As the healthcare industry grapples with the daunting challenges of achieving interoperability, stakeholders are focused on solving the fundamental problem of ensuring that all parties “speak the same language,” through the use of common data models and vocabularies.
Semantic interoperability, the ability of two or more healthcare systems to share clinical information and use it meaningfully, is a critical requirement for enabling population health management and the rapidly approaching transition from fee-for-service to value-based care models.
However, the lack of a universal terminology standard is a major barrier to communication between different electronic health record systems and the ability to derive clinical meaning from EHR data imported or queried from elsewhere.
“There’s not always a shared language. There’s no agreement on a common data alphabet, if you will, about how technology will speak to different systems but also to new and emerging systems,” said National Coordinator for Health IT Karen DeSalvo, MD, at this week’s HIMSS16 conference in Las Vegas.
However, Brian Levy, MD, chief medical officer for terminology management vendor Health Language, points out that semantic interoperability is not just a problem for the electronic exchange of data between disparate EHR systems at different healthcare organizations. Levy says it’s not uncommon for the IT department in a large health system to be charged with governing content for 40 or more information systems—all with their own inherent language and clinical terminology infrastructure.
On Monday at HIMSS16, Department of Health and Human Services Secretary Sylvia Burwell announced that companies providing 90 percent of the EHRs used by U.S. hospitals and more than a dozen of the country’s largest private healthcare systems have pledged to implement three core commitments that will improve the flow of health information to consumers and providers.
“We’ve got lots of big, successful vendors and they produce good software, but each vendor has a proprietary database and they use proprietary terminologies,” adds Stan Huff, MD, chief medical informatics officer at Intermountain Healthcare. “As a result, the data isn’t consistent between any two systems, so it’s not easy to exchange data. And, even within the same EHR vendor, the systems can be configured differently and are not truly interoperable.”
The goal, according to Huff, should be to make data consistent through standardization of information models that are mapped to clinical terminology standards such as LOINC and SNOMED. “Those models become, if you will, a common language around which we can exchange and use information that is non-proprietary, that everyone can support, and creates the ability then to create applications that can run on any platform that supports the standards.”
Huff is chairman of the board of the Healthcare Services Platform Consortium, a group of providers, vendors, system integrators and venture-led firms dedicated to solving the industry-wide interoperability problem. HSPC is attempting to create a next-generation IT platform to build a services architecture foundation that includes standard clinical-data models and terminologies to achieve true semantic interoperability.
According to Health Language’s Levy, accountable care, health information exchange, population health management and value-based care models are all challenged by the current lack of semantic interoperability across the healthcare industry. The Health Language platform is designed to standardize and normalize data from across disparate systems by mapping, translating, updating and managing standard and enhanced clinical terminologies.
Quote“FHIR is still pretty nascent, and one of the next challenges is figuring out how to standardize the content in the FHIR messages,”
“The deeper level of interoperability, where we play, is semantic interoperability,” says Levy. “Organizations need more than just to see the information of the EHR. They need to understand it in a meaningful way. We can’t effectively leverage all this data through analytics unless we have normalized data to make sense of the data in the first place.”
HL7’s Fast Healthcare Interoperability Resources (FHIR) is gaining momentum as an open health data standard that offers a promising approach to meeting the demand for semantic interoperability and minimizing the need for metadata translation services. FHIR is supported by a rich information model to achieve semantic interoperability of clinical data.
For its part, Health Language is planning to incorporate FHIR into its product offerings within the next two years, with the standard being used to both extract and upload data for seamless data management.
“FHIR is still pretty nascent, and one of the next challenges is figuring out how to standardize the content in the FHIR messages,” concludes Levy. “It is an ongoing process to make sure that FHIR has standard value sets and terminology services that are supported.”
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