At the core of advancing data analytics and seamless care collaboration is healthcare interoperability. When you define interoperability, or ask yourself, what is interoperability, it is simply the ability of devices and systems to exchange and use electronic information from other devices and systems without special effort on the part of the user. The question of what is interoperability in healthcare, also referred to as healthcare data interoperability specifically includes the technologies used in patient care to enable the sharing of data to meet the goals of delivering personalized care and effective population health management.

The current lack of interoperability in healthcare can compromise patient safety, contribute to clinician burn-out, and waste billions of dollars a year. One study found that the lack of healthcare data interoperability costs the U.S. health system over $30 billion a year.

As you would expect, the lack of interoperability in healthcare also hinders development, which may be the biggest missed opportunity for the health interoperability ecosystem. Innovators in healthcare system interoperability face challenges accessing data, integrating into highly-customized environments, and scaling semantic interoperability across a variety of data landscapes. In turn, innovators often avoid the healthcare market altogether since developing interoperability in healthcare is extremely challenging.

While interoperability standards in healthcare have made progress forward to define interoperability standards and help providers understand what does interoperability mean, there is still a great deal of work to be done as new challenges face the healthcare system caused by the COVID-19 pandemic.

ONC interoperability rules, CMS policies such as the CMS Interoperability & Patient Access Rule and 21st Century Cures Act, and the growing adoption of new electronic data standards like HL7 FHIR represent great progress, but these are just the first steps toward advancing healthcare data interoperability. Executing real working examples of interoperability in healthcare still remain. The interoperability in healthcare definition and ultimate goal is still to combine all aspects of the patient experience into a comprehensive, complete profile, capable of driving better decision making about which patients require intervention, how and when to address those needs, and deliver better outcomes.

In today’s health interoperability ecosystem, organizations that define interoperability as engaging in the bi-directional exchange of data are experiencing the greatest success. However, clinical data exchange standards are not yet scalable on a macro level, and differences in provider connectivity are a constant hurdle.

With both providers and payers feeling the stress from regulators to enhance outcomes and quality while decreasing costs, the mission for healthcare data interoperability and the interoperability of health information systems remains challenging for most. Many questions remain for both payers and providers around how to best ensure data accuracy, completeness, and define interoperability standards. Different performance measures and varying coding and reporting requirements pose significant hurdles to the interoperability meaning. However, the benefits of scalable data sharing far exceed any existing challenges.

Payers strive to get the complete and accurate data they need. But properly integrated healthcare data interoperability and clinical decision support tools can help ensure payers and providers have the right information at the right time. We’ve moved from a time period of “how do I get more healthcare analytics on my patient” to “how do I turn these data insights into actual revenue generating opportunities.”

We know that health systems, payers, providers, and hospitals are all seeking innovative and yet manageable approaches to interoperability in healthcare. Intelligent organization of claims, accurate diagnosis, computer assisted coding and other patient insights using the latest artificial intelligence in healthcare like NLP technology and medical machine learning will push this endeavor forward. Real-time data exchange of relevant healthcare information between payers and providers improves not only the quality of care, but the efficiency in which it is delivered in the evolution to value-based healthcare.

Interoperability in healthcare will continue to evolve and improve as new advancements in technology are made. In order for the healthcare industry to feel the benefits of interoperability in healthcare and move forward, clinical data needs to flow freely across networks. For this reason, healthcare organizations need IT systems and software applications that communicate and exchange patient data efficiently and securely, using the latest healthcare data interoperability principles.

ForeSee Medical has created a software application using the latest FHIR healthcare interoperability standards for your HCC risk profiles, allowing you to view HCC risk analysis of the patient you are currently interacting with - enabling real-time conversations and recommendations, without having to leave the EHR window.

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Blog by: The ForeSee Medical Team

The Future of Clinical Interoperability in Healthcare