Health Language Blog

National healthcare movements demand an interoperable framework for accurate data exchange across healthcare continuums. As value-based care continues to unfold, the industry at large remains focused on efforts to mature interoperability to support high-level quality initiatives aimed at improving population health and cutting costs.

For this reason, the Office of the National Coordinator (ONC) recently identified two metrics to support specific indicators of “widespread interoperability” in the industry. Developed in response to directives laid out by The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA), the new metrics are:

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Without semantic interoperability among disparate healthcare IT systems, sharing data in a useful way is impossible.

While a doctor knows that dropsy describes the same illness as congestive heart failure, a computer typically can’t make that type of distinction. Semantic interoperability, however, creates a common vocabulary that paves the way for accurate and reliable communication among computers.

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Healthcare’s interoperability quest continues to mature, moving the industry closer to semantic interoperability—the highest level of information exchange as defined by the Health Information and Management Systems Society (HIMSS). ONC’s recent identification of two metrics to support specific indicators of “widespread interoperability” demonstrate this movement.

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In our previous blog, we discussed the importance of leveraging administrative data for better quality assessment. As the wrap-up to this standards blog series, I want to look back at Crossing the Quality Chasm as a foundational work for improving the quality of healthcare delivery. This paper called not only for better quality but also for a reduction in the cost of that care--this at a time when the population is aging, technology is evolving, and research is rapidly expanding evidenced-based medicine. At least eight of the 13 recommendations made by the authors of Crossing the Quality Chasm directly involve the collection, aggregation, and actionable use of healthcare data. The remaining five are supporting those objectives through the development of committees that address quality care and reimbursement models, and in training the workforce to meet the increasing needs of an industry that is becoming more and more reliant on data and analytics.

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Terminology Standards Blog Series: Part 1

In the seminal work Crossing the Quality Chasm, published by the Institute of Medicine in 2001, there was a clear call to action for the U.S. healthcare system. This work has driven much of what we are seeing in healthcare information management today. Crossing the Quality Chasm called for healthcare to be safe, effective, patient centered, timely, efficient, and equitable. The argument was made that the adoption of information technology is critical to meeting these goals. I would agree.

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Without semantic interoperability among disparate healthcare IT systems, sharing data in a useful way is impossible.

While a doctor knows that dropsy describes the same illness as congestive heart failure, a computer typically can’t make that type of distinction. Semantic interoperability, however, creates a common vocabulary that paves the way for accurate and reliable communication among computers.

Read more...

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Healthcare may have been among the last industries to automate, but the sector has made up for lost time.

Indeed, electronic data and healthcare IT (HIT) systems have expanded rapidly in recent years. But technical innovation has developed in isolated pockets. The first wave of HIT development took place in the billing and claims departments. Localized development of ancillary clinical systems such as laboratory, radiology, and pharmacy followed the rollout of administrative systems. More recently, the healthcare industry’s focus has shifted to electronic health record (EHR) systems.

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Semantic interoperability represents the pinnacle of machine-to-machine communication, enabling disparate IT systems to share data in a useful way.

In the healthcare sector, semantic interoperability is critical for bridging the terminology gap among divergent health IT (HIT) systems and data sources. This capability aims to create a common vocabulary that will provide accurate and reliable communication among computers.

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Semantic interoperability has long been a key missing piece of the healthcare industry’s data-sharing puzzle. Semantic Interoperability is the ideal state where the meaning of data can be effectively shared between systems despite the numerous ways the data may be represented in any individual system [1, 2].

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