Health Highlights

The Promise of Data-Driven Healthcare: Megatrends for 2018

By Valerie Barton, Managing Director, Manatt Health | Laura H. Braslow, Director, Manatt HealthKevin McAvey, Senior Manager, Manatt Health

Editor’s Note: For state health programs, payers, providers and life sciences companies, data and analytics have become essential to facilitating efficient and effective healthcare delivery. The right data assets and analytics expertise are core requirements for ensuring access to care, optimizing population health initiatives, and achieving quality and financial goals.

In a recent webinar, Manatt Health revealed the healthcare megatrends that have transformed using data and analytics from an option to a necessity—and shared what organizations need to know about what’s next to stay ahead of the curve. Highlights from the session are summarized below.


A Little Chaos Makes It Exciting

There is a quote by science fiction writer Amelia Atwater-Rhodes that is the ideal lead-in to any discussion about healthcare data and analytics: “Life is nothing without a little chaos to make it interesting.” By that definition, life is very interesting these days for those who are dealing with healthcare data. Healthcare leaders have to navigate a complex array of databases and technologies to make the right decisions about the optimal tools to invest in for their organizations. They have to make those decisions within often stringent time and budget constraints—and balance them against other priorities. 

The technology sector has seen an opportunity in this struggle to apply its expertise in data aggregation, predictive analytics, data mining and software to healthcare. Technology companies are continuing to move into the healthcare space, bringing new ideas and options—but also critical challenges.

The Three Big Challenges in Data-Driven Healthcare

Healthcare is facing three big challenges around data and analytics:

  1. The purpose of data has changed. In the past, data was important for tasks such as paying claims, seeking Food and Drug Administration (FDA) approval for a new drug or device, and supporting financial and clinical transactions. In the past 10 or 15 years, however, the questions being asked of data sources are very different than the ones those sources were built to answer. We’ve gone from needing data only to answer very siloed questions to needing data that cuts across various segments and facets of healthcare. The challenge is figuring out how to use real-world data to advance us toward high-value, “frictionless” healthcare. 
  2. The development of tools for making data impactful has lagged behind the development of IT infrastructure. In many ways, IT has moved ahead faster than the tools needed to put it to work supporting clinical practice, shared decision making and care management. There are many new entrants creating software and tools to make data assets more usable, valuable and streamlined for end users. But we are not there yet.
  3. There is a lot of technology innovation, but it is difficult to identify the highest-value advances and integrate them into an organization’s workflows. It is important that organizations find ways to discern the best options from the ever-expanding array of tools to support their goal of being high-performing healthcare systems. Questions remain around how decision makers can use the power of big data in ways that are of the greatest value to themselves, their organizations and the healthcare system as a whole. 

It is critical that healthcare leaders overcome these challenges and begin to incorporate data and analytics into their organizational work streams to inform decisions, improve communication among care team members, and help achieve quality and financial objectives. What’s driving the crucial need for data and analytics? There are nine megatrends that are key to realizing the promise of data-driven healthcare.

Trend 1: Stakeholders Search for Meaningful Information in a Data-Abundant World.

Data plays a critical role in the modern healthcare payment and delivery system. With more data than ever available for use, organizations must become more sophisticated data consumers, carefully assessing the usefulness of data to inform their program and policy goals.

A Stanford University report noted that by 2020, we will be generating 2,314 exobytes of healthcare data annually—enough to fill the typical PC about 100 billion times. That data holds the promise of bringing significant improvements to our healthcare system. But the promise can only be realized when the data is relevant to our policy and program objectives, easily accessible and usable, and able to be connected to actionable workflows.

For all of its volume, velocity and variety, most healthcare data is only accessible to a subset of users at a time. It is often unrefined and unstructured—and lacking standard definitions and proven use cases. To help realize the promise of data-driven healthcare, organizations are increasingly developing and implementing strategies that will define their data and analytic needs—and connect the right data sources with the right users at the right time.

As our healthcare system expects more from us—to manage population health, cut costs, increase efficiency and mitigate the risks inherent in value-based purchasing—the need for longer-term data strategies is growing. The role of commercial vendors is also growing to fill that need. We are seeing an increasing number of commercial vendors specializing in enterprise resource planning, performance management, business intelligence and data aggregation. They are expanding their capabilities, methods and reporting tools as the market evolves to ensure they are ready to meet emerging requirements.

Public data agencies are also calibrating their roles in this new landscape. Consider, for example, that the Centers for Medicare & Medicaid Services (CMS) is the steward of some of the most valuable healthcare data sets in the country. As we move forward into a new data-driven world, public entities are uniquely positioned to fill the public’s healthcare needs by allocating resources toward higher-value activities.

Trend 2: New Analytics Have the Capacity to Reveal Healthcare Cost Trends.

Data and analytics are enabling stakeholders to understand their cost drivers and develop strategies to address them. Payers and providers, for example, are using data to monitor spending by subpopulations and service lines, develop more efficient clinical practices, test new payment methodologies, and strengthen their referral patterns and networks. They are also using their enhanced data capacity to control administrative spending, streamline claims processing and conduct artificial intelligence (AI)-powered fraud analyses. One payer recently developed its own internal data pipeline and customized AI algorithms to flag potentially fraudulent claims early, saving millions of dollars annually.

Public agencies, such as CMS, are using data to reduce fraud, promote price transparency, respond to cost concerns and reveal price variations for clinical services. In addition, statewide total cost of care measures are allowing policymakers to understand market cost drivers and develop targeted policy solutions to address them.

Employers also are using data to address healthcare costs and understand the impact of those costs on their bottom lines. Self-insured employers particularly—who cover approximately 60% of the U.S. workforce—are implementing new analytic and technological solutions to monitor their employees’ well-being, encourage healthier lifestyles among their employees and predict those at risk of disease to promote early intervention.

In addition, large companies are using data to bypass traditional insurer networks and directly negotiate and contract with providers. A growing number of major employers are also working with technology companies to develop collaborative solutions that reduce costs.

Finally, consumers are more frequently engaging with new applications to assess their plan options and engage in service shopping. With more than a quarter of consumers now in high deductible health plans and many facing even higher coinsurance liabilities, we anticipate there will be an even greater willingness to engage with pricing tools. 

Trend 3: Consumers Are Generating and Using Health Data, but Clinical Connections Remain Limited.

Consumers, particularly younger generations at home with the Internet of Things (IoT), are increasingly comfortable using devices to monitor their health and well-being. Whether this data will be clinically useful remains an open question.   

According to one study, global wearable shipments exceeded 100 million units for the first time last year. During the same time period, U.S. residents downloaded more than 200 million health applications across a wide range of areas, from treatment and prescription compliance to fitness.

Providers are trying to use technology to increase patient engagement by opening up personal health records for patient access. According to a recent study, in 2015, just under 70% of the nation’s hospitals offered the ability for patients to view, download and transmit their personal health data, while 63% allowed patients to securely message their providers. 

Similarly, payers have tried to create transparency tools to steer patients toward value. Patient engagement, however, remains low. A Health Affairs study of 3,000 non-elderly adults shows that only 13% of those who had out-of-pocket spending sought out cost information, and only 3% compared costs across providers. 

While there are many new tools built around consumer-generated data, they are not well connected to clinical practice yet. Successes have been limited to localized cases involving targeted health coaching around specific disease states, such as diabetes. As the market evolves, however, health systems, vendors and consumers all will be looking for applications that bring clear value, drive behavioral change and create more seamless care delivery. 

Trend 4: Population Health Is an Intriguing Paradigm, but Data Development Is Slow.

Population health focuses on health outcomes, cost and quality for groups of individuals. In general, population health programs have yet to show a broad-based return on investment. 

Some delivery systems, in the context of their value-based payment arrangements, are reaching beyond their four walls to manage the populations they treat. In the case of low-income populations, that may include addressing social factors that affect healthcare outcomes.

Data, methods and infrastructure development to support population health have lagged for a range of reasons, including technical complexity and privacy issues. Addressing these deficits is critical for increasing the value of population health programs moving forward. 

Even when delivery systems are committed to making changes to clinical practice to support population health, they face significant challenges. A key hurdle is that funding for infrastructure and data is often inadequate. In addition, while data science can provide the capability to micro-target specific patient subpopulations and identify gaps in care, standardization of that data, as well as interoperability across providers and, where needed, social service agencies, isn’t well developed. 

Technology companies recognize that there are complex delivery system data needs. Traditional healthcare information exchange and electronic health record (EHR) vendors are working to modify their tools to standardize new fields and enable data integration. Cloud service providers are promoting environments for collecting, sharing, analyzing and reporting data for population health models that require collaboration between healthcare stakeholders and social service agencies.

Both traditional vendors and cloud service providers are working to bring in more data sources, provide advanced predictive analytics, and support the dissemination of more meaningful information to providers and care managers through dashboards and reporting platforms. All of these factors are foundational for building effective population health initiatives.

Trend 5: Sharing Data Is Not Widely Accepted as Good Policy or Business.

Healthcare data has existed in silos for a long time. Changes in policy and care delivery, however, are now requiring stakeholders to share data about patients so treatment can be managed across the care continuum.

Sharing data between and among different entities is extremely complex. Data sharing carries business risk, and efforts to pool data are hindered by legal and regulatory frameworks. 

For both providers and plans, data is an extremely important competitive asset. Market incentives still exist for keeping patient panels, demographic information, and utilization and cost data in-house. But a push from Medicare, as well as state reforms that are happening in Medicaid, are providing both incentives and penalties to encourage data holders to share information. To be willing to share their data, providers and plans need to know that what they gain is more valuable than what they might lose in terms of perceived competitive advantage. 

Even when stakeholders are willing to share data, there’s a patchwork of federal and state laws that can present challenges. For example, the federal substance abuse confidentiality regulations almost always require patient consent for data to be shared—and the consent form requirement sometimes means that a single patient has to provide consent on multiple occasions. 

State laws related to mental health, HIV and other types of sensitive health information vary. They also can often prohibit data sharing without patient consent or limit the circumstances under which data can be shared. 

Trend 6: Analytic Methods Are Proliferating. AI Is Emerging as the New Frontier. 

The rapid progression of methods and predictive analytics in the healthcare industry has generated new and exciting tools, as well as new ways of using and thinking about healthcare data. In the near future, the market will begin to focus on high-value use cases around the types of analytics that organizations are incorporating into their performance management and clinical activities.

AI will play a big role. There is promising early evidence around the potential impact that AI may have on clinical practice, performance management and delivery systems. There also, however, are significant challenges to broad-based implementation, including data quality issues and technical infrastructure needs. In the future, however, we believe AI applications will be developed that allow more organizations to apply and acquire AI capabilities. AI just may not be the immediate-term disruptor that it has been framed as in other discussions. 

There is no “one size fits all” answer in terms of the right analytics for an organization. Local data strategies are required for healthcare industry stakeholders to integrate data effectively and make the optimal analytic investments. Most critically, organizations must focus on strategies that link their investments to clearly defined outcomes and/or mission goals.

Trend 7: Data and Analytics Enable Clinical Transformation on the Front Lines of Both Care Delivery and Research.

Many delivery systems are seeking to identify opportunities to leverage investments in health information technology (HIT) and private and public health information exchange capabilities. They are recognizing the chance to improve information sharing among providers and other players, as well as to integrate with clinical and care team workflows. New technologies also offer the opportunity to share information between providers and payers to support more effective population health management.   

One of the most exciting areas of growth is the integration of data and predictive analytics from new platforms with existing clinical protocols to drive increasingly sophisticated clinical decision support. Historically, there have been challenges around the proliferation of data that isn’t as well-targeted or integrated as it could be, making it difficult for providers to engage and take action. To overcome this hurdle, clinical decision support systems are focusing on dashboard reporting and message-based tools that provide actionable information while reducing provider and administrative burden.

Finally, we can’t discuss clinical transformation without speaking about precision medicine. Like AI, precision medicine is a newly emerging area. Unlike AI, however, it already has generated a significant number of real-world cases to prove its value. Life sciences companies, providers, and clinical researchers are increasingly leveraging new genomic, biomarker, and molecular data to drive more accurate diagnoses and more targeted treatments.

Trend 8: Providers and Payers Are Increasingly Using and Sharing Data to Manage Performance and Demonstrate Value.

Payment and delivery transformation is not just about cost management. It encompasses the larger concepts of value-based payment and alternative payment models, as well as of targeting resources within the healthcare system to improve outcomes, quality and value. There is a tremendous amount of innovation and interest around value-based transformation across both the public and private healthcare sectors:

  • Providers: Many leading health systems are building data and analytic capabilities to monitor and manage performance, reduce adverse events and readmissions, and improve quality. The trajectory of value-based performance remains unclear, however, which could be a hurdle to broad adoption of data-driven performance management.
  • Public sector: CMS has implemented a range of alternative payment models and has been a driver behind both sharing and using data to help providers focus on achieving quality and performance management goals. Some states, particularly those pursuing Medicaid innovation and other waivers, are required to measure and report performance data to demonstrate delivery system performance improvements.
  • Private payers: Private payers are continuing to innovate using claims and other data to target high-risk patients, as well as to engage care managers and in-network providers in performance management initiatives.    
  • Life sciences companies: Some life sciences companies are beginning to explore value-based contracting with payers. This is a very new approach but demonstrates that value-based thinking is extending into the life sciences sector. 

Trend 9: Key Data Gaps and Limitations Inhibit Payment and Delivery System Strategic Planning.

Data gaps are more of a mega challenge than a megatrend. Many organizations struggle with significant data gaps in a host of areas, including the universe of providers and the relationships with systems, clinicians and service locations, as well as around payers and enrollment. 

One of the most critical issues is the lack of clear, shared data sources that define the relationships within delivery systems. The delivery system has been changing rapidly in recent years—and that will continue as disruptive delivery models and payment relationships proliferate. Traditional data sources that were used in a volume-focused context don’t help us understand our new value-based environment. Shared data sources don’t currently exist. All stakeholders in the market would benefit if there were shared capabilities to manage and link provider, payer and patient information while at the same time reducing administrative burden. 

The public sector is most likely to develop a shared “source of truth.” State agencies have the ability to develop, leverage, and support shared capabilities and systems that can serve as a common data source across payers and providers. Some private-sector organizations and data vendors have sought to enter this space in limited ways, but they are unlikely to meet the need for a truly shared source—though there is the possibility for a public-private collaboration to create an effective solution.   


In developing these nine critical megatrends around data-driven healthcare, an array of key questions arose that don’t yet have answers: Will organizations be able to keep up with a continually shifting technology landscape? What about those left behind? Will a data divide emerge? How much of data’s potential to improve healthcare is real—and how much is hype? How much of our new data analytic capacity will generate long-term change? Can the industry develop well-calibrated solutions that bring real value while minimizing provider burden?

The long-term prospects for data-driven healthcare will be determined largely by whether key stakeholders can demonstrate value from the data-to-workflow connections they establish. At Manatt, we will continue to monitor the rapidly changing data landscape in healthcare—and help all of the players overcome current challenges to integrate effective data solutions into their organizations. If you have questions around healthcare data and analytics that you’d like to explore, please reach out to Valerie Barton at

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The Opioid Epidemic: The Emergence of a Multi-Layered Approach

By Richard S. Hartunian, Partner, Corporate Investigations and White Collar DefenseJacqueline C. Wolff, Partner, Co-chair, Corporate Investigations and White Collar Defense and Co-chair, False Claims Act Practice | Andrew Case, Associate, Litigation

Editor’s Note: On October 26, 2017, Eric D. Hagan, Acting Secretary of the Department of Health and Human Services, announced that “a public health emergency exists nationwide” as a result of the opioid epidemic. In a recent article in the February issue of Business Crimes Bulletin, summarized below, Manatt examines the multi-layered approach emerging to fight the opioid epidemic, including the civil suits filed as cities, counties and tribes go on the offensive; how state attorneys general are responding; Department of Justice (DOJ) enforcement efforts; and executive and congressional actions.


According to the Centers for Disease Control and Prevention (CDC), from 1999 to 2016, “spending on Medicaid-covered prescriptions used to treat opioid addiction and overdoses increased from $364 million to $920 million, an average annual increase of 19[%] … with a 30[%] increase between 2015 and 2016.” As a result, cities, counties, states and the federal government have mounted an attack.

Cities, Counties and Tribes on the Offensive

Starting with Chicago in 2014, more than 100 cities and counties have filed civil suits against pharmaceutical manufacturers, distributors and retail pharmacies, seeking damages for costs they allegedly spent or will spend to fight the opioid epidemic. On December 5, 2017, the Judicial Panel on Multidistrict Litigation (MDL) consolidated and transferred 64 of these cases, which will now be heard by a single judge in the Northern District of Ohio, and noted there are more than 50 potential “tag-along” actions.

In addition, some municipalities, such as Seattle, have filed individual suits in local state courts and suggested they will resist joining the combined litigation. In addition, the Cherokee Nation has filed an action in tribal court and shows no sign of joining the MDL.

The cases assert varying theories of liability, and a number of different defenses have been raised in response. They all share, however, common questions of fact, including whether:

  • Opioid manufacturers overstated the benefits and downplayed the risks of using their opioids, and aggressively marketed these drugs to physicians; and/or
  • Distributors failed to monitor, detect, investigate and report suspicious orders of prescription opiates.

State Attorneys General Respond

On September 19, 2017, a coalition of 41 state attorneys general issued subpoenas to five pharmaceutical manufacturers and three distributors. Other state attorneys general, including those in Ohio, Washington, Louisiana, New Mexico, Missouri, Oklahoma and Mississippi, have already filed lawsuits against certain manufacturers and distributors.

Cases that have been brought by state attorneys general, like those brought by municipal and county plaintiffs, allege a variety of claims, including violations of state consumer protection laws, together with claims of nuisance, negligence and fraud. State attorneys general, however, also have commended companies, such as CVS, that have taken proactive steps to address opioid abuse.

The DOJ Flexes Its Enforcement Muscles

Over the past five years, the DOJ has prosecuted hundreds of doctors for knowingly distributing prescription opioids improperly. It also has settled civil claims with retail pharmacies allegedly violating the record-keeping provisions of the Controlled Substance Act (CSA) for amounts ranging from $3 million to $80 million. In addition, it has announced major settlements with distributors (e.g., McKesson for $150 million) and manufacturers (e.g., Mallinkrodt for $35 million) for allegedly failing to report suspicious orders in violation of the CSA.

It is likely that enforcement efforts will continue to expand. In November 2017, the Drug Enforcement Administration announced that it is working with 44 states to address opioid diversion and will use “all available means—administrative, civil and criminal—to ensure that its 1.7 million registrants handling prescription drugs comply with the law.” As federal enforcement activity increases, registrants may want to consider actions that can positively impact the determination of charges and penalties, including enhancing compliance and investigation functions, being prepared to implement remediation efforts, and ensuring timely and voluntary disclosure of any wrongdoing.          

Executive and Congressional Actions

Congress has engaged in efforts to fight the opioid epidemic through proposed legislation and its investigative powers. On June 27, 2017, a bipartisan task force in the House of Representatives issued a legislative agenda to “address the opioid epidemic from the perspectives of law enforcement, prevention, treatment and recovery.” In July, the Senate’s Homeland Security and Governmental Affairs Committee requested documents from four manufacturers and three distributors. Allegations in the media that prior enforcement efforts have been lax suggest that future actions may increase.  


In the current environment, any company involved in the opioid supply chain could face risks from lawsuits or government enforcement actions. Companies can minimize those risks—and do their part to address the crisis—by thoroughly reviewing and, when appropriate, strengthening their compliance policies and procedures.  

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New Webinar: America’s Multidimensional Opioid Crisis

As the crisis of addiction accelerates, experts project that opioids could kill nearly half a million Americans over the next decade. Already, close to 100 people a day die from opioids.1

How did the crisis begin? Where are we now? And what can we do going forward? In a new webinar for Bloomberg BNA, Manatt reveals the answers, examining the opioid crisis from the diverse viewpoints of its affected stakeholders, including victims and their families, first responders and law enforcement agencies, pharmaceutical manufacturers, states and cities, and public and private payers. Topics covered include:

  • The genesis and drivers of the opioid crisis from multiple vantage points
  • Short- and long-term strategies that cities, states and the federal government are using to address the crisis through litigation, enforcement and regulation
  • The actions both the public and private sectors are taking to combat the crisis
  • Opioid-related civil and criminal cases brought by cities and counties, state attorneys general, and the Department of Justice
  • The ways False Claims Act theories used in other pharma cases may be applied in opioid cases moving forward
  • The innovative solutions emerging across the full range of stakeholders, including pharmaceutical companies, government payer programs and private insurers
  • The next steps for cities and states in terms of policies, education, community engagement, treatment options and more
  • A look ahead at what the future holds for law enforcement, from the increasing use of data analytics to new theories of liability
  • Next steps to change laws, regulations and treatment protocols to ameliorate the crisis

1STAT Forecast, June 27, 2017


Joel Ario, Managing Director, Manatt Health
Jocelyn Guyer, Managing Director, Manatt Health
Richard Hartunian, Partner, Corporate Investigations and White Collar Defense
Jacqueline Wolff, Partner, Co-chair, Corporate Investigations and White Collar Defense and Co-chair, False Claims Act Practice
Sandy W. Robinson, Managing Director, Manatt Health

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CMS Introduces New Incentives for Remote Patient Monitoring

By Edith Coakley Stowe, Senior Manager, Manatt Health | Jared Augenstein, Senior Manager, Manatt Health

As the Internet of Things (IoT), rising healthcare costs and value-based payment reform converge, it’s clearer now, more than ever, that healthcare organizations need innovative approaches to provide higher-quality yet more cost-effective care.

To stay ahead of the innovation curve and respond to the “consumerization of care” that patients are expecting, many organizations are turning to virtual care models, such as telehealth and remote patient monitoring (RPM), to change where and how healthcare is delivered, provide further access to care, improve outcomes and reduce costs using patient-generated health data (PGHD).

Telehealth and RPM reimbursements accounted for just 0.003% of the Centers for Medicare & Medicaid Services’ (CMS’s) $990 billion budget in 2016. However, after announcing the Physician Fee Schedule for 2018, CMS—the largest payer in the United States—is starting to get on board with digital health technology adoption.

Beginning January 1, 2018, CMS is actively incentivizing the use of RPM in two major ways:

  • CMS unbundled CPT code 99091, meaning fee-for-service clinicians can be reimbursed $58 a month per Medicare patient if they spend a cumulative 30 minutes reviewing data collected via RPM.
  • CMS approved a new Improvement Activity to reward clinicians participating in the Merit-Based Incentive Payment System (MIPS) for using RPM technology to engage patients, called “Engage patients and families to guide improvement in the system of care.”

MIPS 101

MIPS aims to tie payment updates to value by introducing a scoring system that incorporates care quality, total cost of care, “Improvement Activities” and meaningful use of certified electronic health record technology (CEHRT).

Each clinician (or group of clinicians) earns a final MIPS score for the performance year, resulting in a positive or negative update on Medicare Part B professional services rates. The updated rate will apply for a full calendar year, two years following the performance year. The first MIPS performance year was 2017, and healthcare organizations are reporting to CMS in the first three months of 2018, which will drive the first MIPS payment updates in 2019.

Patient-Generated Health Data, Improved

The Improvement Activities category within MIPS is worth 15% of the final score in each of the first two years of the program, and is meant to reward activities that drive clinical practice improvement for all patients seen. To earn points, clinicians choose from 93 activities, including care coordination, patient engagement, safety and more. Bonus points are available for using CEHRT.

While some of the CMS Innovation Center’s test models, such as the Comprehensive Primary Care initiative, have experimented with promoting PGHD over the past few years, clinicians could not gain “credit” in the mainstream Medicare program for the collection and use of PGHD until now. 

After a swath of positive evidence that PGHD utilization improved outcomes, CMS convened a workgroup with industry representatives and crafted a new Improvement Activity called “Engage patients and families to guide improvement in the system of care.” This new activity will enable clinicians using digital tools to collect PGHD to receive 25% of their Improvement Activities points. Clinicians attesting to this improvement activity using CEHRT can also qualify for the available 10% bonus score in the Advancing Care Information (ACI) performance category for the 2018 reporting year.

To be eligible for MIPS credit under this new Improvement Activity, a clinician must use digital health tool(s) that:

  • Engage patients and families to deliver ongoing guidance and assessments outside the encounter.
  • Collect and use PGHD in an “active feedback loop” with the patient (e.g., provide PGHD in real or near-real time to care team members in a way that they pay attention to it, incorporate it into the medical record and/or generate clinically endorsed automated feedback to the patient).
  • Are “clinically endorsed” (e.g., can inform the patient or care team in a timely manner about a patient’s “clinical status, adherence, comprehension or other indicators of clinical concern”).

Clinicians also must be able to attest that they have completed this approach for at least 90 days within the reporting year.

This Improvement Activity will carry a “Medium” weight for reporting year 2017 and a “High” weight for reporting year 2018, according to the CMS Helpdesk.

Eligible Digital Health Tools

While many digital health solutions have the potential to meet the aforementioned criteria, the best eligible tools will transmit both clinically valid and contextual data back to care teams. RPM, use of patient engagement platforms, and use of cellular or web-enabled bidirectional systems are all activities that could potentially fall within the bounds of the Improvement Activity.

A few solutions that clinicians could use to meet CMS’s criteria include:

  •  Noteworth, an RPM platform to prescribe and deliver virtual care to patients at home, and
  •  Wellpepper, which develops clinically validated mobile care plans that incorporate PGHD.

Additional Guidance Needed

CMS has not yet released any additional clinician-facing guidance for this new Improvement Activity, which begs implementation questions as clinicians become more aware of and interested in attesting to it. For example, “clinically endorsed,” “active feedback loop” and “near-real time” are only loosely defined, which they have in common with many terms used across the Improvement Activities category.

Despite these gray areas, we believe that the clear intent of this new activity is to encourage a broad variety of RPM activities, so long as they are “clinical” in the sense that they directly connect to the patient’s care team and plan of care. For example, exchange of glucometer and blood pressure readings would clearly fall within the intent of “clinical,” whereas fitness tracking data—although potentially helpful—would not. In the short term, we expect CMS to take a relatively light touch when monitoring compliance under this category, as long as clinicians can reasonably back up their attestations if audited.

Barriers to Adoption

Now that CMS has worked to remove one of the major barriers to digital health technology adoption by rolling out new financial incentives, healthcare organizations should be further motivated to actively implement patient engagement and RPM tools. Healthcare organizations in the process of selecting tools to implement face the uphill job of not only discovering and vetting the functionality of those solutions, but also choosing those that fit their business goals, reimbursement structures and clinical workflows.

A few critical things healthcare administrators should keep in mind when considering a digital health solution include:

  • Funding for digital health technologies: Does the organization have a flexible budget cycle? Are there funds dedicated to exploring digital health innovations?
  • Clinical staff buy-in: Does this new tool fit into clinicians’ existing workflow? Will the addition of a new tool be disruptive to their day-to-day operations, or will it alleviate administrative burden? Who will handle any necessary education, awareness and training?
  • Patient readiness: Are patients interested in using digital health tools and remote monitoring to share PGHD? Are there specific service lines or patient populations within the organization that would be a particularly good fit?
  • Security and interoperability: Does the digital health tool being considered integrate with the organization’s core financial and clinical management systems, or will it be another silo of data? Does it meet the organization’s security and interoperability goals and standards? Are there sufficient IT resources necessary to support the integration of a new tool?
  • Defining success: Can executives and stakeholders come to a consensus on the clinical and business goals for the new technology? What are the agreed-upon expectations, milestones, objectives and success indicators? How will the tool be evaluated?
  • Billing and documentation: Does the tool integrate with the organization’s internal infrastructure to track and aggregate quality measures toward its target reimbursements, such as the Quality Payment Program (QPP)/MIPS?

One Small Step for Value-Based Care, One Giant Leap for RPM

With the shift toward value-based reimbursement already underway, this latest change signals CMS’s recognition of RPM technology as a fundamental component of high-quality care delivery systems that achieve the Triple Aim: healthier patients, an enhanced patient experience and reduced costs of care.

The update to MIPS demonstrates a significant advancement not only toward making digital health technology an integral part of a patient’s care experience, but also incentivizing clinicians to leverage cutting-edge tools more effectively to improve care quality and outcomes. We see the introduction of the Improvement Activity as a small but concrete step forward in improving the policy environment (and therefore the adoption rate) for RPM.

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FTC Alleges Dental Supply Companies Conspired to Avoid Discounts

By Lisl J. Dunlop, Partner, Antitrust and CompetitionShoshana S. Speiser, Associate, Litigation


The federal antitrust agencies are continuing to focus on anticompetitive practices by healthcare companies, most recently in the dental industry. Last month, the Federal Trade Commission (FTC) sued three dental supply companies for allegedly conspiring to avoid discounts for buying groups. While buying groups are technically combinations of competitors, they serve a procompetitive function and are permissible under the antitrust laws. Coordinated efforts to counteract the leverage of buying groups—particularly in the healthcare field—will be scrutinized under the antitrust laws.

The FTC’s Complaint

On February 12, 2018, the FTC filed an administrative complaint against three distributors of dental products—Benco Dental Supply Company, Henry Schein, Inc., and Patterson Companies, Inc.—alleging that they violated the antitrust laws by conspiring to refuse to provide discounts to group purchasing organizations (GPOs) representing individual dentists and small businesses. The three distributors, who offer a broad range of supplies, including gloves, cements, sterilization products, dental chairs and more, are the only three national dental supply companies and collectively control more than 85% of the $10 billion market.

Buying groups offer solo practitioners and small groups the opportunity to obtain volume discounts without having to join a larger practice. Despite the fact that buying groups represent groups of competitors, the FTC and the Department of Justice’s (DOJ) Antitrust Division maintain that they are generally not anticompetitive, because they generate efficiencies and consumer benefits. The FTC and DOJ Statements of Antitrust Enforcement Policy in Health Care provide a safety zone for buying groups if (1) the purchases account for less than 35% of the total sales of the purchased product and (2) the cost of the products accounts for less than 20% of the total revenues from all products or services sold by each participant in the buying group. Even buying groups that fall outside the safety zone do not necessarily raise antitrust concerns where their activities are carried out under antitrust safeguards.

According to the complaint, Benco had consistently maintained a policy of refusing to provide discounts to buying groups, whereas Schein had worked with some GPOs. Following communications between executives at the two firms around July 2012, however, Schein began refusing to provide discounts or compete for GPO business. The FTC further alleged that Patterson, which historically had sold to GPOs, joined the agreement around February 2013, quoting an email exchange between Benco and Patterson executives.

Documents concerning communications between the distributors’ executives uncovered during the FTC’s investigation play a leading role in the complaint. For example, in February 2013, a Benco executive wrote to Patterson, saying, “FYI: Our policy at Benco is that we do not recognize, work with, or offer discounts to buying groups (though we do work with corporate accounts) and our team understands that policy.” In response, the Patterson executive allegedly wrote: “Thanks for the heads up. I’ll investigate the situation. We feel the same way about these.” The complaint details several additional communications between the distributors’ executives that the FTC describes as attempts to monitor and ensure compliance with the illegal agreement. 

Benco was also separately charged for inviting Burkhart Dental Supply, a regional distributor and the fourth-largest full-service distributor in the United States, to join the agreement. Burkhart never joined the agreement, but the FTC frequently prosecutes “invitations to collude” under Section 5 of the FTC Act.

According to the FTC, the agreement eliminated price and service competition among the distributors for the GPOs’ business. This in turn distorted prices and undermined the ability of independent dentists to obtain lower prices and discounts for dental products. The distributors’ conduct also allegedly unreasonably reduced the output of dental products to GPOs. To date, only Schein has filed an answer, stressing its “unique and long-standing history of doing business with numerous group purchasers, including buying groups[,]” and denying the allegations, as well as stating that the FTC mischaracterized or took out of context statements of its executives.


It can be tempting to assume that because buying groups leverage the collective purchasing power of smaller groups to negotiate lower prices, it is only fair for suppliers to counteract that leverage through coordination with competitors. But such actions are illegal. Buying groups serve as permissible means for individuals and small groups to take advantage of discounts, and coordinated efforts to avoid offering discounts will come under antitrust scrutiny. The FTC’s reliance on written communications also underscores the need for executives to carefully consider the content of any communications with competitors.

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New Webinar: Healthcare Litigation in a Transforming Environment

In just the first year of the Trump administration, healthcare has faced an avalanche of change—from the proposed “conscience regulation” to tightening False Claims Act (FCA) scrutiny to new Medicaid work requirements. The disputes arising from the flood of new developments encompass both legal and regulatory challenges—and are being played out in both courts and government agencies. Ultimately, they may trigger significant shifts in existing healthcare law.

How will healthcare litigation be affected? What are the game-changing trends and cases to watch in 2018—and how could they remap the legal and regulatory landscapes? Find out in a new Manatt webinar for Bloomberg BNA. Participants will:

  • Gain the latest insights into the Trump administration’s healthcare positions, policies and priorities—including what we’ve seen in the first year and what’s likely to come.
  • Understand the major FCA cases transforming fraud and abuse litigation and the decisions to watch in the year ahead.
  • Explore the new guidance from the Centers for Medicare & Medicaid Services (CMS) for states seeking 1115 waivers that condition Medicaid eligibility on work and community engagement.
  • Examine the issues around the proposed “conscience regulation,” as well as the new CMS guidance to Medicaid directors restoring state flexibility to decide program standards.
  • Get an update on the laws and litigation around discrimination on the basis of gender identity and termination of pregnancy.


Ileana Hernandez, Partner, Litigation, Manatt, Phelps & Phillips, LLP
Michael Kolber, Partner, Manatt Health
Craig Rutenberg, Partner, Litigation, Manatt, Phelps & Phillips, LLP

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Rest in Peace, IPAB

By Ian Spatz, Senior Advisor, Manatt Health

Editor’s Note: When Congress passed the budget deal on February 9, it put an end to the Independent Payment Advisory Board (IPAB) that was created in the Affordable Care Act (ACA). In a recent Health Affairs Blog post, summarized below, Manatt Health examines the creation of IPAB—and the reasons behind its demise.


The Creation of IPAB  

Prior to the ACA, there was frustration with both Medicare cost increases and the well-founded belief that Congress lacked the will to make tough decisions related to the program. This led to the concept of delegating the specifics of Medicare to an independent board. 

In 2009, Jay Rockefeller (D-WV) introduced legislation that would have converted the Medicare Payment Advisory Commission—the congressional advisory group on Medicare—into an executive branch commission with specific savings targets and more formal authority to implement them. 

Later that year, Peter Orzag, the Director of the Office of Management and Budget, wrote to Congress supporting Rockefeller’s idea and advancing a related concept modeled very roughly on the Defense Base Closure and Realignment Commission (BRAC). Created by Congress in 1980, BRAC successfully insulated Congress from the tough decisions to close military bases. Similarly, Orzag’s proposed board—the Independent Medicare Advisory Commission (IMAC)—would present a package of Medicare changes to Congress that it could vote up or down. Presumably, the individual changes were politically unpalatable but together might avoid rejection.

Finance Committee Chairman Max Baucus (D-MT) included the idea that became IPAB in his committee’s version of what became the ACA. The committee’s IPAB was a 15-member body that would create a Medicare plan with enough specific cuts to reduce program spending to growth levels set forth in the law. Congress could accept the plan or create an alternative that achieved equal savings. Absent congressional action, the IPAB plan would become law.    

As the ACA moved through the congressional process, IPAB was reshaped and given detail. With estimated savings of $15.5 billion between 2010 and 2019, IPAB was adopted with the rest of the ACA, despite opposition by some health industry advocates.

IPAB’s Failure to Launch

Under the ACA, IPAB could not make recommendations until the Actuary for the Centers for Medicare & Medicaid Services (CMS) certified that projected Medicare spending per capita over a five-year period would exceed targets established in the new law. From 2013 through 2017, the Actuary completed its estimates, which never exceeded the targets. Therefore, IPAB had nothing to do. 

Moreover, IPAB had no members. Congressional Republicans, opposing IPAB and the entire ACA, made no recommendations—and the Obama administration made no appointments, citing the lack of need for members, given the Actuary’s estimates. 

IPAB’s original goals had appeal. To make any important changes to Medicare, CMS must go through the cumbersome process of seeking approval from the House and Senate, whose members have little healthcare knowledge and a history of bending to powerful constituents. IPAB was an attempt to get around this system and bring an evidence-based process to key Medicare decisions. In that, it failed.    

Why IPAB Failed

Some of the reasons for IPAB’s failure can be traced to its design:

  • To control program costs, there is no good reason to wait until arbitrary targets are exceeded. Good management should include regular reviews of where we can improve the value of healthcare.
  • The legislation initially prevented IPAB from recommending cuts to providers already cut by the ACA—raising concerns from those remaining in IPAB’s purview that cuts would focus on them. IPAB also was prevented from making recommendations that might raise revenues, alter beneficiary premiums or cost sharing, limit benefits, modify eligibility criteria, or “ration” healthcare. Therefore, IPAB would have been forced to focus almost exclusively on cutting provider reimbursement.
  • The law’s requirement that IPAB’s recommendations produce specified levels of savings in one year biased it toward short-term goals—and discouraged fundamental changes to healthcare delivery that may have taken years to bear fruit.    
  • IPAB’s members had to be full-time government employees with no other “business, vocation or employment”—rules so stringent they would discourage most qualified people from serving.

Even if these design problems had been corrected, IPAB would likely still have failed. Ideas to evade the messiness of the political process in the interest of more efficient governance are felled by the sharp knives of the political process itself. Although IPAB sought to balance apolitical management with political oversight, it could not ultimately survive the reality of healthcare politics in the United States.

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Healthcare Is Among the Largest, Fastest-Growing U.S. Employment Sectors

Employing more than one in eight members of the U.S. workforce, healthcare is among the nation’s largest and fastest-growing employment sectors. From 2011 to 2016, healthcare employment grew 9%.

Healthcare jobs are also relatively well-paid, with healthcare employers providing their workers and communities nearly $1 trillion in wages. Healthcare workers earn higher-than-average wages, with an average income in 2016 of $55,000 compared to non-healthcare workers, who earned an average of $53,000.

Note: Analysis conducted by Manatt Health senior managers Kevin McAvey, Jessica Nysenbaum and Dhaval Patel.

Source: Manatt analysis of Bureau of Labor Statistics Quarterly Census of Employment and Wages data files, 2010–2017

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