July 13, 2020

Realizing the Promise of Interoperability in 2020 and Beyond

Bill Moroz

Topic:   Industry Focus

Last updated: October 27th, 2020

One of the most important requirements in providing high-quality, efficient care is also one of the most challenging to achieve: how to seamlessly connect vital healthcare processes across public health, health insurers, providers, and technology partners for the ultimate benefit of patients.

As the COVID-19 pandemic is demonstrating, the purpose of interoperability exceeds the capabilities of any single electronic medical record (EMR). This lack of interoperability – and standardization – has a measurable impact on care coordination, public health reporting and response, and clinical research, for example, with healthcare professionals spending inordinate amounts of time gathering data to share through disparate and individual websites and data feeds.

And while this COVID-19 era will irrevocably change healthcare and care delivery in ways not yet fully envisioned today, interoperability is poised to play an essential role in the industry’s near-term recovery and provide the means by which we can achieve fundamental improvements to access and quality.

Interoperability: The Key to the Next Normal

Industry reports estimate that elective care services, a market decimated by COVID-19 response, account for more than 50 percent of a typical provider organization’s revenues.1 As providers prepare for a partial recovery of elective services and adapt to projected depressed demand throughout 2020, patients are embracing care alternatives including, most notably, telehealth. By connecting and supporting workflows across care spectrums, interoperability addresses this progressing area of opportunity while enabling healthcare organizations to nimbly adjust to ever-shifting circumstances.

And yet the criticality of health IT interoperability was apparent before this newest coronavirus battle, as the industry attempted to coalesce around rules and standardization for many years. Still, in many instances, these efforts were standardizations in the “small” rather than in the “large,” hindering the achievement of true interoperability. Variances in standard format for EMR/EHR record sharing (CCD or C-CDA), data integration standards (FHIR vs. HL7 2.x), and payer/provider data matching (clinical vs. claims data) were smaller focal points while larger standardization focal points such as the use of single patient identifiers, common across Europe, remained elusive, collectively contributing to interoperability delays and false starts.

Now, the final interoperability rule of the Cures Act addresses data access provisions and standardization, establishing Fast Healthcare Interoperability Resources (FHIR) as the foundational standard to enable data exchange via secure application programming interfaces (APIs). We support these new rules as a meaningful step in the right direction though we believe standardization alone is not the solution.

The Case for Interoperability With Data Management

As these rules are being put forward, we find many healthcare professionals using the terms integration and interoperability interchangeably, as the hope of interoperability is that it will deliver real-time, meaningful data exchange without the need to address integration or data quality and management.

To holistically manage the patient journey and make operational and care improvements actionable, healthcare organizations must also bring together other critical data sources, including financial, workforce, and survey data.

The truth is, despite new interoperability standards, healthcare data is complex and varied, growing ever more diverse as new sources such as social determinants of health (SDoH), patient-contributed data, and device data add dimension. To holistically manage the patient journey and make operational and care improvements actionable, healthcare organizations must also bring together other critical data sources, including financial, workforce, and survey data.

Bringing all of these sources of healthcare data together requires the ability to:

    • Manage and harmonize millions of code sets
    • Create master records for domains including patient, physician, facility, workforce, and member
    • Curate and manage thousands of complex industry value sets and quality measures

To do so, organizations such as St. Luke’s University Health Network use a data management and analytics platform to create, access, and exchange a single source of trusted data and provide fully realized interoperability benefits across its care spectrum and for its stakeholders. Similarly, The Health Collaborative, a nonprofit health improvement organization that runs a regional health information exchange, uses this approach to deliver next-generation HIE capabilities, equipping health networks; public sector health departments; and social service agencies, physicians, and behavioral health stakeholders with shareable, trusted data.

Fully realizing the promise of interoperability requires not only the critical step of standardization but also the necessary commitment to harmonization and management of data. Taken together, stakeholders across the complexity of patient care and serving in our newly emerging, post-COVID-19 landscape will be able to harness both data and insights to improve the care provided and support the outcomes desired.

*This blog post originally appeared in Healthcare Dive.


1 Leventhal, Rajiv. “The Most Pressing COVID-19 Questions Today: A Perspective from Advisory Board.” Healthcare Innovation, Endeavor Business Media, LLC., 27 Apr. 2020, www.hcinnovationgroup.com/covid-19/article/21135789/the-most-pressing-covid19-questions-today-a-perspective-from-advisory-board.

Bill Moroz is the senior solutions architect for ibi. He has been helping healthcare organizations to derive value from data for more than 20 years. His experience includes interoperability, data management, analytics, and artificial intelligence (AI).

As an innovative, results-driven professional, he participated in developing the HL7 standards and HIE/RHIO networks. Bill has experience in the AI/machine learning space, working on projects for clinical variation management and claims FWA.

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