The Big Unlock: Harnessing Data and Growing Digital Health Businesses in a Value-Based Care Era

By Paddy Padmanabhan and Edward W. Marx

Along with a shift towards value-based care, a digital transformation is under way in health care. However, health care enterprises are having a hard time keeping up with advances in information technology.

Organizations that could once spend months or years developing a strategy to deliver solutions now must implement changes on a near real-time basis. Complicating matters is the emergence of new data sources, new technology architectures and models, and new methods to analyze an avalanche of data.

This book provides a framework for understanding the competitive landscape for digital health and advanced analytics solutions that are harnessing data to unlock insights. It reveals a set of key principles, or universal themes, for success in the digital health marketplace.

Whether youre a health care information technology specialist, a digital health startup or technology firm with a strategic focus on health care, a venture capitalist, or just interested in the industry structure and the emerging technology landscape in health care, youll learn how to grow revenue and profits while creating a sustainable competitive advantage.

Take a key step in navigating the exciting transformation of health care, and harness the power of data and analytics with The Big Unlock.

• Language: English
• Publisher: Archway Publishing
• Release date: Nov 17, 2017
• ISBN: 9781480854598

Paddy Padmanabhan

Paddy Padmanabhan earned a BS in chemical engineering from the Indian Institute of Technology and an MBA in marketing and finance from the Indian Institute of Management. He is a graduate of the CMI executive program of the University of Chicagos Booth School of Business. He has worked in health care information technology for almost two decades, serving in leadership roles at global tech firms Wipro and Accenture, as well as with two silicon valley startups that saw successful exits. He is the founder and CEO of Damo Consulting, a health care growth strategy firm based in Chicago. Take a key step in navigating the exciting transformation of health care, and harness the power of data and analytics with The Big Unlock.

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Copyright © 2017 Paddy Padmanabhan.

All rights reserved. No part of this book may be used or reproduced by any means, graphic, electronic, or mechanical, including photocopying, recording, taping or by any information storage retrieval system without the written permission of the author except in the case of brief quotations embodied in critical articles and reviews.

This book is a work of non-fiction. Unless otherwise noted, the author and the publisher make no explicit guarantees as to the accuracy of the information contained in this book and in some cases, names of people and places have been altered to protect their privacy.

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ISBN: 978-1-4808-5458-1 (sc)

ISBN: 978-1-4808-5460-4 (hc)

ISBN: 978-1-4808-5459-8 (e)

Library of Congress Control Number: 2017916631

Archway Publishing rev. date: 11/9/2017

Contents

Foreword

Introduction

1   Healthcare Data and the Forces Driving the Big Unlock

1.1   Payment Reform and VBC

1.2   Population Health Management

1.3   The Rise of Healthcare Consumerism

1.4   The Internet of Healthcare (and Other) Things

2   New Data and the Analytical Approaches to Unlocking Insights

2.1   Risk Management with NLP: UPMC Health Plan

2.2   Managing At-risk Populations for Behavioral Health: South Florida Behavioral Health Network (SFBHN)

2.3   Unlocking Data with Unusual Partnerships: Quest Diagnostics

2.4   Future-proofing the Technology Backbone of Patient-generated Health Data: Sutter Health

2.5   Online Reputation Management with Social Media Data: Providence Health

2.6   Targeting Consumers with Demographic Data: Lehigh Valley Health Network

2.7   Social Determinants of Health: Central New York Care Collaborative

3   The Key Emerging Technologies that Will Unlock Data

3.1   Cloud Computing: Setting Data Free from Enterprise IT

3.2   Cognitive Computing and AI: Seeking the Threshold for Accelerated Adoption

3.3   Blockchain: Changing the Physics of Data Sharing

4   …And the Forces that Will Restrain It

4.1   Market Maturity: The Teacher is Ready. What About the Student?

4.2   Defending the Citadel: IT Security, Data Privacy, and the Ransomware Threat

4.3   Interoperability: Integrate, Do Not Just Interface

4.4   The Last Mile: Making Analytics Real-time, Invisible, Low Threshold

4.5   Unproven Data Models and Other Challenges

5   The Healthcare Technology Vendor Landscape: Hypercompetition, Disruption, Innovation

5.1   The Custodians: We Have the Data and the Workflow

5.2   The Enablers: We Built it; You Can Rent it

5.3   The Arbitrageurs: We Will Do it For You (and For Less)

5.4   The Innovators: We Have a Whole New Way of Doing it

6   Strategic Positioning, Market Entry, and Expansion

6.1   Understanding the Structure of the US Healthcare Industry

6.2   Competitive Strategy and Revenue Models: Following the Money

6.3   Thought Leadership: The Emerging Model for Engaging with Clients and Prospects

6.4   The Digital Health Funding Environment

7   Universal Themes and General Principles

8   Growth Strategy Frameworks

9   Concluding Thoughts: Working in Healthcare B2B Technology

Acknowledgments

References

Foreword

One of the landmark achievements of healthcare IT over the past decade has been the near total penetration of electronic health record (EHR) systems in the healthcare economy. While the early impetus was primarily to take advantage of meaningful-use incentives, we are now seeing a transformation of healthcare that requires a much deeper understanding of the role of EHRs.

For one, the data residing in EHR systems must be tapped into fully. The vast amount of unstructured data in EHR systems is a data goldmine waiting to be tapped. In the past few years, we have seen the emergence of a multitude of data sources including the Internet of Things (IoT) data, such as wearables, genomic data, and social determinant data. Increasingly, the data is coming at a high velocity; for example, streaming data from smart medical devices that require real-time analysis for timely interventions in managing chronic conditions such as diabetes.

As healthcare moves towards a value-based care era, the role of data in population health management, patient engagement, and revenue-cycle management will be more important than before. Along with new data sources, we are seeing the emergence of new technology infrastructure models to store and process the avalanche of data and new methods of analyzing the data. The term big data analytics has given way to more sophisticated techniques such as artificial intelligence and cognitive computing.

The speed of change of technology and healthcare is unprecedented. Coupled with the rise of consumerism, many individuals and organizations have become exasperated trying to determine strategy, let alone solutions. It used to be that organizations had the luxury of months to develop a strategy and then execute solutions over the course of three to five years. Today that time period has shrunk to the point where we are leveraging agile processes in strategy development and execution.

While serving as a leader in one of the nation’s largest faith-based systems, we found ourselves working on strategy on a continual basis. The challenge was to develop a business intelligence system that could easily adapt and pivot without knowing all the changes the organizations would experience. We deployed a flexible architecture that could respond to the chaos of healthcare and helped guide the organizations in making sound business and clinical decisions.

At Cleveland Clinic, we are helping lead the revolution in digital medicine, and the ability to assimilate and analyze data in real-time is foundational to our effort. While the shelf life of strategy has shrunk considerably, we must still anticipate the future and, to the extent possible, create it. Central to our strategy is our collaboration with IBM Watson and directing our scientists, technologists, and caregivers to focus on solutions. Consuming data from disparate and heterogeneous sources, we are able to transform healthcare with predictive and prescriptive analysis. We continuously look to build out and strengthen our foundation so we can become resilient and responsive to economic market forces and the continuous adoption of best practices.

Healthcare IT solution providers are working closely with enterprises to help transform the technology and applications infrastructure in order to meet the emerging needs of consumerism, improved health outcomes, and organizational efficiency. There is a thriving ecosystem of digital health startups, fueled by venture capital, that is trying to tap into the opportunity.

However, the path toward value-based care is neither easy nor quick. Technology-led innovation in healthcare faces many obstacles, including funding models, evidence of improved healthcare outcomes, and preparedness for change. Healthcare has not traditionally been a pioneer in technology adoption, but more of a fast follower. The lack of interoperability among systems and growing threats of cyberattacks are among the major challenges that impact the rate of change in healthcare.

The cost of healthcare in the United States is the highest in the world by far, and there is not much evidence that healthcare outcomes are better than in any other country. In fact, studies show it is the opposite. We are at the cusp of an unprecedented opportunity to transform healthcare by unlocking data and using advanced analytics technologies to develop and deploy insights for improving outcomes and reducing costs. This book is timely, in that it not only outlines the drivers of the opportunity for enterprises and technology providers alike, but provides a framework for understanding how to create value with the Big Unlock.

The work is just beginning.

Edward W. Marx

Chief Information Officer

Cleveland Clinic

Introduction

This book is based on my experience of nearly two decades in healthcare, as a technology executive and later as an analytics entrepreneur. I have tried to provide a view into how the unlocking of existing and emerging data sources is creating unprecedented opportunities. The book draws from around sixty opinion pieces I wrote in CIO magazine from January 2015 until early 2017. The primary audience for the book consists of technology business executives looking to identify and expand growth opportunities in digital health. Health system executives seeking to understand emerging technology solutions will also benefit from the insights into how the landscape is changing with the huge inflow of venture-capital (VC) money into digital health startups and innovation programs by leading health systems.

The premise of digital health is the creation of new, engaging platforms that will drive improved healthcare outcomes while lowering costs and enhancing patient experiences. To do this effectively, digital health programs must rely on applications that deliver insights from a variety of data sources, structured and unstructured, and from a variety of clinical and non-clinical sources. The unlocking of these insights also relies on advanced analytical methods, for which stakeholders in the digital health ecosystem have to leverage new approaches and new technologies. The challenges in the journey towards value-based care and advanced analytics include data interoperability, information security and privacy, and most importantly a revenue and business model for new digital health solutions. Done correctly, this will unlock profits for everyone, starting with the healthcare consumers who now bear increased financial responsibility for their healthcare.

The Big Unlock refers to the massive opportunity unfolding in healthcare from the digitization of patient medical records and the emerging tsunami of data from a wide range of medical and non-medical sources, especially unstructured data such as text and speech. Collectively, these data will enable the unlocking of insights for improving the quality of care, reducing costs, and creating new sources of value for healthcare providers, consumers, and technology firms. In this book, I have developed a framework for understanding the competitive landscape of digital health solutions and a set of key principles, which I call universal themes, for success in the digital health marketplace.

The book is meant to be a reference document for digital health startups and their venture capitalists, technology firms with a strategic focus on healthcare, and healthcare IT leaders who are keen to understand the solution provider and emerging technology markets. For each of these stakeholder groups, the book provides insights into increasing revenues and profits, while creating a sustainable competitive advantage from the Big Unlock. Finally, the book is a primer for anyone interested in understanding the exciting transformation of healthcare under way and the important role of data and analytics in this transformation.

The book contains insights from interviews and conversations with dozens of C-level executives whom I have had the privilege of working with over the years. This is a view from the trenches that informs corporate strategy, product strategy, technology strategy, and revenue strategy.

This book focuses on business-to-business (B2B) technology markets in healthcare that address the information technology needs of healthcare enterprises. Healthcare B2B technologies play a key role in the economics and delivery of healthcare—primarily providers (physicians, clinics, hospitals, and health systems) and commercial payers (national and regional health insurance companies).

1 Healthcare Data and the Forces Driving the Big Unlock

If data is the new oil, digital health is the new oil refinery.

After the massive effort to digitize patient medical records under the Affordable Care Act and the Health Information Technology for Economic and Clinical Health (HITECH) Act during the Obama administration, the next stage of evolution for healthcare is to unlock the value of the data. Healthcare data is getting bigger all the time. A typical five-hundred-bed hospital today generates fifty petabytes of data.¹ The pace of growth of data is exploding, and our ability to digitize and analyze it is struggling to catch up. Many enterprises to consider themselves to be data rich but insight poor.

Along with this, the rate of change in the way we are digitizing and analyzing the data in the health space is accelerating. Big data analytics is expected to be a $187 billion market by 2019, according to research firm IDC.² Healthcare is a fast-growing segment that is expected to be a $43 billion market by 2024.³ According to the widely read annual report on Internet trends in May 2017 by Mary Meeker of VC firm Kleiner Perkins, healthcare is at a digital inflection point.⁴ The rapid growth of healthcare data (48 percent annual growth as of 2013) and the accumulation of digital health data from a variety of sources is leading to a generation of new and improved insights for driving healthcare outcomes. New data sources such as wearables and the Internet of Things (IoT) present new opportunities and challenges; research firm Gartner predicts that twenty-one billion IoT devices will be online by 2020.

The growing volume of data and the emerging opportunities for value creation by generating new insights make big data the new oil. What is driving the exploration of the new oil is the healthcare industry’s shift to value-based care (VBC).

The per capita cost of healthcare in the United States in 2015 was around $9,900, the highest in the world by a wide margin, with the sector accounting for a fifth of the gross domestic product (GDP).⁵ The higher costs in the United States are not necessarily producing better outcomes.

The Institute of Healthcare Improvement (IHI), a not-for-profit organization, defines the triple aim of healthcare as improving the patient experience of care, improving the health of populations, and reducing the per capita cost of healthcare.⁶ To achieve this triple aim, the healthcare sector needed to be made accountable. As the largest payer of healthcare services, the federal government decided to use the biggest lever it had—payment reform.

VBC shifts financial risk while increasing accountability in the healthcare system. It challenges health plans, health systems, and pharmaceutical companies to change their mind-sets about their revenue models. The most important aspect of this shift, besides providers getting used to not being paid for volume, is the unlocking of insights from data to improve healthcare outcomes and reduce costs. With an estimated $35 billion in taxpayer money paid out as meaningful-use incentives over the past eight years to digitize health records,⁷ the need of the hour is to unlock insights from the data to drive improved healthcare outcomes. The key competencies required are data aggregation and analysis to drive physician productivity, care management, and patient engagement. Creating the digital and analytical infrastructure required to navigate this transition to VBC is the biggest opportunity in front of the healthcare sector and technology-provider community.

The transition to VBC is neither easy nor assured. It involves significant financial risks in upfront investments, radically new ways of approaching healthcare delivery, and a culture shift that emphasizes the role of data and insights for care decisions. While it is widely acknowledged that healthcare is an area of tremendous opportunity for big data analytics, innovation has been slow due to margin pressures, a risk-averse mind-set, and market-related factors.

A study by Quest Diagnostics (Quest) and analytics company Inovalon, based on a survey of healthcare payers and providers, indicates progress toward VBC but also points to the opportunity for further alignment between health plans and providers to advance VBC.⁸ Despite the industry’s progress toward VBC, the vast majority of payments still flow through the fee-for-service (FFS) system. Within healthcare, adoption levels for VBC models fall on a wide spectrum between large, integrated networks operating on accountable care models and smaller independent and rural health systems holding on to FFS. The Quest report indicates that, while 82 percent of physicians and health-plan executives agreed the transition to VBC will continue regardless of policy changes, only 29 percent of physicians and health-plan executives said they believe healthcare in the United States is value-based. This percentage was a marginal increase from the findings of the previous year.

At the time of writing, healthcare policy in the United States is in a state of tremendous flux and uncertainty. However, behind the scenes, the shift to VBC is quietly taking place, driven by the 2015 Medicare Access and CHIP Reauthorization Act (MACRA), a bipartisan piece of legislation that creates incentives to move away from FFS to value-based reimbursements. Neal Singh, CEO of Caradigm, a GE Healthcare company that provides population health management solutions, says, Just over a year ago, nobody was talking about MACRA, and now, everybody is talking about MACRA because, guess what, whether you like it or not, the healthcare provider’s compensation is going to be heavily influenced by MACRA over time. The levels of risk are going to change over time as well. The Centers for Medicare and Medicaid Services (CMS) is very clear about where they want to lead healthcare. The formats may change, the names may change, the types of payment systems may change, but the fact is that the laws of economics will not change. The laws of economics are fundamentally saying that the current system of basic FFS is not sustainable.⁹

As all these pieces evolve rapidly, the healthcare industry is looking at implementing systems designed to be future-proof in relation to policy changes. A big part of that is putting in systems that will be able to deal with the exploding volume and variety of data and generate insights in real-time for improved healthcare outcomes and reduced costs of care.

We are in the very early stages of the effort to unlock the value of the data. Much of the data remains locked in proprietary third-party vendor technologies (more on that later), and the investment required to unlock insights and the returns required to justify these investments have yet to line up. The biggest challenge by far remains interoperability between various proprietary EHR systems. Efforts to promote data sharing through health-information exchanges (HIE) have also not been as successful as expected, for a variety of reasons.

At the same time, we have new data sources coming online, such as the IoT and genomic testing, to name a couple. These new data sources are emerging as important factors in the Big Unlock.

In early 2017, the New England Journal of Medicine (NEJM) published the results of a survey of healthcare executives who were asked what the most useful sources of data were expected to be in five years.¹⁰ Clinical data, and specifically EHR data, was seen as the most important data source by far, indicating the enormous focus by healthcare enterprises on optimizing their investments in EHR systems over the past several years. However, the expected rise of patient-generated and genomic data provides interesting insights into what is emerging as important data.

Today, we are seeing a convergence of demand- and supply-side forces that are unlocking the potential of advanced analytics. Some of these are

• increasing importance of analytics for enterprise growth and profitability;

• falling prices for data storage and computing capacity;

• acceleration of technology-led innovation; and

• alternate payment models and the transition to population health management.

A nagging question that keeps coming up in boardrooms is what the return on investments is on new technology investments, especially digital health, is. The answers are not clear today. A survey of nearly four hundred CEOs and senior managers across sectors by research firm Gartner indicated they rate the productivity gains from breakthrough technologies to be very low in the next five years.¹¹ It may be too early in the game to fully appreciate the potential benefits of these technologies.

Some of the factors driving the sentiment are

- demonstration of the ability of digital health solutions to improve outcomes and deliver financial returns;

- data security and interoperability challenges;

- operationalization of digital health and analytics solutions in clinical workflows;

- ability to adapt to new data sources such as wearables, IoT, genomic data, and patient-generated health data (PGHD); and

- talent acquisition and retention.

Value creation in analytics today is focused on a couple of areas: data integration and insight generation through the use of predictive models for managing clinical outcomes, especially in the context of population health management (PHM). I call this the zone of activity. However, most health systems lack a plecosystem—an integrated platform ecosystem approach (more on this later) to derive benefits from advanced analytics by incorporating them into the clinical workflow in hospitals.

In recent years, expensive and complex analytical tools and technology have become accessible and affordable to people and businesses. The computational horsepower needed to conduct analysis on vast amounts of data has also dropped significantly in recent years in line with Moore’s law (coined by Intel cofounder Gordon Moore in 1965, the law broadly states that the computing capacity that can be packed into chips has doubled every year since their invention while computing costs have halved).¹² With storage and