result in Improvement? 8</p> <p>The PDSA Cycle for Improvement 9</p> <p>Tools and Methods to Support the Model for Improvement 13</p> <p>Designing PDSA Cycles for Testing Changes 15</p> <p>Analysis of Data from PDSA Cycles 19</p> <p>Summary26 Key Terms 26</p> <p><b>Chapter 2 Using Data for Improvement 27</b></p> <p>What Does the Concept of Data Mean? 27</p> <p>How are Data Used? 29</p> <p>Types of Data 36</p> <p>Using A Family of Measures 43</p> <p>The Importance of Operational Definitions 47</p> <p>Data for Different Types of Studies 51</p> <p>Sampling53 Sampling Strategies 55</p> <p>What About Sample Size? 58</p> <p>Stratification of Data 61</p> <p>What about Case-Mix Adjustment? 63</p> <p>Transforming Data 65</p> <p>Analysis and Presentation of Data 68</p> <p>Summary75 Key Terms 75</p> <p><b>Chapter 3 Understanding Variation Using Run Charts 77</b></p> <p><b>Introduction77 What Is a Run Chart? 77</b></p> <p>Use of a Run Chart 80</p> <p>Constructing a Run Chart 80</p> <p>Examples of Run Charts for Improvement Projects 84</p> <p>Rules to Aid in Interpreting Run Charts 89</p> <p>Special Issues in Using Run Charts 97</p> <p>Stratification with Run Charts 113</p> <p>Using the Cumulative Sum Statistic with Run Charts 116</p> <p>Summary120 Key Terms 121</p> <p><b>Chapter 4 Learning from Variation in Data 123</b></p> <p>The Concept of Variation 123</p> <p><b>Introduction to Shewhart Charts 129</b></p> <p>Depicting and Interpreting Variation Using Shewhart Charts 135</p> <p>The Role of Annotation with Shewhart Charts 140</p> <p>Establishing Limits for Shewhart Charts 141</p> <p>Revising Limits for Shewhart Charts 145</p> <p>Stratification with Shewhart Charts 147</p> <p>Shewhart Charts and Targets, Goals, or Other Specifications 152</p> <p>Special Cause: Is It Good or Bad? 155</p> <p>Summary157 Key Terms 158</p> <p><b>Chapter 5 Understanding Variation Using Shewhart Charts 159</b></p> <p>Selecting the Type of Shewhart Chart 160</p> <p>Shewhart Charts for Continuous Data 163</p> <p>I Charts 164</p> <p>Examples of Shewhart Charts for Individual Measurements 166</p> <p>Rational Ordering with an I Chart 168</p> <p>Example of I Chart for Deviations from a Target 170</p> <p>Xbar S Shewhart Charts 171</p> <p>Shewhart Charts for Attribute Data 177</p> <p>Subgroup Size for Attribute Charts 178</p> <p>The P Chart for Classification Data 180</p> <p>Examples of P Charts 182</p> <p>Creation of Funnel Limits for a P Chart 186</p> <p>Shewhart Charts for Counts of Nonconformities 188</p> <p>c charts 190</p> <p>U Chart 192</p> <p>Creation of Funnel Limits for a U Chart 195</p> <p>Alternatives for Attribute Charts for Rare Events 197</p> <p>G Chart for Opportunities Between Rare Events 198</p> <p>T Chart for Time Between Rare Events 202</p> <p>Process Capability 206</p> <p>Process Capability from an I Chart 208</p> <p>Capability of a Process from Xbar and S Charts 208</p> <p>Capability of a Process from Attribute Control Charts 210</p> <p>Capability from a P Chart 210</p> <p>Capability from a C or U Chart 210</p> <p>Summary211 Key Terms 212</p> <p>Appendix 5.1 Calculating Shewhart Limits 213</p> <p>I Chart (For Individual Values Of Continuous Data) 213</p> <p>Xbar S Chart (For Continuous Data In Subgroups) 214</p> <p>P Chart (For Classification Data) 217</p> <p>c chart (count Of Incidences) 218</p> <p>U Chart (Incidences Per Area Of Opportunity) 219</p> <p>G Chart (Cases Between Incidences) 220</p> <p>T Chart 221</p> <p><b>Chapter 6 Additional Tools For Understanding Variation In Data 223</b></p> <p>Depicting Variation 223</p> <p>Additional Tools for Learning from Variation 225</p> <p>Frequency Plots 225</p> <p>Frequency Plot Construction 226</p> <p>Frequency Plots Used with Shewhart Charts 228</p> <p>Frequency Plots and Stratification 232</p> <p>Pareto Charts 236</p> <p>Pareto Chart Construction 238</p> <p>Pareto Charts Used with Shewhart Charts 239</p> <p>Pareto Chart and Stratification 244</p> <p>Scatterplots250 Scatterplot Construction 251</p> <p>Scatterplots Used with Shewhart Charts 254</p> <p>Scatterplots and Stratification 258</p> <p>Radar Charts 260</p> <p>Constructing a Radar Chart 261</p> <p>Radar Charts Used with Shewhart Charts 261</p> <p>Radar Charts and Stratification 263</p> <p>Summary265 Key Terms 265</p> <p><b>Chapter 7 Shewhart Chart Savvy: Dealing with Common Issues 267</b></p> <p>Creating Effective Shewhart Charts 267</p> <p>Tip 1: Type of Data and Subgroup Size 267</p> <p>Tip 2: Rounding Data 268</p> <p>Tip 3: Formatting Charts 268</p> <p>Tip 4. Decisions for Recalculating limits, or Rephasing, on a Shewhart Chart 274</p> <p>Extending Centerline and Limits Backward 277</p> <p>Typical Problems with Software for Calculating Shewhart Charts 279</p> <p>Characteristics to Consider When Purchasing SPC Software 282</p> <p>Another Caution with I Charts and Chart Selection 285</p> <p>Guidelines for Shewhart Charts in Research Studies and Publications 287</p> <p>Use of Shewhart Charts in Research Studies 288</p> <p>Shewhart Charts in Publications 290</p> <p>Shewhart’s Theory versus Statistical Inference 292</p> <p>Summary296 Key Terms 296</p> <p><b>Part II Advanced Theory and Methods with Data For Improvement 297</b></p> <p><b>Chapter 8 More Shewhart-Type Charts 299</b></p> <p>Other Shewhart-Type Charts 301</p> <p>The NP Chart 301</p> <p>Xbar Range (Xbar R) Chart 302</p> <p>Median Chart 304</p> <p>Attribute Charts with Large Subgroup Sizes (P’ and U’) 306</p> <p>Prime Charts (P’ and U’) 307</p> <p>Negative Binomial Chart 313</p> <p>Some Adaptations to Shewhart Charts 316</p> <p>MA Chart 317</p> <p>CUSUM Chart 320</p> <p>Exponentially Weighted Moving Average (EWMA) Chart 328</p> <p>Standardized Shewhart Charts 331</p> <p>Multivariate Shewhart-Type Charts 334</p> <p>Summary338 Key Terms 339</p> <p><b>Chapter 9 Special Uses for Shewhart Charts 341</b></p> <p>Shewhart Charts with a Changing Centerline 341</p> <p>Shewhart Charts with a Sloping Centerline 342</p> <p>Shewhart Charts with Seasonal Effects 344</p> <p>Adjusting Shewhart Charts for Confounders 349</p> <p>Transformation of Data with Shewhart Charts 355</p> <p>Shewhart Charts for Autocorrelated Data 361</p> <p>Risk-Adjusted or Case-Mix Adjusted Shewhart Charts 366</p> <p>Comparison Charts 368</p> <p>Confidence Intervals and Confidence Limits 369</p> <p>Summary373 Key Terms 373</p> <p><b>Chapter 10 Drilling Down Into Aggregate Data for Improvement Ii 375</b></p> <p>What are Aggregate Data? 375</p> <p>What is the Challenge Presented by Aggregate Data? 376</p> <p><b>Introduction to the Drill Down Pathway 381</b></p> <p>Stratification 381</p> <p>Sequencing 382 Rational Subgrouping 383</p> <p>An Illustration of the Drill Down Pathway: Adverse Drug Events384 Drill Down Pathway Step One 385</p> <p>Drill Down Pathway Step Two 385</p> <p>Drill Down Pathway Step Three 387</p> <p>Drill Down Pathway Step Three, Continued 389</p> <p>Drill Down Pathway Step Four 393</p> <p>Drill Down Pathway Step Five 397</p> <p>Drill Down Pathway Step Six 400</p> <p>Summary400 Key Terms 401</p> <p><b>Part III Applications of Shewhart Charts in Health Care 403</b></p> <p><b>Chapter 11 Learning from Individual Patient Data 405</b></p> <p>Examples of Shewhart Charts for Individual Patients 407</p> <p>Example 1: Asthma Patient Use of Shewhart Charts 408</p> <p>Example 2: Prostate-Specific Antigen (PSA) Screening for Prostate Cancer 409</p> <p>Example 3: Monitoring Patient Measures in the Hospital 411</p> <p>Example 4: Bone Density for a Patient Diagnosed with Osteoporosis 412</p> <p>Example 5: Temperature Readings for a Hospitalized Patient 415</p> <p>Example 6: Shewhart Charts for Continuous Monitoring of Patients 418</p> <p>Example 7: Monitoring Weight 420</p> <p>Example 8: Monitoring Blood Sugar Control for Patients with Diabetes 421</p> <p>Example 9: Using Shewhart Charts in Pain Management 422</p> <p>Summary423</p> <p><b>Chapter 12 Learning from Patient Feedback to Improve Care 425</b></p> <p>Summarizing Patient Feedback Data 429</p> <p>Presentation of Patient Satisfaction Data 437</p> <p>Using Patient Feedback for Improvement 438</p> <p>The PDSA Cycle for Testing and Implementing Changes 438</p> <p>Improvement Team Working on Clinic Satisfaction 438</p> <p>Improvement Team Working on Pain 442</p> <p>Feedback from Employees 444</p> <p>Using Patient Satisfaction Data in Planning for Improvement 445</p> <p>Special Issues with Patient Feedback Data 447</p> <p>Are There Challenges When Summarizing and Using Patient Satisfaction Survey Data? 447</p> <p>Does Survey Scale Matter? 449</p> <p>Summary450 Key Terms 450</p> <p><b>Chapter 13 Using Shewhart Charts in Health Care Leadership 451</b></p> <p>A Health Care Organization’s Vector of Measures 452</p> <p>Developing a VOM 453</p> <p>So How do We Best Display a VOM? 461</p> <p>Administrative Issues with a VOM 464</p> <p>Some Examples of Measures for Other VOMs 467</p> <p>Emergency Department 468</p> <p>Primary Care Center 468</p> <p>System Flow Measures 469</p> <p>Health Authority 469</p> <p>Large Urban Hospital 471</p> <p>IHI Whole System Measures 471</p> <p>Summary473 Key Terms 474</p> <p><b>Chapter 14 Shewhart Charts for Epidemic Data 475</b></p> <p>Shewhart Charts in Epidemiology 476</p> <p>Development of Shewhart Charts for Epidemic Data 479</p> <p>c charts (Epoch 1) 479</p> <p>Charts of Epoch 2 481</p> <p>Charts for Epoch 3 485</p> <p>Charts for Epoch 4 486</p> <p>Some Issues with the Hybrid Chart for COVID-19 Deaths 487</p> <p>Data Quality 487</p> <p>Day-of-the-Week Adjustment 487</p> <p>Application of the Hybrid Charts to Cases, Hospitalizations, and Intensive Care Unit Admissions 489</p> <p>Summary492 Key Term 492</p> <p><b>Chapter 15 Case Studies 493</b></p> <p>Case Study A: Improving Access to a Specialty Care Clinic 495</p> <p>Case Study B: Radiology Improvement Projects 504</p> <p>Case Study C: Reducing Post-Cabg Infections 514</p> <p>Case Study D: Drilling Down into Percentage of C-Sections 526</p> <p>Case Study E: Reducing Length of Stay After Surgery 537</p> <p>Case Study F: Reducing Hospital admissions 551</p> <p>Case Study G: Accidental Puncture/Laceration Rate 558</p> <p>Case Study H: Improving Telemedicine Failed Calls and No Shows 568</p> <p>Case Study I: Variation in Financial Data 583</p> <p>Index 595</p> <p>Shewhart Chart Selection Guide 609</p>

<p><b>LLOYD P. PROVOST</b> 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.</p> <p><b>SANDRA K. MURRAY </b>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.</p>

<p><b>AN ESSENTIAL TEXT ON TRANSFORMING RAW DATA INTO CONCRETE HEALTH CARE IMPROVEMENTS</b></p> <p>Now in its second edition,<i> The Health Care Data Guide: Learning from Data for Improvement </i>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. <p>This book is the perfect companion resource to <i>The Improvement Guide: A Practical Approach to Enhancing Organizational Performance, 2nd Edition,</i> and offers fulsome discussions of how to use data to test, adapt, implement, and scale positive organizational change. <p><i>The Health Care Data Guide: Learning from Data for Improvement, Second Edition</i> provides: <ul><li>Easy to use strategies for learning more readily from existing health care data</li> <li>Clear guidance on the most useful graph for different types of data used in health care</li> <li>A step-by-step method for making use of highly aggregated data for improvement </li> <li>Examples of using patient-level data in care</li> <li>Multiple methods for making use of patient and other feedback data</li> <li>A vastly better way to view data for executive leadership</li> <li>Solutions for working with rare events data, seasonality and other pesky issues</li> <li>Use of improvement methods with epidemic data</li> <li>Improvement case studies using data for learning</li></ul> <p>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.

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