Americas healthcare transformation strategies and innovations

www.ebook3000.com America’s Healthcare Transformation Strategies and Innovations www.ebook3000.com America’s Healthcare Transformation Strategies and Innovations Edited by Robert A Phillips Rutgers University Press Medicine New Brunswick, New Jersey, and London Library of Congress Cataloging-in-P ublication Data Names: Phillips, Robert A., 1951–, editor Title: America’s healthcare transformation : strategies and innovations / edited by Robert A Phillips Description: New Brunswick, New Jersey : Rutgers University Press, [2016] | Includes bibliographical references and index Identifiers: LCCN 2015042932 | ISBN 9780813572222 (hardcover : alk paper) | ISBN 9780813572239 (e-book (ePub)) | ISBN 9780813572246 (e-book (Web PDF)) Subjects: | MESH: Delivery of Health Care—United States | Efficiency, Organ izational—United States | Health Care Reform—United States | Patient Safety—United States | Quality of Health Care—United States Classification: LCC RA445 | NLM W 84 AA1 | DDC 326.10973—dc23 LC record available at http://lccn.loc.gov/2 015042932 A British Cataloging-in-P ublication record for this book is available from the British Library This publication was supported in part by the Eleanor J and Jason F Dreibelbis Fund This collection copyright © 2016 by Rutgers, The State University Individual chapters copyright © 2016 in the names of their authors All rights reserved No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, or by any information storage and retrieval system, without written permission from the publisher Please contact Rutgers University Press, 106 Somerset Street, New Brunswick, NJ 08901 The only exception to this prohibition is “fair use” as defined by U.S copyright law Visit our website: http://r utgerspress.r utgers.edu Manufactured in the United States of America www.ebook3000.com CONTENTS Preface and Acknowledgments ix Contributing Authors xiii Part I Patient Safety and Quality Organizing Performance Management to Support High Reliability Healthcare Erin S DuPree Mark R Chassin Elimination of Unintended Variation in Patient Care 17 Gary S Kaplan Fundamental Approaches to Measuring and Improving Patient Safety 31 Sarah P Slight David W Bates The Organ izational Culture that Supports Patient Safety 42 Alberta T Pedroja The Role of Health Information Technology in Patient Safety 60 Sarah P Slight David W Bates Training Physician Leaders in Patient Safety and Quality: Prog ress and Challenges 72 Susan A Abookire v vi Contents Use of Registries and Public Reporting to Improve Healthcare 87 Kasaiah Makam Sandra A Weiss William S Weintraub Part II Healthcare Delivery Redesign Achieving Higher Quality and Lower Costs via Innovations in Healthcare Delivery Design 105 Elizabeth Malcolm Arnold Milstein Population Health Management: The Lynchpin of Emerging Healthcare Delivery Models 113 Julia D Andrieni 10 Healthcare Delivery Redesign: Team-Based Care 128 Nana E Coleman Alicia D H Monroe 11 Medicine Unplugged: Can M-Health Transform Healthcare? 142 Ju Young Kim Steven R Steinhubl 12 Telemedicine: Virtually Redefining the Delivery of Care 163 Jason Gorevic 13 Grand-A ides: Leveraging the Workforce for More Effective and Less Expensive Care 178 Arthur Garson Jr 14 Conven ience Care and the Rise of Retail Clinics 197 Tine Hansen-Turton Kenneth W Patric Janet J Teske Part III Emerging Paradigms in the Practice of Medicine 15 Using Guideline-Based Medicine to Improve Patient Care 217 Kunal N Karmali Philip Greenland www.ebook3000.com Contents 16 Precision Medicine: Expanded and Translational 239 Hanh H Hoang Mauro Ferrari 17 Evidence-Based Medicine and Shared Decision Making 262 Kasey R Boehmer Victor M Montori Henry H Ting Part IV Healthcare Reform and New Payment Methods 18 The Rise of Consumerism and How Insurance Reform Will Drive Healthcare Delivery Reform 281 James L Field 19 Creating the Healthcare Transformation from Volume to Value 295 Nikhil G Thaker Thomas W Feeley Part V Patient Experience, Engagement, and Services 20 Innovations in Patient Experience 319 Deirdre Mylod Thomas H Lee Sharyl Wojciechowski 21 Behavioral Economics and Stanford Health Care’s C-I-CARE Patient Experience 336 Amir Dan Rubin 22 Impact of an Engaged Workforce on Patient Care: Our Culture of I CARE 345 Marc L Boom Index 355 vii www.ebook3000.com PREFACE AND ACKNOWLE DGMENTS In the United States, we are in the midst of a fundamental transformation of the practice of medicine and of the $3 trillion per year healthcare industry Landmark events in the 1990s that stimulated these dramatic shifts include the conceptualization and widespread adoption of evidence-based medicine, the introduction of computerized physician order entry, and elevation of patient safety and quality as a healthcare priority following the 1999 report by the Institute of Medicine (IOM) titled To Err Is H uman: Building a Safer Health System In the first two decades of the 21st century, events that have spurred the transformation of healthcare include the completion of the Human Genome Project in 2003, the passage of the Affordable Care Act in 2010, emergence of precision medicine, advanced analytics to enable population health management, the widespread use of smartphones and associated apps that enable remote monitoring, and the shift toward patient-centered care with emphasis on the patient experience It is not an exaggeration to state that we are in the m iddle of the largest change in healthcare practice and delivery in history The mission of this book is to provide a comprehensive roadmap for navigating t hese historic and sometimes confusing times by focusing on the five major domains that are influencing and experiencing the greatest paradigm shifts These domains are “Patient Safety and Quality,” “Healthcare Delivery Redesign,” “Emerging Paradigms in the Practice of Medicine,” “Healthcare Reform and New Payment Methods,” and “Patient Experience, Engagement, and Ser vices.” In doing so, this book touches on virtually every facet of the ongoing transformational changes in healthcare and the practice of medicine To achieve this aim, we assembled a group of experts who are at the leading edge of thought and implementation of these transformational changes Authors ix 362 Index Eswaran, J., 247 ethnography, applied, 1 09 evidence-based medicine, 43, 262–276; clinical practice guidelines in, 217–234; confidence in evidence in, 263, 263t; patient preferences in, 263–264, 265; in population health management, 124; principles of, 262–264, 276; in retail clinics, 210; and shared decision making, 262, 267–276; in V irginia Mason Production System, 21, 24, 28 evidence synthesis in shared decision making, 268, 269f, 270, 275 excellence: in Houston Methodist I CARE approach, 345–354; operational, exchanges for purchase of health insurance, 282, 288–289, 290 experience synthesis for decision aids, 268 eye examinations, smartphone technology in, 150–151 family involvement: in Stanford Health Care, 339–340; in team-based care, 130–131, 134–135, 137, 138–139 FastCare, 208t fee-for-service model, 283, 287, 296, 304–305, 309 The Flexner Report, 73 Fogg, B. J., 338–339, 341 Food and Drug Administration, 251 forcing functions, 48 Ford, Loretta, 199 Francis, Robert, 37 Fulford, Bill, 133 Gail Model on breast cancer, 243 Geisinger Health System, 109 General Electric, perform ance improvement in, 7, 11 genet ic factors: crowdsourced research on, 151; in precision medicine, 240–247, 251, 253, 255; wireless body sensor network systems in diagnosis of, 149 genomics, 239, 256; and pharmacogenomics, 149, 241, 242 geographic expansion of serv ices, 310–311, 311f George Washington University Health Sciences Programs, 82 Get with the Guidelines (GWTG) program, 231, 232 global provider budgets, 305 Global Trigger Tool of IHI, 34 glucocorticoid therapy in asthma and precision medicine, 242 glucose monitoring: with mobile health technology, 148–149, 154; in telemedicine, 164, 172 Golinkin, Web, 205 Google Glass, 152 GRADE Working Group, 263 graduate medical education, competency- based, 77–79 Grand-A ides, 178–194; in disease-based programs, 181; employment and payment of, 180, 188, 189; number of patients seen by, 180, 188; in population-based programs, 181, 186; regulations on practice of, 186–187 Grand-A ides USA, 188, 189–190, 192 green b elt trainees in Robust Process Improvement, 13 Grenny, Joseph, 342 Griffith, John, 351 Grimshaw, J. M., 223 guideline-based medicine, 217–234 Guidelines Applied in Practice (GAP), 231–232 Guidelines International Network (GIN), 223, 227 habit development in Stanford Health Care, 341 Han, Y. Y., 63 hand hygiene, 4, 44 Hannan, E. L., 90, 95, 96 Hansen-Turton, Tine, 205 Harless, Angela, 347 Harvard Medical Practice Study, 34 Harvard Medical School, 73, 83, 84t HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey, 321f, 321–322, 322f, 324, 326, 328; Stanford ranking in, 337 Health, Chip and Dan, 340 www.ebook3000.com Index Healthcare Clinic at Walgreens, 199, 204, 208t, 210 healthcare delivery, 103–214; achieving higher quality and lower costs in, 105–111; clinical practice guidelines in, 217–234; consumer-oriented, 292–293; conven ience of, 197–213, 292–293; conventional roles and relationships in, 285–287, 286f; empathy in, 322; evidence-based medicine in, 262–276; fragmentation of serv ices in, 297; gap between recommended and a ctual care in, 227–228; geographic expansion of serv ices in, 310–311, 311f; Grand-A ides in, 178–194; in home settings, 108; information technology in, 60–68, 105, 106, 110; insurance reform affecting, 281–294; integrated practice units in, 298, 310–311; mobile technologies in, 142–157; networks of providers in, 290–292; patient experience in, 319–334; for patients-a s-consumers, 284–285; population health management in, 113–127; precision medicine in, 239–256; quality improvement in (See quality improvement); retail clinics in, 107, 197–213; team-based care in, 128–139; telemedicine in, 163–176; unmet needs in, 105, 106, 109–110, 322, 324, 326; value-based, 295–313; volume-based, 295, 296 Health Care Financing Administration (HCFA), 88, 90 Health Care Improvement Foundation, 209 healthcare report cards, 88–89; consumer benefits of, 94–95; on coronary artery bypass graft surgery, 89, 90–97 health information technology, 35, 60–68 See also technology Health Information Technology for Economic and Clinical Health (HITECH) Act, 62 health insurance, 281–294; for catastrophic coverage, 289; co-payments in, 176, 282, 287, 288, 289; cost of premiums in, 169, 176, 282, 288, 289, 290, 291; deductibles in, 169, 176, 282, 287, 288, 289; employer provision of, 169, 176, 286–287, 288, 289, 363 290; exchanges for purchase of, 282, 288–289, 290; networks of providers in, 290–292; preferred provider organizations in, 287, 291 Health Insurance Portability and Accountability Act (HIPAA), 182–183, 331 health maintenance organizations (HMOs), 290, 306 Health Plan Employer Data and Information Set (HEDIS), 97, 206 Health Professions Education: A Bridge to Quality, 74 health risks pyramid, 117–118, 118f heart failure: clinical practice guidelines in, 228; Grand-A ide visits in, 178, 181, 182, 184; patient needs in, 324–325 heart rate monitoring: with telemedicine, 164; with wireless body sensor network systems, 145, 146, 147, 148f heparin therapy, 46–47, 50–51; smart pump technology in, 66 hierarchical model on hospital mortality, 90–91 high-reliability healthcare, 3–15; culture of safety in, 6f, 6–7; leadership commitment to zero harm in, 5; perform ance improvement methods in, 7–15 high-reliability organizations (HROs), 4, 6–7, 35, 46 HIPAA (Health Insurance Portability and Accountability Act), 182–183, 331 histone deacetylase (HDAC), 246 HITECH (Health Information Technology for Economic and Clinical Health) Act, 62 HIV infection: mobile health technology applications in, 156; precision medicine in, 248 home settings: blood pressure monitoring in, 122, 147; Grand-A ide visits to, 178–194; healthcare delivery in, 108 Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, 321f, 321–322, 322f, 324, 326, 328; Stanford ranking in, 337 “Hospitals Compare” database of CMS, 232 Hospital Survey on Patient Safety Culture (AHRQ), 35 364 Index Houston Methodist Hospital: culture of I CARE in, 345–354; population health management strategy in, 119–120, 120f, 121f, 122, 1 23f human-centered design, 109 hypertension: clinical practice guidelines in, 231; genetic factors and precision medicine in, 241; G rand-A ide visits in, 185–186; home monitoring of blood pressure in, 122, 147; population health management in, 119, 120, 121f, 122, 123f; wireless body sensor network monitoring in, 147 I CARE culture in Houston Methodist Hospital, 345–354 IHI See Institute for Healthcare Improvement image-g uided interventions, 249 imaging procedures: evidence-based order for, 21–22, 22f; nanotechnology in, 248–249; in precision medicine, 248–250 immunizations in population health management, 123, 124 implementation of clinical practice guidelines, 228–232 implementation science, 228 incident-reporting systems, 34–35 indirect costs, 300 individualized care: in evidence-based medicine, 263–264; in population health management, 114, 117–118, 119–120, 126; in precision medicine, 239–256 infections: antibiotic therapy in, 24, 28–29; clinical practice guidelines on treatment of, 222; hospital-acquired Clostridium difficile, 44–45; mobile health technology in, 149, 150, 151, 155–156; precision medicine in, 248; retail clinic care in, 200, 203, 206; sepsis treatment variations in, 23–24 Infectious Disease Society of America clinical practice guidelines, 222, 224 Influence: The Psychology of Persuasion (Cialdini), 338 Influencer: The Power to Change Anything (Patterson, Grenny, Maxfield, McMilian & Switzler), 342 information technology, 35, 60–68 See also technology informed decision-m aking model, 266, 267 inherent suffering, 323t, 323–324, 325t Institute for Healthcare Improvement (IHI), 43, 51, 74; Breakthrough Collaborative Model of, 36; Global Trigger Tool of, 34; open school program of, 82–83, 83f; safety campaigns of, 53, 74; T riple Aim model of, 129–130 Institute of Medicine (IOM): on annual death rate from healthcare injuries, 60, 61; Clinical Practice Guidelines We Can Trust report of, 224–225; Crossing the Quality Chasm, 3, 32, 74, 75; definition of patient safety, 31; To Err Is H uman, 3, 31–32, 36, 43, 74; on quality of healthcare, 32; standards on clinical practice guidelines, 224–225, 225t, 227 insurance, health, 281–294 See also health insurance integrated practice units (IPUs), 298; geographic expansion of, 310–311 integrity, in Houston Methodist I CARE approach, 345–354 intensified care management: in complex chronic illness, 108; in population health management, 116, 119 intensive analysis process, 50 International Patient Decision Aid Standards (IPDAS), 268 intravenous medications, smart pump technology for, 65–66 IOM See Institute of Medicine Jaffe, M. G., 231 Jefferson School of Population Health, 82, 82f Jha, A. K., 61 Johns Hopkins Hospital, 73 The Joint Commission, 49, 51, 60; on culture of safety, 53; on rapid response teams, 53; on reliability in healthcare, 5; on retail clinics, 209 Juergens, R. A., 246 just culture model, 47 Kahneman, Daniel, 337, 338, 343 Kaiser F amily Foundation, 169 www.ebook3000.com Index Kaiser Permanente: bedside shift reports in, 109–110; hypertension quality improvement program in, 231; response rate to surveys of, 329 kaizen events in V irginia Mason Production System, 20, 22 Katz, M., 192 kidney disorders: home dialysis in, 108; precision surgery in, 250 Kinnard, Charlotte, 347 Kissoon, Niranjan, 19 Klepstad, P., 2 42 knowledge-based work, 43, 44, 45–46, 49; accountability for errors in, 56f; transition to rule-based work, 44, 51 Koay, E. J., 250 Komajda, M., 222 Kouzes, Jim, 338 Krieger, Rick, 200 Kroger Co retail clinics, 199, 205 laboratory tests: alerts on results in, 67; computer database on results in, 35; data collection and analysis on, 115; Grand-A ide serv ices in, 191; health information technology in, 62, 67; in retail clinics, 203, 204; smartphone technology in, 149, 150 The Leadership Challenge: How to Make Extraordinary T hings Happen in Organ izations (Kouzes & Posner), 338 leadership commitment: to culture of safety, 57; to Robust Process Improvement program, 11–12, 14; to zero harm, lean approach, 8–9, 36, 74, 105; in Robust Process Improvement, 9–11, 14; in Stanford Operating System, 339; in Virginia Mason Production System, 25 Leapfrog Group, 43, 64 Lee, T. H., 296, 313 legal issues: Affordable Care Act (See Affordable Care Act); clinical practice guidelines as standard in, 219; litigation threat in, 52–53; in shared decision making, 274; in telehealth serv ices, 211–213 leukemia, chronic lymphocytic, 240 Li, Y., 253 limonene in breast cancer, 248 365 Lin, L., 241 literat ure review in Virginia Mason Production System, 21 The L ittle Clinic, 199, 205, 208t Lopez, Maria, 348 loss aversion as motivating factor, 343 Lucian Leape Institute, 75 lung cancer, precision medicine in, 241, 246, 256 magnetic resonance imaging, 248, 250; evidence-based order for, 21, 22f; in image-g uided interventions, 249 malpractice litigation, 52–53; clinical practice guidelines as standard in, 219 mammography: clinical practice guidelines on, 223; in population health management, 116, 123; underutilizers of, 116; unintended variations in, 25, 27 Manchester Patient Safety Framework (MaPSaf ), 35 Marx, David, 47 Massachusetts Institute of Technology, 150, 331 mass spectrometry and chromatography, 247 masters programs in healthcare quality and patient safety, 81–82, 82f maternal–i nfant visits from Grand-A ide, 186 Maxfield, David, 342 Mayo Clinic: Biobank database of, 254; perform ance improvement methods in, 11; Shared Decision Making National Resource Center, 274 McGoff, Chris, 194 McMilian, Ron, 342 MD Anderson Cancer network, 311, 311f MEDEX primary care training program, 200 Medicaid, 285; G rand-A ide visits in, 181, 185, 186, 188, 188t; pay for perform ance programs in, 306; telemedicine serv ices in, 166 medical education, 72–84; AMSA patient safety topics in, 80, 81f; competency standards in, 76–79, 83, 84f; degree programs on quality and patient safety in, 81–82; in Harvard Medical School, 83, 366 Index medical education (continued) 84t; in IHI open school, 82–83, 83f; on population health management, 125–126; on precision medicine, 254–255; for primary care practice, 167–168; on shared decision making and decision aids, 273; on team-based care, 137–139; in Virginia Mason Production System, 23–24; WHO patient safety topics in, 80, 81t Medicare, 285; Grand-A ide visits in, 181, 186, 188t; payment systems in, 306, 308, 328; population health management in, 114, 124–125; projected growth in, 167; telemedicine serv ices in, 166 Medicare Advantage (MA), 124–125, 211 Medicare Improvements for Patients and Providers Act (2008), 224 Medicare Shared Savings Program (MSSP), 114, 124–125, 307 medication errors, 32–33, 35, 46–47; in administration, 33, 61, 64–65; adverse events in, 32–33, 62, 65, 66; computerized physician order entry in prevention of, 35, 53, 62–64; diagnostic, 33; frequency of, 33; health information technology in prevention of, 61–66; in heparin therapy, 46–47, 50–51, 66; in ordering, 35, 53, 61, 62–64; in prescription, 33, 64; root cause analysis of, 50; as sentinel event, 46; in transcription, 35, 61, 64; types of, 33 Medscape Physician Compensation Report, 168 Merritt Hawkins study on healthcare access, 168–169 metabolomics, 244, 247 metastatic cancer, precision medicine in, 241, 245, 246, 249 m-health technologies, 142–157 See also mobile health technologies Mid Staffordshire NHS Foundation Trust, 37 milestones in competency-based curriculum, 77, 78 Miller, J. A., 248 MinuteClinic, 199, 200, 205, 208t mitigation strategies in culture of safety, 47, 49–50 mobile health technologies, 142–157; access to health information with, 152–153; in acute communicable disease, 155–156; augmented and virtual reality in, 152; in chronic noncommunicable disease, 154; crowdsourced clinical t rials in, 151; in developing countries, 156; in Grand-A ide visits, 182–183; growth of, 156–157, 157t; patient online communities in, 151; point-of-need testing in, 149–151; provider–consumer relationship in, 152–154; in telemedicine, 164; wireless body sensor networks in, 143–149 monitoring: in G rand-A ide visits, 185–186; health information technology in, 67, 110; mobile health technology in, 143–149, 156; in population health management, 122; in telemedicine, 164, 172; wireless body sensor networks in, 143–149 Montori, V. M., 271 mortality rates: in chronic diseases, 154; in injuries related to errors, 3, 60, 61, 74; public reporting affecting, 95–98; public reporting on, 90–92 Moscucci, M., 97 motion and activity monitoring, 67; with telemedicine, 164; with wireless body sensor network systems, 145, 146, 148 motivation: disgusters in, 109; loss aversion in, 343 Motorola, perform ance improvement in, Mulder, W. J., 248 multidetector computed tomography (MDCT), 249 multidisciplinary approach: in accountable care organizations, 307; in integrated practice units, 298; in precision medicine, 245, 254 multiple regression modeling, 91 Multi-professional Patient Safety Curriculum Guide (WHO), 80 Murray, S., 19–20 nanomedicine, 248–249 nanotechnology, 239, 245, 248–249, 256 Narins, C. R., 97 narrow networks of providers, 290–291 National Advisory Group on the Safety of Patients in E ngland, 37 National Association of Community Health Centers, 167 www.ebook3000.com Index National Center for Biotechnology Information, 254 National Committee on Quality Assurance Health Plan Employer Data and Information Set, 97, 206 National Committee on Vital and Health Statistics, 88 National Council for Quality Assurance patient-centered medical home standards, 122–124 National Guideline Clearinghouse, 223 National Health Serv ice (NHS), 34, 37, 61, 67, 218 National Institute for Health and Clinical Excellence (NICE), 218, 233, 234 National Institutes of Health precision medicine research, 252–253 National Integrated Accreditation for Healthcare Organizations (NIAHO), 52, 53 National Quality Forum, 93; clinical practice guidelines of, 220 Naylor, Mary, 190 near miss events: recovery phase in, 50; in team-based care, 132 Nemec, S. F., 249 networks of providers: assemblers of, 291–292; narrow, 290–291; provider costs in, 291, 292 neurological disorders, precision medicine in, 240, 241, 242, 243–244, 247 New Zealand, rate of adverse events in, 61 Next Accreditation System of ACGME, 79 NIAHO (National Integrated Accreditation for Healthcare Organizations), 52, 53 nicotine dependence, population health management in, 119, 120, 121f, 123f nighttime interventions in hospitals, sleep interruptions for, 325–326 nonphysician providers in primary care, 199–200 norm-referenced methods, 91 Norsworthy, Oscar, 345 Northwestern University, 331; Feinberg School of Medicine Institute for Healthcare Studies, 81 Nudge: Improving Decisions about Health, Wealth, and Happiness (Thaler & Sunstein), 338 367 nurse pract it ioners, 199–200; in retail clinics, 203, 206, 210 nurses: bedside shift reports of, 109–110; in V irginia Mason Production System, 24 nursing care mana gers in population health management, 116–117, 119, 120, 121–122, 126 nursing home quality, public reports on, 97 obesity, G rand-A ide visits in, 185–186 Omoigui, N. A., 93, 97 OncolIMPACT, 251 oncophysics, transport, 245, 250, 256 100,000 Lives Campaign, 53, 74 online patient communities, 151; in crowdsourced clinical t rials, 151; patient engagement in, 122, 154; in population health management, 122 online physician ratings and reviews, 330–333; accuracy of, 331; of Stanford Health Care, 343 open school of IHI, 82–83, 83f operating room: sponge and instrument count in, 43, 46, 49–50; time-outs in, 22, 23f, 46, 50 operational excellence, opioid therapy, genet ic factors and precision medicine in, 242–243 orders: computerized physician order entry, 35, 49, 62–64; electronic medication administration record on, 64–65; evidence-based, for MRI, 21, 22f; prevention of medication errors in, 35, 53, 62–65 org ani z at ional culture See culture, org an iz at ional Osler, William, 73 Ottawa Registry of Decision Aids, 274 outcome measures, 34; in bundled payments, 308, 309, 310; criteria on, 298f; hierarchical model on hospital mortality in, 90–91; hierarchy of importance in, 299, 299f; multiple regression models in, 91; patient-reported, 34, 107, 299; in pay for perform ance programs, 306; public reporting affecting, 95–98; public reporting of, 89, 90–92; risk adjustment 368 Index outcome measures (continued) in, 90–92; in value-based healthcare delivery system, 296, 298–299 outpatient care: bundled payments for, 308; cost and quality of healthcare in, 107–108, 114; errors in, 33; fee for serv ice in, 304; Grand-A ide serv ices in, 191; measuri ng costs in, 299, 302; mobile health technology in, 142–157; population health management in, 126, 127; retail clinics in, 197–213; telemedicine in, 171 ovarian cancer, precision medicine in, 249, 256 overutilizers of health resources, 116; Grand-A ide visits to, 181, 185 pain management, genet ic factors and precision medicine in, 241, 242–243 palliative care, Grand-A ide visits in, 184 pancreatic cancer, precision medicine in, 243, 250 Partners Healthcare, 63, 67 paternalistic decision making, 265 patient-centered healthcare, 32, 114, 285, 295; conven ience and access in, 292–293; in evidence-based medicine, 263–264, 265; in Robust Process Improvement, 9, 10f; in safety and quality improvement, 37; in shared decision making, 270; in team-based care, 130–131; in Virginia Mason Production System, 1 patient-centered medical homes (PCMHs), 113, 119, 122–124, 283, 3 07 Patient-Centered Outcomes Research Institute (PCORI), 88 patient engagement: in evidence-based medicine, 265; in mobile health technologies, 143, 154; in online communities, 122, 154; in population health management, 114, 119, 120–122; in selection of physician, 331–332; in team-based care, 130–131, 138–139 patient experience, 319–334; conven ience in, 292–293; data collection and analysis on, 322–333; e-m ail surveys on, 326–328, 327f; HCAHPS survey on, 321–322, 324, 326, 328; in Houston Methodist I CARE approach, 353; leadership commitment to, 5; online physician ratings and reviews based on, 330–333, 343; reduction of suffering in, 319–334; in shared decision making, 270; in Stanford Health Care C-I-CARE approach, 336–344; in team-based care, 130–131, 135; in Triple Aim, 129, 270; unmet needs in, 322, 324, 326; validity of data on, 330 patient–provider relationship: in Grand-A ide program, 182; in mobile health technology, 152–154; in population health management, 116–117, 119, 120–122, 126; in shared decision making, 266–276; in team-based care, 130–131, 134–137; in values-based practice, 133–137 patient registry data on healthcare outcomes, 87–88, 89–90 patient-reported outcome measures, 34, 107, 299 patient safety, 1–102; and annual deaths in error-related injuries, 3, 60, 61, 74; definition of, 31; in drug therapy, 61–66 (See also medication errors); frequency and types of incidents affecting, 32–33; health information technology in, 35, 60–68; high-reliability approach to, 3–15; indicators of, 33–34, 61; leadership commitment to, 5; measurement of, 33–35, 52–57; operating room time-outs for, 22, 46, 50; in org aniz at ional culture, 6–7, 35, 42–57 (See also culture of safety); perform ance improvement in, 7–15; in retail clinics, 209; in Robust Process Improvement, 9–15; in SafeCare Initiative, 36; in shared decision making, 270; storytelling impact on, 51; in team-based care, 131, 133, 137; in telemedicine, 174; training physician leaders on, 72–84; zero harm as goal in, 3, patient safety organizations (PSOs), 56 patients-a s-consumers, 284–285 patient satisfaction: access and conven ience affecting, 292–293; in Houston Methodist I CARE approach, 351, 354; in retail clinics, 207, 210; in Stanford Health Care C-I-C ARE approach, 336–344; in www.ebook3000.com Index team-based care, 130–131, 134, 139; in telemedicine, 172 PatientsLikeMe, 151 patient suffering, 319–334; avoidable, 323, 323t, 324, 325t; empathy in, 322; inherent, 323t, 323–324, 325t; in unmet needs, 322, 324, 326 Patterson, Kerry, 342 pay for perform ance programs, 306–307 payment systems, 73–74, 75, 84, 302–310; in accountable care organi zations, 307–308; in Affordable Care Act, 283; bundled, 308–310; capitation model in, 305–306; clinical practice guidelines as standard in, 219, 224, 228; current roles and relationships in, 285–287, 286f; diagnosis-r elated groups in, 72, 73; fee-for-s ervice model in, 283, 287, 296, 304–305, 309; global provider budg ets in, 305; insurance reform on, 281–294; population health management in, 114, 125, 126; quality and efficiency of care as f actors in, 106; in retail clinics, 200–201; in telehealth serv ices, 212–213; in value-b ased healthcare delivery, 296; value-b ased purchasing in, 306–307, 328 PDSA (plan-do-study-act) cycle, 36, 74 Peabody, Francis W., 73 Pennsylvania Health Care Cost Containment Council, 92 peptidomics, 244, 247–248 percutaneous coronary interventions, public reporting on, 92, 97–98 perform ance improvement, 7–15, 105; change management in, 9; culture of safety in, 5, 7; DMAIC approach to, 7–8, 8f; lean approach to, 8–9, 36; operational excellence in, 7; PDSA cycle in, 36, 74; Robust Process Improvement method in, 9–15; Six Sigma approach to, 7–8, 36–37, 105; in team-based care, 137 perform ance measures, clinical practice guidelines in, 219, 220 Peterson, E. D., 96, 97 Pew Research Center, 331 pharmacogenet ics, 241, 242 pharmacogenomics, 149, 241, 242 369 physician-a s-a gent model of decision- making, 266 physician assistants, 199–200; in retail clinics, 203, 206, 210 Physician Compensation Report (Medscape), 168 physicians: adherence to clinical practice guidelines, 227–231, 229f, 230t; autonomy of, 18, 49, 52, 53, 87, 98; compensation of, 168, 286; in culture of safety, 5–6, 46, 53; in decision-m aking process, 265–267; education and training of (See medical education); online reviews and ratings on, 330–333, 343; public reporting on, 92–93, 330–333; referrals by, 95, 109; in V irginia Mason Production System, 21, 24, 25 Piedmont Healthcare (Atlanta GA), 331, 332, 333 Pioneer ACO model, 3 07 plan-do-study-act (PDSA) cycle, 36, 74 pneumonia, clinical practice guidelines in, 222, 228 point-of-need testing, mobile health technology in, 149–151 population health management (PHM), 113–127; business model of, 126; components of, 114–115, 115f; data aggregation and analytics in, 113, 114, 115–117; engagement of patients in, 114, 119, 120–122; f uture sustainability and support for, 125–127; individualized healthcare plans in, 114, 117–118, 119–120, 126; mechanics of, 116f; in Medicare Shared Savings Programs, 114, 124–125; patient-centered medical homes in, 114, 119, 122–124; risk stratification in, 113, 114, 116, 117–119; team approach in, 131–132; in T riple Aim model, 129 Porter, M. E., 296, 313 positron emission tomography, 248, 250 Posner, Barry, 338 The Power of Habit: Why We Do What We Do in Life and Business (Duhigg), 341 practice-based learning in competency- based physician training, 78, 79 precision medicine, 239–256; as absolute necessity, 245–246; biomarkers of disease 370 Index precision medicine (continued) in, 253; in cancer, 240–241, 243–253, 256; clinical trial validation of, 251; funding of research on, 252–253; genet ic factors in, 240–247; in imaging techniques, 248–249, 250; multidisciplinary approach in, 245, 254; regulatory approval issues in, 245, 251–252, 256; in surgery, 249–250; and systems medicine, 251; and taxonomy of diseases, 244, 255; use of term, 239–240 Precision Medicine Initiative, 252, 254 preferred provider organizations, 287, 291 prescriptions: of antibiotics, unnecessary, 28–29; errors in, 33, 64; in retail clinics, 204, 206; in telemedicine, 172 Press Ganey, 350; national database on physician ratings, 332; patient experience survey of, 324; Stanford ranking in surveys of, 337 prevention of errors, 31, 32, 33; and adverse events, 35, 43, 61, 62, 66, 68, 128; in culture of safety, 42, 43, 45, 48–49, 51, 52, 57; and deaths from injuries in, 74; in drug therapy, 32, 35, 61, 62, 66, 68; health information technology in, 60, 61, 62, 66, 68; in high-reliability organ izations, 4, 35; in Robust Process Improvement, 14 preventive serv ices: Affordable Care Act on, 283; gap between recommended and a ctual care in, 227; in G rand-A ide visits, 181, 185–186; mobile health technologies in, 154; in population health management, 115, 117, 119, 123, 126; in retail clinics, 206; in team-b ased care, 132; in V irginia Mason Production System, 25 primary care practices: declining number of physicians in, 167–168; Grand-A ides in, 181, 184–185; nonphysician providers in, 199–200; population health management in, 114, 119–120, 125–126; problems in patient access to, 167–169; referrals to specialists from, 109; in retail clinics, 197; rooming process in, 24–25, 26f–27f; telemedicine in, 164, 169–171 priming effect, 341 privacy concerns: in online physician ratings, 331; in Precision Medicine Initiative, 254; in telehealth serv ices of retail clinics, 211–212 problem-solving, 37; DMAIC approach to, 7–8, 8f process-based report cards, 89 process improvement, 7; lean approach to, 8–9; Robust Process Improvement method in, 9–15; Six Sigma approach to, 7–8 process indicators on quality of care, 34 professionalism, competency-based physician training on, 78 Project BOOST, 191–192, 193t Project RED, 190–191, 193t prospective payments, 73 prospect theory, 343 prostate cancer, 250 proteomics, 244, 247–248 prototype development for decision aids, 268, 269f Provost, L. P., 19–20 public health campaigns, 132; mobile health technologies in, 155–156 public reporting, 87–98; administrative data in, 89–90; and avoidance of high-r isk patients, 97; Bayesian methods in, 92; in bundled payment system, 310; consumer benefits of, 94–95; on coronary artery bypass graft surgery, 89, 90–97; criterion- referenced methods in, 91; data sources for, 89–90; hierarchical models in, 90–91; on high-value clinical teams, 107; on individual surgeons, 92–93; multiple regression modeling in, 91; norm-referenced methods in, 91; online physician ratings and reviews in, 330–333, 343; outcomes-b ased, 89, 90–92; process-based, 89; at program level, 93; on readmission rates, 92; registry data in, 87–88, 89–90; risk adjustment in, 90–92, 95–96, 97; types of information in, 92–94 quality assurance in retail clinics, 204–205, 206, 207–210 quality improvement, 1–102; appropriate use criteria in, 220, 221; clinical practice www.ebook3000.com Index guidelines in, 217, 222–223, 231; with cost reduction, 105–111; high-reliability approach to, 3–15; Institute of Medicine report on, 32; leadership commitment to, 5; measurement indicators in, 33–34, 36–37, 89, 220; patient safety in, 6–7 (See also patient safety); PDSA cycle in, 36, 74; perform ance improvement methods in, 7–15; public reporting in, 87–98; Robust Process Improvement approach to, 9–15; SafeCare Initiative on, 36; standards in, 36; team-based care in, 128, 129, 133, 137; telemedicine in, 164; training physician leaders on, 72–84; Virginia Mason Production System approach to, 17–29 quality indicators, 33–34, 36–37; in clinical practice guidelines, 219, 220; process- based report cards on, 89 QuickMedx, 200–201, 205 RAND study of telemedicine, 173–174 Rapid Process Improvement Workshops (RPIWs), 25 rapid response teams, 53 readmission rates: in G rand-A ide program, 178, 181, 184, 187–188, 192–194; healthcare costs associated with, 187–188; in population health management, 117; public reporting on, 92 Reason, James, 42, 43, 47, 53 reckless beh avior in just culture model, 47 recovery strategies in culture of safety, 47–48, 50–51 Red Cross Hospital (Beverwijk, Netherlands), 12 RediClinic of Rite Aid, 199, 208t redundancy in culture of safety, 48, 52 referrals: costs and quality of care as factors in, 109; public report cards affecting, 95; from retail clinics, 204 registry data on healthcare outcomes, 87–88, 89–90 regulatory approval issues in precision medicine, 245, 251–252, 256 rehabilitation, mobile health technologies in, 148–149 371 relative value unit system, 299–300 reliability: definition of, 48; in high- reliability healthcare, 3–15; prevention strategies improving, 48–49; in team- based care, 132 report cards on healthcare, 88–89; consumer benefits of, 94–95; in coronary artery bypass graft surgery, 89, 90–97; outcomes-based, 89; process-based, 89 reporting systems, 34–35; anonymous reporting of incidents in, 34; on coronary artery bypass graft surgery, 89, 90–97; in culture of safety, 5, 35, 47, 51, 52, 53, 56; public, 87–98 (See also public reporting) residency programs: competency requirements in, 78; historical development of, 73 resource-based relative value scale, 300 respect, in Houston Methodist I CARE approach, 345–354 respiratory disorders: antibiotic therapy in, 28; mobile health technologies in, 147–148, 155; precision medicine in, 244 retail clinics, 197–213, 285; cost of healthcare in, 107; definition of, 202; as disruptive innovation, 197–199, 207, 211; f uture directions for, 210–213; historical development of, 197–199; initial uncertainty about, 198, 206–207; operational hours of, 203; in partnerships with hospitals and medical groups, 207, 208t; patient flow in, 203–204; in population health management, 125; quality assurance in, 207–210; serv ices offered in, 200–201, 203, 210–213; sociodemographics of patients in, 202f; staff of, 203; telehealth serv ices of, 211–213; timing of visits to, 201f–202f return on investment in improvement programs, 11, 12 reward mechanisms: in Houston Methodist I CARE approach, 349–350, 351; in Stanford Health Care, 341, 343 risk adjustment in outcomes reporting, 90–92, 95–96, 97 risk of behavior in just culture model, 47 risk stratification in population health management, 113, 114, 116, 117–119 372 Index Rite Aid, retail clinic of, 199, 208t RNA sequencing technology, 247 Roberts, N. J., 243 Robust Process Improvement (RPI), 9–15; change leaders in, 14; education and training in, 11, 12, 13–14; leadership commitment to, 11–12; patient-centered processes and outcomes in, 9, 10f; project selection in, 12 rooming process in primary care, standardization of, 24–25, 26f–27f root cause analysis, 50 Rosenbluth, Hal, 204, 205 Rosenthal, G. E., 96 rule-b ased work, 43–45; accountability for errors in, 55f; cost of healthcare delivery in, 107; in heparin therapy, 46–47; transition from knowledge- based work to, 44, 51 SafeCare Initiative, 36 Safety Attitudes Questionnaire, 35 safety of patients See patient safety St. Peter’s Hospital (Albany NY), 96 SARS (severe acute respiratory syndrome), 155 SBAR (situation, background, assessment, and recommendation) process, 49 Schoen, Michelle, 347 Seattle Children’s Hospital, 74 sensors in wireless body network systems, 143–149; types of, 145 sentinel events, 46; reporting of, 52; root cause analysis in, 50 sentinel lymph node dissection, molecular imaging in, 250 sepsis treatment: conflicts of interest in guidelines on, 224; reducing variation in, 23–24 Shahian, D. M., 92 Shalala, Donna, 205 shared decision making, 262, 266–276; decision aids in, 267–268, 271, 272f, 273, 274–275; documentation and measure ments in, 273; evidence of value for, 271; f uture directions of, 272–275; importance of, 269–270; pending research in, 274–275; policy challenges in, 274; process of, 271–272; role in evidence- based medicine, 275–276 Shared Decision Making National Resource Center (Mayo Clinic), 274 Shen, H., 249 Shewhart, Walter, 74 Shewhart cycle, 36, 74 shock, septic, 23 short message serv ice (SMS) texting, 156 Silver, Henry, 199 Singh, H., 67 single nucleotide polymorphisms, 242 single-photon emission computed tomography (SPECT), 250 situation, background, assessment, and recommendation (SBAR) process, 49 Six Sigma approach, 7–8, 36–37, 105; in Robust Process Improvement, 9–11, 12, 1 skill-based work, 43, 44, 45; accountability for errors in, 54f–56f sleep: in hospitals, nighttime interventions affecting, 325–326; mobile health technologies in monitoring of, 146–147 smartphone technology, 149–151; in crowdsourced health research, 151; in population health management, 121; in telemedicine, 164; in wireless body sensor networks, 145, 146–147 smart pump technology, 65–66 Smith, Douglas, 200 SMS (short message serv ice) texting, 156 social networking: crowdsourced clinical t rials in, 151; in population health management, 122 Society of Thoracic Surgeons (STS), 98; CABG composite score of, 92, 93t, 93–94, 94f; star rating system of, 91, 94, 94f socioeconomic factors in population health management, 117, 118–119 Sparks, Ashlee, 347 SPECT (single-photon emission computed tomography), 250 sponge count in surgery, 43–44, 49–50 Stanford Health Care, 336–344; C-I-CARE approach in, 336–344; design of facilities in, 342f, 342–343; reward mechanisms in, 341, 343 Stanford Operating System, 339 www.ebook3000.com Index Stanford University: health care system affiliated with, 336–344; mobile technology in cancer screening, 151 state-based exchanges for health insurance, 282, 288, 289 The State of Aging and Health in America (CDC), 169 Statin Choice Decision Aid, 272f, 273, 274 statin therapy, shared decision making on, 271–272, 272f, 273 Stauffer, B. D., 192 Stead, Eugene, 199 storytelling, role in patient safety, 51 Strength of Recommendation Taxonomy (SORT) method, 21 stress management, wireless body sensor network systems in, 145–146 stroke rehabilitation, wireless body sensor network systems, 148 structural indicators on quality of care, 34 suffering of patients, 319–334 See also patient suffering Sunstein, Cass, 338 surgery: appropriateness test of, 29; avoidance of high-r isk patients in, 97; Google Glass technology in, 152; image-g uided interventions in, 249; operating room time-outs in, 22, 23f, 46, 50; patient preference for lower cost options in, 108; in precision medicine, 249–250; public reporting on outcomes in, 88–98; sponge and instrument count in, 43–44, 46, 49–50 Survey of America’s Physicians: Practice Patterns and Perspectives, 168 Sutcliffe, K., 4, 46 sweat analysis with mobile health technologies, 149 Switch: How to Change T hings When Change Is Hard (Heath), 340 Switzler, Al, 342 systems-based practice, competency-based physician training on, 78, 79 systems medicine, and precision medicine, 245, 246, 251 Take Care Health Systems, 204, 205, 210 Tantisira, K. G., 242 373 Target, retail clinics of, 199, 208t taxonomy of diseases, precision medicine affecting, 244, 255 team approach, 128–139; Affordable Care Act on, 283; composition of teams in, 134–135; in culture of safety, 45–46, 47, 49–50, 57; education and training for, 128, 129, 137–139; enhancing patient experience in, 130–131, 135; healthcare costs in, 129, 132–133; historical perspective of, 129–130; in integrated practice units, 298; patient engagement in, 130–131, 138–139; patient goals in, 134, 136–137; patient values in, 131, 134, 135, 136–137; in population health management, 131–132; in Triple Aim model, 129–130; in values-based practice, 133–137; in V irginia Mason Production System, 20, 22, 24 TeamSTEPPs program of AHRQ, 46 technology, 35, 60–68; access to health information with, 152–153; artificial intelligence in, 110, 144; augmented and virtual reality systems in, 152; bar-code systems in, 35, 64–65; computerized physician order entry (CPOE) in, 35, 49, 53, 62–64; cost and value of healthcare delivery using, 105, 106, 110; and crowdsourced clinical t rials, 151; electronic health records in (See electronic health records); electronic medication administration records in, 64–65; and e-m ail surveys on patient experience, 326–328; in Grand-A ide visits, 182–183; mobile health, 142–157 (See also mobile health technologies); in monitoring, 67, 110, 143–149, 156, 172; and online patient communities, 122, 151, 154; and online physician reviews, 330–333, 343; and patient engagement, 121, 122, 154; in patient safety, 35, 60–68; in point-of-need testing, 149–151; in population health management, 121, 122, 124, 125–126; and provider–patient relationship, 121, 152–154; smartphone (See smartphone technology); telemedicine in, 163–176; in test follow-up, 66–67; in value-based healthcare delivery system, 311–313, 312t; 374 Index technology (continued) wireless body sensor network systems in, 143–149 Teladoc serv ice, 165, 167, 170–171, 172, 173; RAND study of, 173–174 telehealth serv ices, 166; in Grand-A ide program, 192, 193t; legal definitions of, 212; privacy concerns in, 211–212; in retail clinics, 211–213 telemedicine, 163–176; asynchronous interactions in, 171–172; common conditions treated in, 172, 174, 174t; definition of, 166; examples of physician visits in, 165–166; in Grand-A ide program, 178, 182–183, 192, 193t; RAND study of, 173–174; in retail clinics, 211–213; synchronous interactions in, 171; Towers Watson–N BGH survey on, 174–175 testicular cancer, 245 test results: alerts provided on, 67; health information technology in follow-up on, 66–67; with mobile health technology, 149–151 Thaler, Richard, 337–338 ThedaCare (Appleton WI), 74 Thinking, Fast and Slow (Kahneman), 337 time-d riven activity-based costing, 300–302, 301f, 302f; in bundled payments, 309, 310; value-added opportunities for, 303t timeliness of care, 32 time-outs, presurgical: in culture of safety, 46, 50; variation in, 22, 23f tiny habit change, 338–339 To Err is H uman (Institute of Medicine), 3, 31–32, 36, 43, 74 Towers Watson–National Business Group on Health survey, 174–175, 176 Toyota, results of perform ance improvement in, Toyota Production System, 74; Stanford Operating System adaptation of, 339; Virginia Mason Production System adaptation of, 17, 18, 20 transcription errors in drug therapy, 35, 61, 64, 65 transcriptomics, 244, 247 transformation, compared to change, 194 transient ischemic attack (TIA), cost of healthcare delivery in, 107–108 transitional care, G rand-A ide visits in, 181–183, 184, 190–192, 193t transparency: in costs and pricing, 176, 203, 209; in culture of safety, 42, 43, 51, 52, 53, 57; in guideline-based medicine, 223, 225, 225t; in network inclusion or exclusion, 292; in online reviews of physicians, 330–333; public reporting in, 89; public trust and confidence in, 332; in transformation of healthcare, 75; in values-based medicine, 137 transport oncophysics, 245, 250, 256 Tricoci, P., 224 Triple Aim, 129–130, 270 tropical storm Allison, response of Houston Methodist to, 349 trust: in culture of safety, 5, 6f, 52; in data transparency, 332; in Grand-Aide relationship, 178, 179; in Houston Methodist workplace, 350; in population health management, 121–122; in shared decision making, 267; in team-based care, 137 Tversky, Amos, 343 23andMe, 151 type of work: and accountability for errors, 53, 54f–56f; Reason classification of, 42, 43, 53 Ukimura, O., 249 ultrasound, handheld equipment for, 150 underutilizers of health resources, 116, 117 United Kingdom: developers of clinical practice guidelines in, 218, 233, 234; Manchester Patient Safety Framework in, 35; National Health Serv ice in, 34, 37, 61, 67, 218; outpatient treatment of TIA in, 108; Quality Commission in, 60; rate of adverse events in, 61 United States Preventive Serv ices Task Force (USPSTF), 218, 219, 223 University Healthsystem Consortium, 83 University of California, Davis, 200 University of Colorado, 199 www.ebook3000.com Index 375 University of Pittsburgh Medical Center, volume of data collected in, 330 University of Texas MD Anderson Cancer Center, 311, 311f University of Utah Health Care: census- based surveys of, 329; e-m ail surveys of, 327–328; online physician ratings of, 331, 332, 333; volume of data collected by, 330 University of Virginia, Grand-A ide program in, 178, 179, 184 University of Washington School of Medicine, 200 Unmet Needs (Lucian Leape Institute), 75 unmet needs of patients and clinicians, 105, 106, 109–110; in professional education on patient safety, 75; suffering of patients in, 322, 324, 326 utilization of health resources, 116–117; Grand-A ide visits affecting, 181, 185; insurance coverage affecting, 289–290 p rocess, 24–25, 26f–27f; in sepsis treatment, 23–24; V irginia Mason Production System approach to, 17–29; as waste, 20 Veterans Administration: alerts on abnormal test results in, 67; clinical practice guidelines in, 231; global provider budgets in, 305 Virginia Mason Production System, 17–29, 74; antibiotic therapy in, 24, 28–29; appropriateness test in, 29; clinical value stream process in, 20, 21; decision rules in, 21; literat ure review in, 21; presurgical time-outs in, 22, 23f; rooming process in, 24–25, 26f–27f; sepsis treatment in, 23–24; strategic plan in, 18, 19f virtual reality, 152 Vision for the Second C entury of Houston Methodist, 351–352, 3 52f volume-based healthcare delivery, 295, 296 validity of data, 3 30 value-based healthcare delivery, 295–313; cost measures in, 296, 299–302; geographic expansion of serv ices in, 310–311, 311f; information technology in, 311–313, 312t; outcome measures in, 296, 298–299; payment models in, 306–310; strategic agenda in, 296, 297f value-based insurance design (VBID), 307 value-based purchasing programs, 306–307, 328 value of healthcare, 295–313; in Affordable Care Act, 287; with higher quality and lower costs, 105–111 values-based practice: in Houston Methodist I CARE approach, 345–354; team approach in, 133–137 van der Poel, H. G., 250 variation, intended: differentiated from unintended or unnecessary variation, 19–20; in surgery, 22 variation, unintended or unnecessary: in antibiotic therapy, 28–29; differentiated from intended variation, 19–20; DMAIC approach to, 7–8, 37; in presurgical time-outs, 22, 23f; in rooming Wacholder, S., 243 wait times for healthcare, 32, 170, 209, 292; in emergency room, 153; in global provider budgeting, 305; in primary care practices, 168–169; in Stanford Health Care, 342 Wake Forest Baptist Health (Winston-Salem NC), 331, 333 Walgreens, retail clinic of, 199, 204, 205, 208t, 210, 285 Walmart, retail clinic of, 199, 285 waste reduction, 37; in unintended variation, 20 Weick, K., 4, 46 Weill Cornell Medical College Institute for Precision Medicine, 255 wellness programs: mobile health technologies in, 145; in population health management, 116, 119, 122; in retail clinics, 203 Werner, R. M., 89 white coat hypertension, 122 WHO (World Health Org an iz at ion), 33, 80, 81t, 143 Williams, Mark, 191 Winthrop Hospital (NY), 96 376 Index wireless body sensor networks (WBSN), 143–149; architecture of, 144f; types of sensors in, 145 workforce engagement in Houston Methodist I CARE approach, 345–354 World Health Org an iz at ion (WHO): on frequency of patient safety incidents, 33; on mobile health technologies, 143; patient safety curriculum of, 80, 8 1t Yale-New Haven Hospital, reducing nighttime interventions in, 325–326 yellow b elt trainees in Robust Process Improvement, 14 zero defects, zero harm, 4; leadership commitment to, Zhang, J., 243 Zhu, J., 248 www.ebook3000.com ...America’s Healthcare Transformation Strategies and Innovations www.ebook3000.com America’s Healthcare Transformation Strategies and Innovations Edited by Robert A Phillips... New Jersey, and London Library of Congress Cataloging-in-P ublication Data Names: Phillips, Robert A., 1951–, editor Title: America’s healthcare transformation : strategies and innovations. .. Part IV Healthcare Reform and New Payment Methods 18 The Rise of Consumerism and How Insurance Reform Will Drive Healthcare Delivery Reform 281 James L Field 19 Creating the Healthcare Transformation

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