Provider-Led Population Health Management: Key Strategies for Healthcare in the Cognitive Era

Table of Contents

Cover

Title Page

Copyright Page

About the Authors

Credits

Acknowledgments

Foreword

Introduction

Changing the Mindset

Current Trends

Patient Engagement

A Roadmap for Population Health Management

What This Book Is About

Section 1: New Delivery Models

Chapter 1: Population Health Management

What Is Population Health Management?

The Beginnings of Change

The Three Pillars of PHM

Conclusion

Chapter 2: Accountable Care Organizations

The ACO Environment

Conclusion

Chapter 3: Patient‐Centered Medical Homes

Initial Results Are Promising

Managing the Medical Neighborhood

PCMH Background

Role of Information Technology

Conclusion

Section 2: How to Get There

Chapter 4: Clinically Integrated Networks

Clinically Integrated Networks

The Need for Speed

Conclusion

Chapter 5: Meaningful Use and Population Health Management

Meaningful Use Overview

PHM Components of Meaningful Use

Conclusion

Chapter 6: Data Infrastructure

Data Sources

Big Data's Role

Analytics

Timely Response

Other Big Data Directions

Conclusion

Chapter 7: Predictive Modeling

Predictive Modeling Basics

Turning Predictions into Action

Provider Attribution

Risk Adjustment

Financial Risk

Data Sources

Conclusion

Chapter 8: Automation Solutions and the ROI of Change

Automated Population Health Management

How Automation Produces ROI

How to Calculate ROI

Conclusion

Section 3: Implementing Change

Chapter 9: Care Coordination

Defining Care Coordination

The Physician Group Practice Demonstration

The Patient‐Centered Medical Home

Technology Use in Care Coordination

Conclusion

Chapter 10: Lean Care Management

A Lean Foundation in Health Care

High‐Performing Practices

Lean Care Management

Automation in Lean Processes

Conclusion

Chapter 11: Patient Engagement

The Physician‐Patient Relationship

How to Engage Patients

Care Management

Conclusion

Chapter 12: Automated Post‐Discharge Care

New Government Incentives

Gaps in Care Transitions

Best Practices

Automation

Conclusion

Chapter 13: Social and Behavioral Determinants of Health

SDH Impact on Health

Approaches to SDH

Behavioral Health

Solving the SDH Puzzle

Conclusion

Chapter 14: Cognitive Computing: The Future of Population Health Management

Cognitive Computing 101

Natural Language Processing

Data Types

Population Health Management

Conclusion

Conclusion

Endnotes

End User License Agreement

List of Tables

Chapter 03

Table 3-1: Identification of Automation Opportunities in Manual Care Management Process

Chapter 10

Table 10-1: Leaning Out Eight Types of Waste in Primary Care

Chapter 13

Table 13-1: Models for Addressing SDH

Provider-Led Population Health Management:

Key Strategies for Healthcare in the Cognitive Era, 2nd Edition

Richard Hodach, MD, MPH, PhD

Paul Grundy, MD, MPH

Anil Jain, MD, FACP

Michael Weiner, DO, MSM, MSIST

Provider-Led Population Health Management: Key Strategies for Healthcare in the Cognitive Era, 2nd Edition

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John Wiley & Sons, Inc.

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Copyright © 2016 by John Wiley & Sons, Inc., Indianapolis, Indiana

Published simultaneously in Canada

ISBN: 9781119277231

ISBN: 9781119277255(ebk)

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About the Authors

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 (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.

Credits

Associate Publisher: Jim Minatel

Vice President, Professional Technology & Strategy: Barry Pruett

Editorial Manager: Rev Mengle

Project Editor: Paul Levesque

Copy Editor: Becky Whitney

Production Editor: Barath Kumar Rajasekaran

Special Help: Camille Graves

Cover Designer: Michael Trent

ACKNOWLEDGMENTS

We would like to thank the extraordinary group of people who made significant contributions to this book. Without them, this book would certainly not exist.

Bill Buck

Ted Courtemanche

Donna Daniel

Jerry Green

Jon Mark Harmon

Jeffrey Havlock

Guy Mansueto

Adam McCoy

Jorge Miranda

Russell Olsen

Marina Pascali

Mavis Prall

Kristy Sanders

Steve Schelhammer

Carly Sheppard‐Knoll

Ken Terry

FOREWORD

Health care in the U.S. does not function as an effective system for a variety of well‐documented reasons, as I pointed out in my introduction to the textbook Population Health: Creating a Culture of Wellness. With a strong push from the federal government, as well as private payers, the U.S. health care industry is slowly pivoting toward value‐based reimbursement. This transition to income for outcome will incentivize health care providers to pay more attention to non‐visit care and will induce health care organizations to start managing the health of their patient populations, not just their health care. Only by doing so can they hope to reduce costs and improve quality enough to succeed financially under the new payment models. Moreover, to manage care properly, disparate health care providers and institutions will have to cooperate with each other to build a real health care system.

The premise of this book, contained in its title, is that population health management (PHM) cannot succeed unless physicians, their care teams, extended care networks, and community resources align with each other. It makes a whole lot of sense for doctors to play a leading role in population health management. Outside of friends and family, consumers trust physicians more than any other health care constituency, and certainly more than insurance or drug companies. The doctor‐patient relationship is the key to patient engagement, which can lead to improved medication adherence, evidence‐based guideline compliance, and lasting, sustainable health behavior change.

Written by the experienced team at IBM Watson Health, the book focuses sharply on the practical mechanics of how healthcare organizations can transition to population health management. While generous dollops of theory are also provided, the most germane parts of the book describe the practice of this new model (to most practitioners) of health care delivery.

For example, consider the chapters about consumer engagement and the social determinants of health. Individual engagement is a prerequisite of population health management; without it, people are less likely to make the lifestyle changes required to prevent or reduce the impact of chronic illnesses. But to get individuals engaged and support them in self‐care management, health care providers must also be aware of the social determinants of each person's health. As noted in Chapter 13, clinical health care accounts for only 10%‐25% of the variations in individual health over time. Health care's influence on the length of quality life would be markedly augmented, however, if it were combined with efforts to improve the social, economic, emotional, and physical environmental factors that contribute to health.

Research supports the need for population health management to extend beyond health care. Collaboration among providers on care coordination will ultimately need to incorporate social services, behavioral health, job placement and advancement, housing, and possibly spiritual and other community resources.

During my tenure in many population health leadership roles, including being the Global Medical Leader of GE and Corporate Medical Director for Truven Health Analytics, I learned the importance of paying attention to all health determinants, especially in engaging non‐adherent individuals. Often their adherence can be supported by enlisting other domains for assistance. Many people are more inclined to manage their own care, for example, after establishing a home to live in and finding a steady job.

Another theme that runs through the book is the need to build a health IT infrastructure that can support population health management. Initially, many health care delivery systems assumed that they could simply rely on their EHR vendor to give them everything they needed. But experience has demonstrated that the EHR is only a starting point. It requires additional advanced data sources, cognitive analytics, secure, cloud‐based platforms and mobile capabilities to establish a robust population health solution.

Moreover, PHM requires the ability to aggregate, normalize and analyze data from many different sources. Individuals receive their care across multiple care settings; many different care providers function inside a variety of delivery systems; and members of accountable care organizations (ACOs) utilize many different EHRs and patient portals. To connect these providers and health records requires the pursuit of interoperability, which is still largely lacking in health IT systems. These systems also lack the kind of clinical decision support and automation tools needed to facilitate care management and to make it efficient and effective. Longitudinal care coordination will ultimately require a personal health record that includes data from all care settings in which the patient has been treated.

The book's final chapter takes an in‐depth look at the exciting developments in cognitive computing, which has the potential to take health care and PHM to a whole new level. A next‐generation big data approach, cognitive computing can help health care organizations understand their populations better by providing insights into factors such as demographics, geographical location, behavioral health, transportation, lifestyle choices, consumer purchases, and socioeconomic status.

Cognitive computing can also search the medical literature in seconds, can use natural language processing to convert unstructured data into structured data, can improve predictive modeling, and can provide the analytic power to help physicians understand the genomic information about the people on their panel. This is what doctors will need in 21st century medicine. On their own, they will never be able to absorb more than a tiny fraction of the 1 million new published articles that come out each year. And with the emergence of genomics, proteomics, and microbiomics data, analytics will be an essential part of everyday medicine. Doctors will require significant learning — indeed, cognitive — computing resources to determine the relevance of all this data so they can provide highly personalized care, precision medicine, and the most appropriate care pathway for each person.

The most valuable lesson you will gain from this book, however, is that health care providers can impact the health status of the communities they serve. By doing so, they can improve the health of individuals and can also contribute to their performance as workers and as family and community members. The potential impact is enormous. This can lead not only to a higher quality of life for individuals, but also to enhanced productivity for employers and greater prosperity for communities.

Ray Fabius, MD

Co‐founder, HealthNext

Former Chief Medical Officer, Truven Health Analytics, and GE Global Medical Leader

INTRODUCTION

The $3.2 trillion healthcare industry, as conventional wisdom has it, is a big ship to turn around. But employers, consumers, and government can no longer afford healthcare costs that, while growing more slowly than in past years, have reached stratospheric levels.1 The fee‐for‐service payment system that rewards providers for the volume of services has been implicated in the high cost of health care.2 So, with a concerted push from payers, the industry is in the midst of a rapidly accelerating shift from fee‐for‐service to various forms of pay‐for‐value.

The Centers for Medicare and Medicaid Services (CMS) has already taken a number of steps in its transition to value‐based payments. To start with, the Medicare Shared Savings Program (MSSP) is rewarding accountable care organizations (ACOs) that create savings and meet quality goals.3 Though most of the 434 ACOs participating in this program today are taking only upside risk in the form of shared savings, many of them will have to accept downside risk as well, starting in 2018, if they choose to renew their MSSP contracts.4 Moreover, CMS has launched a Next Generation ACO program with 21 ACOs that have agreed to take financial risk in return for higher rewards.5 CMS also has placed a small portion of hospitals' Medicare revenue at risk for achieving cost and quality goals, and it began applying a similar pay‐for‐performance program to physicians in 2015.6,7

By the end of 2018, half of Medicare payments are expected to go to alternative payment models (APMs) such as ACOs, patient‐centered medical homes (PCMHs), and bundled payments.8 Further, the new law that replaces the sustainable growth rate (SGR) formula with a different Medicare payment approach gives physicians involved in APMs a 5 percent annual bonus from 2019 to 2024.9

Private payers are moving in tandem with CMS. In March 2014, Anthem BlueCross BlueShield, one of the nation's largest health insurers, said that it had tied a third of its commercial reimbursements to pay‐for‐value quality programs.10 UnitedHealth Group said it was expanding its incentive programs, with a goal of offering at least half of its network physicians the ability to earn bonuses for value, quality, and efficiency within a few years.11 Aetna is paying incentives to practices that have achieved PCMH recognition and is working with scores of provider groups and health systems to create ACOs.12

About half of the 700‐plus ACOs have contracts with private payers. Most of these contracts are based on shared savings rather than on capitation, which is a set monthly fee for each member of a patient population. But 45 percent of private‐payer agreements include downside risk, meaning that providers can lose money if their healthcare spending exceeds their budget.13

What all of this means is that healthcare providers can no longer avoid the reality that their current business models are obsolete. As they transition to new care‐delivery methods, they must stop basing business decisions on how their clinicians and facilities can produce additional, and ever more costly, billable services. Those services and facilities have been profit centers until now; but in the new world of value‐based reimbursement and financial risk, they are becoming cost centers.

The fulcrum of profitability in this new world is maintaining or improving patients' health and delivering good outcomes. The only proven way to achieve these goals is to manage population health effectively and efficiently. To do that, healthcare organizations need advanced health IT, including analytics and automation tools that enable them to transform their mindset, culture, and work processes.

Changing the Mindset

Except for group‐model health maintenance organizations (HMOs) such as Kaiser Permanente and Group Health Cooperative, certain large groups and independent practice associations (IPAs) in California, and a few healthcare systems in other states, healthcare providers are not well positioned for population health management (PHM). While many healthcare organizations are creating new structures to prepare for value‐based reimbursement, health care is still oriented to fee‐for‐service. Physician practices still organize care around office visits, and hospitals focus on acute care within their four walls.

One recent study found that physician practices of all sizes increased their use of evidence‐based care management processes from 2006 to 2013. But, by the end of that period, even large groups used fewer than half of the recommended processes for chronic disease management, on average.14

The concept of caring for entire patient populations on a continuous basis, whether or not individual patients seek care, is only gradually seeping into the consciousness of healthcare managers and providers. And it is still difficult for many provider organizations to accept the idea that filling beds and appointment slots is less important than ensuring that all patients receive recommended preventive and chronic condition care.

To transform themselves, above all, organizations must have a leadership team that understands and embraces the implications of changing from a volume‐based culture to a value‐based one and the tenacity to stay the course. Health systems acknowledge the road to value is not smooth, but many report it is rewarding, even joyful for clinicians and staff at all levels.15

In terms of the work to be done, organizations must reduce two kinds of waste: first, the avoidable tests, procedures, and hospital admissions and readmissions that lead to high costs for employers and consumers; and second, the internal waste that inflates the cost of care delivery. The reorganization of care processes can address both kinds of waste simultaneously by improving the quality and efficiency of care.

Organizations that go down this path need to adopt consistent policies and procedures, starting with a common set of clinical protocols. They must form care teams that can coordinate care for every patient, tailoring their approach to the individual's health risks and conditions; restructure workflows so that each member of the care team is working up to the limit of his or her training and skill sets; and use their care managers as efficiently as possible in order to provide appropriate support to all patients who need help.

Electronic health records (EHRs) are essential to any PHM strategy. But EHRs are not designed to support PHM. Though they can supply much of the data required to track and monitor patients' health and identify care gaps, they must be combined with claims data to provide a broad view of population health and to track individual patients across care settings. Moreover, providers need electronic registries to identify care gaps and provide the near‐real‐time data required to intervene with subgroups of patients efficiently and in a timely manner. Although some EHRs include such registries, they're not as complete, flexible, or usable as those available from third‐party developers.

The IT infrastructure for PHM must also include applications that automate the routine, repetitive work of care management. These automation tools offer several advantages: First, they can lower the cost of care management by taking over time‐consuming chart research and outreach work. Second, they free up care managers to devote personal attention to high‐risk patients who urgently need their help. Third, they allow providers to do essential pre‐visit planning and post‐visit follow up on a consistent basis. Fourth, they can bring noncompliant patients back in touch with their personal physicians. And fifth, these tools enable organizations to quickly scale up their care management efforts so that they can continuously care for all patients in their population.

Most important, the combination of these tools offers a mechanism for engaging patients in their own health care. Without patient engagement, population health management is impossible.

Current Trends

The rise of accountable care organizations in recent years reflects the concurrent emergence of value‐based reimbursement and financial‐risk contracts. Composed of physicians and hospitals that are committed to lowering costs and improving quality, ACOs must be able to deliver high‐quality care within a budget. Strategies such as admitting patients to lower‐cost hospitals and de‐emphasizing expensive tests can help them do this in the short term; but in the long term, ACOs will have to manage population health well to be successful.

The patient‐centered medical home — a holistic approach to primary care that includes a whole‐person orientation and integrated care coordination — is considered an essential building block of ACOs. The National Committee for Quality Assurance (NCQA) has awarded medical home recognition to more than 10,000 practices, composed of over 48,000 providers, and the number of PCMHs is growing rapidly.16

The growth of patient‐centered medical homes bodes well for the transformation of health care through ACOs and other APMs. But to coordinate care effectively across care settings, the primary care physicians who have built medical homes must gain the cooperation of specialists, hospitals, and other healthcare players in the medical neighborhood.

This might seem like a no‐brainer at a time when healthcare organizations are trying to prepare for value‐based payments. But during this transitional period, when most specialists and hospitals still depend to a large extent on volume‐based reimbursement, it is not easy for primary care doctors to persuade them that their future success depends on working with medical homes to coordinate care and reduce costs. Physicians employed by healthcare systems will follow organizational directives to some extent, but at least half of physicians are still in independent practices.17

Some healthcare organizations, including hospital systems and independent practice associations (IPAs), have formed clinically integrated networks (CINs) that facilitate the collaboration of providers across care settings and business boundaries under value‐based contract mechanisms. These networks, which depend on health IT for communications and data sharing, can connect providers who otherwise might not