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Life sciences outlook for 2019: Moving from the hypothetical into a new reality

Health Care Current | December 11, 2018

This weekly series explores breaking news and developments in the US health care industry, examines key issues facing life sciences and health care companies, and provides updates and insights on policy, regulatory, and legislative changes.

My Take

Life sciences outlook for 2019: Moving from the hypothetical into a new reality

By Greg Reh, vice chairman, US and Global Life Sciences leader, Deloitte LLP

As we step into the new year, the pace of change in life sciences feels like it is moving faster than ever. While trends in the industry generally take place over decades rather than years, many of the foundational elements to shift from treatment to wellness, for example, are beginning to take shape.

Several trends will likely continue to shape biopharmaceutical and medical device manufacturers in 2019. As the sector continues to face pressure to drive prices down and demonstrate the value of their products, the use of outcomes-based payment models is expected to become more common. In response, health care stakeholders, including medical device manufacturers and biopharma companies, will likely need to accept more risk for the value that their products provide. At the same time, biopharma companies will likely continue to seek ways to reverse the declining return on research and development investments, and they should adapt to the new regulatory frameworks that are expected to emerge in the year ahead.

These trends, taken collectively, are likely going to push life sciences companies to become more efficient, nimble, and customer-focused. Growth in the use of digital technologies, increased use of omics and real-world data (RWD), ongoing breakthroughs in the fundamental science behind therapies and cures, the incorporation of the patient voice throughout the lifecycle of therapy development, and new types of partnerships and collaborations are signaling a shift in how the life sciences sector might operate in 2019 and beyond.

In 2019, the industry might finally reach the tipping point that moves it beyond the hypothetical and into a new reality. First, consider these four macro trends:

  1. Scrutiny over drug pricing: 2018 was undoubtedly one of the biggest years for policy efforts to reduce drug prices and out-of-pocket expenses for patients. In April, the White House and the US Department of Health and Human Services (HHS) released a “blueprint” to lower drug prices, reduce out-of-pocket costs for consumers, and make drugs more accessible. Some of the big focus areas were on proposed changes related to how Medicare Part B pays for drugs and the International Price Index, 340B changes, and proposed changes to require drugmakers to include list prices in their direct-to-consumer ads.
  2. Increased interest in contracts that demonstrate value: The launch of several gene and cell therapies has been a catalyst to advance the discussion of alternative payment models. As health plans embrace more value-based contracts, we expect life sciences companies will need to develop pricing strategies that demonstrate the long-term value of their products.
  3. The declining return on investment (ROI) for research and development (R&D): Our analysis on the ROI of R&D among 12 large-cap biopharma companies portrays a steep decline over the nine years that we have performed the analysis. Last year, R&D returns declined to 3.2 percent—down from 10.1 percent in 2010. The trend for this year looks even worse (stay tuned, we will be releasing new data in the coming weeks from our 10th annual analysis).
  4. Evolving regulatory frameworks and collaboration between industry and regulators: The US Food and Drug Administration’s (FDA) pre-certification program, which launched in late 20171, is a great example of how collaboration between industry and regulators can drive more self-regulation that is rooted in a culture of quality, organizational excellence, and performance monitoring. As software-based medical products become more mature, the feedback provided during the pilot phase of this program will help FDA refine the proposed regulatory model and could influence new regulations, address outstanding issues, and ensure that new regulations and guidelines are fit for purpose.2 FDA has also indicated that it intends to work more collaboratively with companies to bring innovations to market more quickly. In addition to its Software as a Medical Device (SaMD) pilot,3 FDA has also supported increased use of RWD and has approved a large number of innovative therapies over the past year.4 Collaboration can allow stakeholders to deliver more proactive, cost-effective care and improved outcomes.

In response to these macro trends, life sciences companies should shift their strategies—and their mindsets—to prepare for a future that is grounded in digital, data, personalization, and efficiency.

Here’s how we think life sciences companies can respond:

  • Embrace a digital-first mindset: Digital technology has the potential to change everything from the way R&D is conducted, to how clinical trials are designed, to how new products are commercialized. But, many companies are still in the experimental stage when it comes to digital and have been reluctant to make bold moves, according to a survey of biopharma executives that we conducted with the MIT Sloan Management Review. For companies to address mounting pressures, a digital-first mindset will likely be required to make business operations more efficient and bring transformational therapies to the market. We expect to see more adoption of technologies such as robotic-process automation (RPA), which can help improve the efficiency of R&D including clinical trials. Cognitive, artificial intelligence, and RWD will likely continue to transform the way new innovations are developed.

    We also expect to see more companies bring digital talent from the outside. There appears to be an expectation that these digitally savvy outsiders can offer a fresh perspective to typically conservative life sciences companies. Case in point: Global pharmaceutical manufacturer Merck recently hired its first chief digital and information officer, whose most recent experience was with consumer product companies including Nike Inc.5 Novartis’ chief digital officer was previously the CDO at one of the United Kingdom’s largest online retailers, and also held senior positions at
  • Use new forms of data to demonstrate value: The targeted nature of precision medicine could mean better patient outcomes in an increasing number of therapeutic areas—particularly if digital tools can be used to ensure patients comply with their treatment regimens, monitor the effectiveness of therapies, or report adverse events. And with outcomes-based and alternative payment models being piloted, we expect life sciences companies will focus more attention on multiple external data sources, which have the potential to drive disruption across the entire value chain—from R&D, to the delivery of care, to regulatory review and approvals. RWD can be the key to creating new business models by using patient outcomes to support value-based contracts for personalized medications, or using information from wearable devices to understand and improve the patient journey. It can help ensure medical adherence, and also help better predict outcomes.

    According to our real-world evidence (RWE) benchmarking survey, however, companies haven’t fully unlocked the potential. Only half of surveyed companies have capabilities that are mature enough to take full advantage of RWD. With the business value now better understood, more life sciences companies will align with RWD strategies in 2019 as they prepare for a new future.
  • Collaborate with new partners: 2018 was a big year for nontraditional competitors and technology companies entering the market. One of the more significant market signals in this overall industry shift was Roche’s acquisition of Flatiron Health earlier this year, pointing to the focus of big data, analytics, and personalized medicine. We’ve historically seen life sciences companies partner with providers and academia, but we expect more non-traditional acquisitions and partnerships in the new year to drive innovation and patient-focused agendas. For example, we could see more partnerships between life sciences companies and patient advocacy organizations, informatics companies, or technology firms to improve the design and delivery of therapies. Stronger partnerships between life sciences firms and their physician and hospital customers can be formed around the patient. We expect IoMT (or the internet of medical things) to lead to some interesting partnerships in 2019 as companies focus on more connected devices.
  • Find new ways to connect with consumers: Advancements in electronic health records (EHRs) are paving the way for consumers to take more active roles in their health and wellness. While some consumers still might be leery of this concept, we are seeing a willingness to embrace new tools and technologies, according to our 2018 health care consumer survey. The challenge, however, will be how to create intrinsic value for consumers and ultimately win their trust (the same survey told us consumers are least likely to share their data with life sciences companies). Technology could help bridge the gap and make clinical trials—and other connection points—more patient-friendly and accessible.

    We also expect more at-home diagnostics to enter the market in 2019, which could help put consumers at the center of their care. Data from these diagnostics, along with wearable devices, can drive more proactive health care and help companies understand their patient populations.

I believe that 2019 will be a year of change—and a year of continually evolving and advancing trends. It also could be a foundational year as companies continue to focus on wellness in addition to treatment, and on adding value to the overall health care system. The industry will be paving the way for a new future for life sciences and health care—even if it might seem incremental, these are monumental shifts to an industry focused on care driven by data and cross-collaboration across all health care (and nontraditional) stakeholders. We’ll see what 2019 has in store.

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FDA press release, September 2017 (
FDA press release, September 2018 (
Statement from FDA Commissioner Scott Gottlieb on advancing new digital health policies to encourage innovation, December 2017 (
Statement from Commissioner Scott Gottlieb on FDA’s new strategic framework to advance use of RWD to support development of drugs and biologics (
Merck press release, October 17, 2018 (
Novartis press release, August 24, 2017 (


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In the News

White House report: Competition can lower health care costs, drive quality

On December 3, the White House released a report criticizing hospital consolidations and recommending that states scale back their scope-of-practice (SOP) rules and certificate-of-need (CON) statutes to allow for more competition. According to the report, consolidation activities in health care, such as hospitals’ purchase of physician practices, contribute significantly to rising costs for patients.

Related: A day after the White House released its report, HHS Secretary Alex Azar outlined the administration’s vision for reforming the health care system. During a December 4 meeting hosted by the American Enterprise Institute (AEI) in Washington, D.C., Azar said that rather than trying to make health insurance more affordable, the administration is focusing on reducing the cost of care. Under the existing health care system, he said health plans and government payers pay for procedures instead of prioritizing value and making payments based on outcomes. He also noted there is a significant difference between what Medicare pays for services performed at hospital-owned facilities versus what is paid for services performed at outpatient centers. Costs, he added, could be reduced in Medicare by moving to a site-neutral payment system. He also told attendees that patients should be more involved in making decisions about their care.

CMS previews 2019 hospital star ratings

On December 1, CMS said hospitals can begin previewing star ratings before the February 2019 final release. The release comes after CMS delayed finalizing the ratings in July. The agency says it delayed publication of its hospital star ratings to explore updating its methodology.

In this latest release, CMS made some changes to the methodology and retained other aspects, including:

  • Keeping the latent variable model technique. A latent variable model makes statistical adjustments that assume the measures we can see (those that are reported) are related to measures we cannot see (latent). Hospital groups have said this model inaccurately depicts the quality of their services, and sometimes one measure accounts for the weight of an entire category.
  • Removing measures that negatively skew the results of the latent model.
  • Changing its measurement of health care-associated infections to more accurately reflect the rate of hospital infections.

CMS launched the rating system in 2016 to help consumers make more informed decisions about their care by providing them with a way to compare hospitals based on quality ratings. Deloitte’s 2017 analysis of the program found that, overall, there are many ways to achieve a 5-star rating. Moreover, hospitals that earn the top rating generally have better scores in the heavily weighted categories (i.e., mortality, patient experience, safety, and readmission), and scores for individual outcomes measures vary widely.

FDA Database Recognition program will let test developers use public genetic data

Genetic and genomic test developers can use information from public human genetic-variant databases to support the agency’s review of their tests, the FDA announced December 4. The FDA Database Recognition program aims to encourage database administrators to make genetic-variant data publicly available. The first genetic variant database in the program is the National Institute of Health (NIH)-funded Clinical Genome Resource (ClinGen), which developers can now use.

A genetic-variant database contains information regarding genetic differences that researchers can use to make informed assessments of a genetic variant and a specific disease or condition. By making this information publicly available, test developers might not need to generate their own supporting data. FDA will consider information from the databases to be valid scientific evidence.

(Source: FDA, FDA Recognition of Public Human Genetic Variant Databases, December 2018)

MACPAC releases annual data on Medicaid and CHIP enrollment, spending

The Medicaid and CHIP Payment and Access Commission (MACPAC) released the 2018 edition of the MACStats: Medicaid and CHIP Data Book on December 6. The report has updated data on national and state Medicaid and CHIP enrollment, benefits, and spending. It also includes information on beneficiary health, utilization, and access to care. Findings in this year’s report include:

  • Total national enrollment in Medicaid and CHIP decreased 2.2 percent from July 2017 to July 2018. According to MACPAC, enrollment growth varied by state, and 37 states and the District of Columbia—including both expansion and non-expansion states—experienced enrollment declines.
  • More than one-quarter of the total US population was enrolled in Medicaid or CHIP at some point in 2017, with 85.3 million in Medicaid and 9.5 million in CHIP.
  • Over 40 percent of all Medicaid and CHIP enrollees had family incomes below 100 percent of the federal poverty level (FPL) in 2017. Nearly 60 percent of all enrollees had incomes below 138 percent FPL—the threshold for Medicaid eligibility in states that have expanded the program to low-income adults.
  • Medicaid accounted for 9.4 percent of the federal budget, which was smaller than Medicare’s share (14.9 percent), during fiscal year (FY) 2017.
  • In FY 2017, drug rebates reduced gross Medicaid drug spending by more than half (54.5 percent). During this time, over half (62.4 percent) of Medicaid gross spending for drugs occurred within managed care plans.

(Source: MACPAC, MACStats: Medicaid and CHIP Data Book, December 2018)

Health care spending is rising more slowly, CMS’s actuaries find

According to a report from CMS’s Office of the Actuary and published in Health Affairs, the US spent $3.5 trillion on health care—about $10,739 per person—in 2017. The rate of spending growth fell from 4.8 percent in 2016 to 3.9 percent in 2017. The report attributed the slower growth in spending to decreased health service utilization (as opposed to price increases) in some of the major spending categories: hospital care, physician and clinical services, and prescription drugs. Prices did increase somewhat, but the major contributor to the deceleration in spending growth was use of services and slower adoption of more complex services. Out-of-pocket spending growth also fell significantly, from 4.4 percent to 2.6 percent. CMS attributed the drop to slower growth in nursing home and continuing care retirement communities and physician, clinical, and dental services. The actuaries found that spending growth slowed in 2017 for private health insurance and for Medicaid, while Medicare spending was flat.

(Source: Health Affairs, National Health Care Spending In 2017: Growth Slows To Post Great Recession Rates; Share Of GDP Stabilizes, December 6, 2018)

AHIP, CMS, NQF finalize effort to align quality measures across payers

On December 4, the trade group America’s Health Insurance Plans (AHIP), CMS, and the National Quality Forum (NQF) formalized the Core Quality Measures Collaborative (CQMC)—a voluntary, multi-stakeholder initiative to promote measure alignment for public and private health plans. CQMC developed eight core measure sets that cover seven medical specialties and primary-care services: cardiology, gastroenterology, HIV/Hepatitis C, medical oncology, orthopedics, obstetrics and gynecology, and pediatrics.

These measures are designed to improve care, reduce physician burden, and increase transparency for consumers. According to AHIP, plans can use the measures for their own quality-improvement programs and tailor the measures to patient groups with specific health needs.

Breaking Boundaries

CMS innovation center announces AI Health Outcomes Challenge

The Center for Medicare and Medicaid Innovation (CMMI) intends to launch an artificial intelligence (AI) challenge to seek new applications for AI and analytics related to clinical care and patient health improvement. The Artificial Intelligence Health Outcomes Challenge, which is expected to launch in early 2019, aims to harness new ideas for AI innovation across the health care industry. The challenge is open to technology vendors, clinicians, scientists, academics, and patients who have ideas for using AI to improve the quality of health care. Specifically, CMMI is interested in how clinicians and health care stakeholders can leverage AI to better predict health outcomes and enhance care delivery.

CMMI intends to incorporate innovative ideas into existing and new payment and delivery models. The Center announced it will have more information on the challenge’s timeline and awards in early 2019.

RELATED: AI is now being deployed across the health care system to inform and improve cancer prevention, cardiac care, and to advance cellular medicine. As the technology becomes more common, stakeholders are seeking to identify safe and effective applications that are targeted to the right populations and conditions. In November 2018, researchers published a study in the Journal of Digital Imaging that showed how AI can estimate full-dose positron emission tomography (PET) images from scans with significantly lower dosages of radiation to patients. A PET scan is an imaging test that shows how tissues and organs are functioning. PET scans use a radioactive drug to show activity and to detect potential diseases. In the new study, researchers demonstrated that a residual convolutional neural network could analyze PET images using one-tenth the radioactive drug without sacrificing image quality.

The study would need to be expanded for researchers to see if these technologies work on a larger scale. But the results suggest that there is potential for AI and deep learning to lower PET imaging costs and reduce radiation exposure.

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