Achieving speed-to-precision in patient engagement and care

Oct. 31, 2018
Eric Sullivan, Senior Vice President, Innovation & Data Strategies, Inovalon

Organizations across the healthcare landscape are increasingly relying on more disparate sources of clinical, claims, and other types of data to further improvements in patient care. The ability to create a timely, accurate, and complete Enhanced Patient Profile (EPP) from which actionable information can be infused into patient engagement and care strategies is key to meaningfully advancing better care quality and clinical outcomes in the U.S. Extracting, analyzing, and filtering the enormous amount of information collected proves challenging, however, when a lack of system connectivity and limited and inaccurate data sources are the rule rather than the exception. In the absence of the EPP, clinicians are often left unable to treat patients in the most efficient, effective, and precise manner.

Accelerating the identification of meaningful healthcare data

When combined with clinical interoperability, innovative artificial intelligence (AI) technologies like machine learning (ML) and natural language processing (NLP) attempt to address these obstacles head on. First and foremost, big data approaches that focus on combining typical claims-based information with clinical data require access to electronic health records, and for most payers and large non-integrated health systems, this is neither a feasible nor practical matter.

With the clinical data in hand, one needs to leverage real-world applications of ML and NLP, which are now showing promise to drive greater efficiencies and overall value in healthcare. With much of the most relevant patient-level information supporting the EPP buried in loosely or fully unstructured text, ML and NLP technologies are proving highly valuable to accelerate the time it takes to confidently mine and validate it as parsed information able to stand on its own. The EPP, which effectively operates as the prized patient-level “single source of truth,” supports the calculation of quality-based and other clinical measures—only now achievable with these advancing technologies.

Empowering clinicians with real-time, on-demand data-driven insights

In a value-based care environment, traditional batch systems and technologies are being replaced with more real-time analytic models to identify the right patients to engage—as well as how and when to engage them—and ultimately arm clinicians with the insights required to deliver at the point of care. This is derived best through the EPP.

By combining the interoperability investment used to create the EPP with the in-memory technologies that can perform advanced analytics, the healthcare industry is just now able to achieve real-time data insights. Armed with the ability to access these insights on-demand at the point of care, clinicians are better enabled to identify and address gaps in quality, utilization, and medical history and drive improvements in clinical and quality outcomes across their patient population, as well as economic performance. The ability to deploy platforms that analyze millions of unique and evolving data points to create patient-level insights is transformative for improving the treatment of many clinical conditions. While many organizations strive to do this within their unique workflow, most still rely on “outside” systems for support. Fortunately, we are seeing more advanced and innovative healthcare technology firms stepping out into that exciting territory.

A continued evolution

The advancements of big data analytics stemming from interoperability and AI technologies continues to evolve. Scalable, cloud-based platforms—coupled with integrated diverse data sets and real-time patient-specific analytics culminating in the EPP—are shifting the role of the clinician from merely diagnostician to well-informed decision maker. As big data analytics and AI technologies support healthcare stakeholders in making more informed care decisions, faster, reimbursement and payment models will also evolve to reflect these capabilities. And, as organizations across the healthcare continuum vie to demonstrate speed-to-value in the delivery of high-quality, cost-effective care, the entirety of the healthcare industry will benefit from better health outcomes and a more seamless healthcare experience for patients.