Slowly but surely, the pace of change in healthcare is starting to accelerate, and 2019 will be a dynamic year for the industry with major regulatory, technological, and business innovation. There will be false hype, breakthroughs, the failure of traditional business models, and plenty of cross-pollination both within healthcare (payers, providers,Life Sciences) and between industries (healthcare and technology).
Below are five trends impacting the year ahead, and specific predictions related to each trend. I’ve tried to skip the obvious trends/predictions (political battles over drug prices, legal battles over the Affordable Care Act, explosion of data in the industry, gradual movement to the cloud, etc.), and focus on the more subtle changes shaping the industry.
In December, the Department of Health and Human Services’ (HHS) Office of Civil Rights circulated a Request for Information to the public, seeking input on how the Health Insurance Portability and Accountability Act (HIPAA) might be modified to further enable coordinated, value-based care.
Separately, 2018’s privacy scandals and the implementation of GDPR in Europe have led to a surge in interest in a general federal privacy law, which–though not specific to healthcare–would have consequences for health data that is not already covered by HIPAA. Several states seem prepared to follow in the footsteps of the California Consumer Privacy Act and pursue their own legislation, and federal privacy legislation is a real possibility for the first time in decades.
Any regulatory changes will take place against the backdrop of frequent health (and other) data breaches. There will be many contributing factors, from insecure legacy systems to employee error; from the rapid proliferation of consumer-facing health devices to bad actors. At the same time, inquisitive journalists are likely to find many instances of the improper monetization and use of health data. These incidents will put a spotlight on patient privacy, and will heighten the debate around new regulation.
Predictions:
While the FDA has a long-track record of using RWE for post-marketing drug safety surveillance (Sentinel; NEST), and–to a lesser extent–measuring efficacy (historical comparators in single-arm studies), the framework that the FDA released in December lays out an initial roadmap for new ways that real world data could be used in conjunction with traditional clinical trials for drug approvals.
The FDA has already reviewed applications for oncology treatments that incorporate real-world evidence; is funding the replication of 30 randomized controlled trials to better understand RWE methods and trial designs; and has indicated that it is prepared to consider RWE when adding or modifying drug indications.
As RWE becomes increasingly accepted, sponsors and contract research organizations (CROs) are racing to build up competence in collecting real-world data at the point of care, incorporating lab and genomic data in their trials, and performing the analytics necessary to convert the data into RWE.
Predictions:
I’ve already written about how Roche’s acquisition of Flatiron marked the loudest shot yet in healthcare’s platform wars asLife Sciences companies evolve into modern data companies. GSK’s investment in 23andMe gave them exclusive access to the company’s DNA database, while sequencing and diagnostics company GRAIL drew new investment from Merck and Johnson & Johnson (as well as Google and Amazon).
Meanwhile, in the broaderLife Sciences market, CROs are also making aggressive moves related to data, responding to IQVIA’s acquisition of IMS and PRA’s acquisition of Symphony Health in the last few years. New business models are emerging that are more focused on effective data sharing between entities than aggregating and reselling data.
These acquisitions fit into a broader data strategy that enables the acquiring companies to set up flywheels where they can use data to discover, develop and get drugs to market more quickly than competitors (all while generating additional data in the process).
Predictions:
As more companies pursue vertical integration in 2019, large, stand-alone health insurance companies will find themselves at a disadvantage competing with integrated health delivery systems. The combination of CVS Health and Aetna now functions as a retail pharmacy (CVS), a provider (MinuteClinics), a pharmacy benefits manager (Caremark), and an insurer (Aetna). If the integration is successful, the consolidated company will be uniquely positioned to support medication adherence, offer additional services for chronic care management, and–as a result–offer more competitive premiums than traditional insurance companies.
In addition to the traditional players consolidating into vertically integrated firms, there are new but well-heeled healthcare entrants. While there are still more questions than answers when it comes to Amazon, Berkshire, and JPM’s flashy joint health venture, Amazon raised eyebrows when it acquired PillPack, an online pharmacy; and again when it recruited a Head of Measurement to the project from Blue Cross Blue Shield in November. Others have already speculated that Amazon will enter the insurance market in 2019. And who better to transform the consumer health experience than the customer-obsessed technology giant that completely transformed retail (and recently announced that it has over 100 million Prime members)?
Predictions:
One of the biggest health tech announcements in 2018 was that the Apple Series 4 watch would feature an FDA-cleared ECG that would notify users of heart arrhythmias (there are already over 800,000 in circulation). Clinicians and patient advocacy groups are racing to keep up to validate the potential benefit of these devices; the Health eHeart study aims to better understand the benefits of heart rate monitoring through wearables, including early detection of atrial fibrillation. The Apple watch is only one of many direct-to-patient offerings: from omic tests to glucometers to blood pressure cuffs.
As health applications and devices proliferate and give patients access to more of their health data than ever before, there are two primary challenges. The first is validating the accuracy and potential benefit of these devices. The second is ensuring that all of this data is interoperable, allowing patients to share data with relevant providers (already a challenge just with electronic health records).
Today, patient portals have limited functionality and physicians report that few patients meaningfully interact with these systems. However, increasing patient engagement is leading to significant demand for a simple way to navigate all of one’s relevant health data, and to better understand how to act on that data.
Predictions:
It should be an exciting year ahead!
Thanks to Bob Borek, Shahir Kassam-Adams, Jason LaBonte, Patsy Bailin, and Sam Roosz for their help in drafting and conceptualizing this article.
Healthcare Predictions for 2019 was originally published in Datavant on Medium, where people are continuing the conversation by highlighting and responding to this story.
AnalyticsIQ, a marketing data and analytics company, recently adopted Datavant’s state de-identification process to enhance the privacy of its SDOH datasets. By undergoing this privacy analysis prior to linking its data with other datasets, AnalyticsIQ has taken an extra step that could contribute to a more efficient Expert Determination (which is required when its data is linked with others in Datavant’s ecosystem).
AnalyticsIQ’s decision to adopt state de-identification standards underscores the importance of privacy in the data ecosystem. By addressing privacy challenges head-on, AnalyticsIQ and similar partners are poised to lead clinical research forward, providing datasets that are not only compliant with privacy requirements, but also ready for seamless integration into larger datasets.
"Stakeholders across the industry are seeking swift, secure access to high-quality, privacy-compliant SDOH data to drive efficiencies and improve patient outcomes,” says Christine Lee, head of health strategy and partnerships at AnalyticsIQ.
“By collaborating with Datavant to proactively perform state de-identification and Expert Determination on our consumer dataset, we help minimize potentially time-consuming steps upfront and enable partners to leverage actionable insights when they need them most. This approach underscores our commitment to supporting healthcare innovation while upholding the highest standards of privacy and compliance."
As the regulatory landscape continues to evolve, Datavant’s state de-identification product offers an innovative tool for privacy officers and data custodians alike. By addressing both state-specific and HIPAA requirements, companies can stay ahead of regulatory demands and build trust across data partners and end-users. For life sciences organizations, this can lead to faster, more reliable access to the datasets they need to drive research and innovation while supporting high privacy standards.
As life sciences companies increasingly rely on SDOH data to drive insights, the need for privacy-preserving solutions grows. Data ecosystems like Datavant’s, which link real-world datasets while safeguarding privacy, are critical to driving innovation in healthcare. By integrating state de-identified SDOH data, life sciences can gain a more comprehensive view of patient populations, uncover social factors that impact health outcomes, and ultimately guide clinical research that improves health.
Both payers and providers are increasingly utilizing SDOH data to enhance care delivery and improve health equity. By incorporating SDOH data into their strategies, both groups aim to deliver more personalized care, address disparities, and better understand the social factors affecting patient outcomes.
Payers increasingly leverage SDOH data to meet health equity requirements and enhance care delivery:
Payers’ consideration of SDOH underscores their commitment to improving health equity, delivering targeted care, and addressing disparities for vulnerable populations.
Capital District Physicians’ Health Plan (CDPHP) incorporated SDOH, partnering with Papa, to combat loneliness and isolation in older adults, families, and other vulnerable populations. CDPHP aimed to address:
By integrating SDOH data, CDPHP enhanced their services to deliver comprehensive care for its Medicare Advantage members.
Value-based care organizations face challenges in fully understanding their patient panels. SDOH data significantly assists providers to address these challenges and improve patient care. Here are some examples of how:
By leveraging SDOH data, providers gain a more comprehensive understanding of their patient population, leading to more targeted and personalized care interventions.
While accessing SDOH data offers significant advantages, challenges can arise from:
To overcome these challenges, providers must have robust data integration strategies, standardization efforts, and access to health data ecosystems to ensure comprehensive and timely access to SDOH data.
With Datavant, healthcare organizations are securely accessing SDOH data, and further enhancing the efficiency of their datasets through state de-identification capabilities - empowering stakeholders across the industry to make data-driven decisions that drive care forward.
Explore how Datavant can be your health data logistics partner.
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