Provider-Led Population Health Management

Richard Hodach, MD, MPH, PhD, is Vice President, IBM Watson Health, previously serving as Chief Medical Officer and Vice President of Clinical Product Strategy at Phytel, now part of IBM Watson Health. Dr. Hodach has long been recognized as a leader of population health management strategies. He is responsible for providing strategic direction and clinical expertise for the development of Phytel's solutions. Dr. Hodach is a regular contributor to prestigious peer]review journals such as The American Journal of Managed Care, The Journal of Population Health Management, hfm (published by the Healthcare Financial Management Association), The Group Practice Journal, and more. He was instrumental in the CMS Innovation Award of a $20.75 million grant which Phytel, VHA Inc., and TransforMED received from The Center for Medicare & Medicaid Innovation (CMMI). In addition to his leadership position at Phytel, Dr. Hodach also serves on the board of directors of the American College of Medical Quality. Before joining Phytel, he held senior leadership positions at Matria Healthcare and Accordant, and co]founded MED.I.A. Dr. Hodach has a Ph.D. in Pathology and an M.D. with Board Certification in Neurology and Electrodiagnosis, as well as a Master's Degree in Public Health.Paul Grundy, MD, MPH, is Global Director, Healthcare Transformation at IBM, and President of the Patient]Centered Primary Care Collaborative. Dr. Grundy is known as the "godfather" of the patient]centered medical home. An active social entrepreneur and speaker on global healthcare transformation, he concentrates his efforts on driving comprehensive, linked, and integrated healthcare. Dr. Grundy's work has been covered by The New York Times, BusinessWeek, Health Affairs, The Economist, The New England Journal of Medicine, and other newspapers, radio, and television stations across the U.S. He is a healthcare ambassador for the nation of Denmark and adjunct professor at the University of Utah Department of Family and Preventive Medicine. Dr. Grundy is a member of National Academy of Science's Institute of Medicine, director of the ACGME, and member of the national advisory board of the National Center for Interprofessional Practice & Education, Mayo Clinic Center for Connected Care. He is a retired senior diplomat with the rank of Minister Consular U.S. State Department. Dr. Grundy graduated as valedictorian from the Southern California College, earned an M.D. from the University of California–San Francisco Medical School, and received a Masters of Public Health from the University of California–Berkeley.Anil Jain, MD, FACP, is Senior Vice President and Chief Medical Officer, IBM Watson Health, previously serving as Chief Medical Officer of Explorys FOR SCREEN VIEWING IN BPA ONLY(now part of IBM Watson Health), formed in 2009 based on innovations that he developed while at the Cleveland Clinic. In this role, Dr. Jain directs the informatics and analytics innovations, product management, and software development, as well as leading the life sciences business unit. In addition to serving on state and national committees focused on driving quality and research through health IT, he has authored more than 100 publications and abstracts and has delivered numerous talks on the benefits of sustainable health IT innovation, clinical informatics, and big data analytics. Dr. Jain also continues to practice and teach medicine part]time in the Department of Internal Medicine at Cleveland Clinic and had previously served as an Attending Staff and Senior Executive Director of IT. He is a former leader at Better Health Greater Cleveland and had served as co]Director of Informatics of Case Western School of Medicine's CTSA. Dr. Jain is an active member of the Health Information Management & Systems Society (HIMSS) and the American Medical Informatics Association (AMIA), and is a Fellow of the American College of Medicine (ACP), and is also a Diplomat of the American Board of Internal Medicine (ABIM). He received a degree in Biomedical Engineering and a degree in Medicine from Northwestern University prior to his post]graduate training in Internal Medicine at the Cleveland Clinic.Michael Weiner, DO, MSM, MSIST, is Chief Medical Information Officer at IBM. Prior to his current position with IBM, Dr. Weiner served as the Chief Medical Information Officer and Director of Clinical Informatics for the DoD VA Interagency Program Office, where he was responsible for creating a unified Interagency Electronic Health Record for more than 125,000 providers and 18 million beneficiaries worldwide. He is an active member of the American College of Physicians and the American Osteopathic Association, and is a former NASA Space Shuttle takeoff and landing physician. Dr. Weiner serves on the Philadelphia College of Osteopathic Medicine Alumni Board and the board of the American Medical Informatics Association, as well as having served on the Health and Human Services' Office of the National Coordinator Health Information IT Policy Committee, helping create Meaningful Use Stage 1. He has received numerous awards from the President of the United States, for his service in the Navy, including two Meritorious Service Medals, and two Air Medals. Dr. Weiner is an adjunct professor of Health Information Technology at the George Washington University and is one of only a few physicians ever to have been certified as a Chief Information Officer by the U.S. General Services Administration. He is a graduate of the U.S. Naval Academy and attended medical school at the Philadelphia College of Osteopathic Medicine. Dr. Weiner is a board-certified practicing physician in Internal Medicine, and holds a Master's degree in Management and a Master's degree in Information Systems Technology from George Washington University.

• Acknowledgments  viForeword  xiiiIntroduction  1Section 1: New Delivery Models  91 Population Health Management 11What Is Population Health Management? 13Key components 14Obstacles to PHM 16The Beginnings of Change 17Examining the crucial role of automation 18Managing the entire population 19The Three Pillars of PHM 20Conclusion 222 Accountable Care Organizations 25The ACO Environment 27Government support 28ACO snapshots 29Population health management 31The role of information technology 32Automation and analytic tools 33Conclusion 353 Patient-Centered Medical Homes 37Initial Results Are Promising 38Managing the Medical Neighborhood 40PCMH Background 40Medical home certification 41Challenges and solutions 43Building the medical neighborhood 44How much will it cost? 45Role of Information Technology 46Automation tools 47Conclusion 50Section 2: How to Get There  514 Clinically Integrated Networks 53Clinically Integrated Networks 54Current definition 56Basic requirements 56Automation tools and CINs 58Risk stratification 59Patient outreach 60Care management 60Patient engagement 61Post-discharge care 63Performance evaluation 63The Need for Speed 64Conclusion 645 Meaningful Use and Population Health Management 67Meaningful Use Overview 68Meaningful Use nuts-and-bolts 70Upping the ante in Stages 2 and 3 71PHM Components of Meaningful Use 71Clinical decision support 72Patient engagement 72A leap forward for PHM 73Health information exchange 74MIPS and MACRA 76Conclusion 776 Data Infrastructure 79Data Sources 83Administrative data 83Clinical data 84Claims data 84Patient-generated data 85Provider attribution 86Patient matching 87Unstructured data 87Data governance 88Big Data’s Role 88Data lake approach 89Data normalization 91Analytics 91Registries 92Work lists 93Predictive modeling 93Risk stratification 94Performance evaluation 95Timely Response 95Other Big Data Directions 96Conclusion 977 Predictive Modeling 99Predictive Modeling Basics 101Turning Predictions into Action 103Prescriptive analytics 104Risk stratification 104Directing resources 105Making a difference 105Automation tools 106Clinical judgment and culture 107Provider Attribution 108Risk Adjustment 109Financial Risk 110Data Sources 112Claims data 113Clinical data 113Patient-reported data 114Broadening the data palette 115Conclusion 1168 Automation Solutions and the ROI of Change 119Transition to value-based payments 121The new return on investment 123Automated Population Health Management 124How Automation Produces ROI 126Patient outreach 126Analytics 127Care management 128Patient engagement 128Transitions of care 129How to Calculate ROI 130Patient outreach: Additional visit revenues 131Pay-for-performance: Maximizing incentives 131Risk contracts: Lowering overall costs 132The bottom line 132Conclusion 133Section 3: Implementing Change  1359 Care Coordination 137Defining Care Coordination 139The Physician Group Practice Demonstration 140The Patient-Centered Medical Home 141Technology solutions 142NCQA criteria 143Technology Use in Care Coordination 145Key building blocks 146Continuum of care 148Conclusion 14910 Lean Care Management 151A Lean Foundation in Health Care 154High-Performing Practices 157Performing at top of license 158Care-coordination approaches 159Lean Care Management 160Automation in Lean Processes 162Basic automation tools 163Top-of-license approach 166Downstream value 166Conclusion 16711 Patient Engagement 169The Physician-Patient Relationship 171How to Engage Patients 172Activation models 173Obstacles to patient engagement 174Care Management 175Patient outreach 175Risk stratification 176Patient education 177Telemedicine 178Mobile health apps 179Personal health records 180Social media 181Conclusion 18212 Automated Post-Discharge Care 185New Government Incentives 186Gaps in Care Transitions 188Poor educational techniques 188Poor handovers 189Best Practices 190IHI’s patient-centered approach 190Coleman Care Transitions Intervention 191Naylor Transitional Care Model 191Automation 192Assessing patient risk 193Patient education and engagement 194Connecting providers to each other 194Conclusion 19513 Social and Behavioral Determinants of Health 197SDH Impact on Health 200Approaches to SDH 201Model 1: Targeting health behaviors 201Model 2: Referral to community services 203Model 3: Targeted social support within a healthcare framework 204Model 4: Patient-centered medical homes 205Model 5: Holistic care management 206Behavioral Health 208Advantages of integration 209Solving the SDH Puzzle 210Team-based approach 212Harnessing technology 213Other data sources 214Conclusion 21614 Cognitive Computing: The Future of Population Health Management 219Cognitive Computing 101 223IBM Watson arrives 224Natural Language Processing 225Unstructured EHR data 226Medical literature 228Data Types 228Genomic data 229Imaging data 230Monitoring data 230Non-healthcare data 232Population Health Management 232Predictive modeling 233Patient engagement 234Care coordination 235Workflow integration 235Conclusion 236Conclusion  239End Notes 241