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Health Data Standards Support Healthcare Interoperability

Thinkstock via EHR Intelligence

The healthcare industry contains a number of different standards development organizations (SDOs) which create, define, update, and maintain health data standards through collaborative processes that involve health IT users.

SDO’s are well regarded as they promote interoperability and heightened efficiency. However, lack of widespread adoption and use lessen the effectiveness of existing standards, according to a new article at EHR Intelligence.

According to HIMSS, interoperability “describes the extent to which systems and devices can exchange data, and interpret that shared data. For two systems to be interoperable, they must be able to exchange data and subsequently present that data such that it can be understood by a user.”

The article goes on to identify three levels of interoperability: foundational, structural, and semantic.

Foundational interoperability is the ability of one IT system to send data to another IT system. The receiving IT system does not necessarily need to be able to interpret the exchanged data — it must simply be able to acknowledge receipt of the data payload. This is the most basic tier of interoperability.

Structural interoperability is “the uniform movement of healthcare data from one system to another such that the clinical or operational purpose and meaning of the data is preserved and unaltered,” HIMSS states.

To achieve structural interoperability, the recipient system should be able to interpret information at the data field level. This is the intermediate level of interoperability.

Semantic interoperability is the ability of health IT systems to exchange and interpret information — then actively use the information that has been exchanged. Semantic interoperability is the highest level of interoperability.

“Semantic interoperability takes advantage of both the structuring of the data exchange and the codification of the data including vocabulary so that the receiving information technology systems can interpret the data,” stated HIMSS.

According to the Office of the National Coordinator (ONC), “standards are agreed-upon methods for connecting systems together. Standards may pertain to security, data transport, data format or structure, or the meanings of codes or terms.”

Revenue cycle faces similar challenges. Rather than mass adoption of the standard ANSI codes, many payers utilize proprietary codes that require interpretation, leading to denied claims – which means manual adjustments and delayed payments. Additionally, in many cases, healthcare organizations are not able to utilize payment data from paper-originated remittances to feed downstream systems.

Fortunately, technologies utilizing advanced AI and Deep Learning technologies are able to electronify the paper-originated remits that are not only able be be auto-posted, but also utilized for the downstream systems.

This blog contains forward-looking statements. For more information, click here.

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