Healthcare isn’t ready for real-world data: How technology can help

Healthcare has a good problem: too much patient data. It’s everywhere, spewed across the care continuum from electronic health records (EHRs) to claims processing systems, pharmacy information systems and more. And with growing evidence that data on social determinants of health (SDoH) like food insecurity, housing instability or illiteracy is needed to inform diagnosis and treatment, the massive influx of data will only continue to grow.

When SDoH data is combined with patient data like access to health services with excessive emergency room visits or poverty level with heart arrhythmia—we can refer to all this data derived from a variety of sources as real-world data (RWD)—it has the potential to deliver a new healthcare model that takes into account the entirety of each person’s health experience while improving patient health outcomes and reducing the cost of care.

But traditional healthcare and life sciences companies are missing out on the gold mine that is RWD, because the industry isn’t ready to meet rising patient and governmental demands.

That’s because the U.S. healthcare system has a deeply flawed technology architecture. When government regulations drive innovation, it shows just how far behind the curve an industry is. A shift to a new technology architecture based on interoperability that allows for more data sharing and greater patient accessibility is needed; otherwise, healthcare organizations will be left vulnerable to compliance issues and unable to meet patient demand.

Federal guidelines drive the need for change

The challenge of interoperability—or technology that enables healthcare organizations to easily exchange patient data—has been revealed by two major shifts in regulations that govern health data management.

In healthcare, the U.S. Department of Health and Human Services (HHS) recently announced that by 2020, insurers must make healthcare data accessible to patients and adopt EHR interfaces that enable data sharing. This move stands to address one of the most difficult challenges facing the industry today: the cost of care. The Senate Health Committee Chairman, Lamar Alexander, cites a lack of interoperability as a key factor driving up healthcare costs. When patients and their providers don’t have all the information, mistakes are made, unnecessary tests are run, hospital stays are extended and healthcare costs balloon. Multiply that across the entire health system, and it’s easy to see why some estimates put the impact in the range of $35 billion each year.

In life sciences, the FDA framework for real-world data (RWD) and real-world evidence (RWE), which was released in December 2018, provides a roadmap for how the FDA will incorporate RWD and RWE in the future. Think of RWD as the raw data captured across devices and databases, while RWE is the analysis of that data for use in drug and medical product and healthcare service development.

By issuing guidelines ahead of marketplace adoption, the FDA is acknowledging the potential of real-world data and RWE. It stands to make critical improvements to the entire life sciences industry, from drug discovery to post-market surveillance, with benefits like a faster time-to-market for new drugs or patient safety interventions that take into account their everyday experiences.

However, there are gaps in sources of RWD, such as longitudinal data on worsening conditions or unstructured information only located in physician’s notes. Presently there’s a lack of strategies to address those gaps, and it’s threatening to undermine the potential of real-world data. Most drug and medical device manufacturers are scrambling to keep up with the regulatory shift.

Because many healthcare and life sciences organizations lack the core platforms and competencies to accomplish interoperability and take advantage of big data, they’ll be at risk of non-compliance with the FDS and HHS mandates. In the long-term, this will result in an increase in cost to patients and missed opportunities to improve outcomes.

Clearly our healthcare system and all of its payers and providers need to move in a direction that enables better data quality, accessibility and consistency. To meet the demands of a rapidly evolving regulatory environment and patient expectations for a whole-person, total health experience, healthcare organizations need to begin by transforming their data services architecture.

The new tech approach to enable information-sharing

Many of today’s healthcare and life sciences technology stacks rely on a digital foundation known as monolithic architecture to manage, support and share information between their applications and data. Because of the unyielding, one-size-fits-all design of a monolithic architecture, it doesn’t play well with new technologies required to incorporate RWD and RWE.

Think of it as a typical house – you can’t simply add several floors on top without causing problems to the foundation. Any changes in programming or data sharing in a monolithic architecture impact the whole system, necessitating complete redevelopment.

To implement and realize the full potential of RWD, RWE and interoperability, companies must shift to a new technology architecture. In our distributed healthcare system, where drug and device manufacturers, hospitals, payers and providers may all run different databases with unique programming languages, an emerging type of architecture stands to bridge the interoperability gap: microservices.

A recent study by Zion Market Research projects that the U.S. healthcare microservices market will grow from $130 million in 2018 to $519 million in 2025. If monolithic architecture relies on a static foundation that needs to be rebuilt to accommodate new modifications, microservices architecture is a modular home capable of being scaled and connected to designs as needed. It enables healthcare organizations to leverage data in ways they couldn’t previously. Whether that means simple solutions like a provider having a patient’s entire medical history available at the touch of a button or the more complex of garnering insights from their smartwatch to identify health interventions, real-world data from all sources can be leveraged to create better outcomes and reduce the cost of care. A microservices strategy is far more suited to the future, which is cloud-based software with API development that empowers data sharing between applications, not to mention delivering the interoperability mandated by impending regulations.

Ultimately, the goal is a more connected care ecosystem that realizes the whole-person, total health experience that today’s patients deserve and will come to expect. Microservices can increase the speed of care delivery, accelerate innovation and enable deployment of new care models that heighten the efficiency of business operations. By breaking down legacy care silos, the gaps preventing shared data and communication, and integrating data through interoperability, we can take a fragmented industry and stitch together the future.

Disruption rarely announces itself before turning an industry on its head. With regulators demanding increased sharing and a more solid framework for patient data, healthcare companies need to react, not just to survive but to thrive—and they must do so now if they want to play a leadership role in the era of information sharing.

To learn more about how Concentrix Catalyst is changing the landscape of patient data in healthcare, download our whitepaper on using artificial intelligence to predict hospital readmission rates.

About the Author

Ham Pasupuleti has held strategy and operations roles in the IT industry for more than 27 years, implementing and managing business-critical applications and systems infrastructure for Global 1000 companies. At Concentrix Catalyst, he provides business analytics and optimization solutions to healthcare organizations, enabling them to transform into outcome-based delivery models that are high quality, accountable, patient-centric, and cost-effective.