Data normalization: Working toward a common clinical terminology

When it comes to medical coding terms, there’s a lot to keep track of and a lot to keep straight. From CPT terms, to LOINC to ICD-10-CM codes, it’s hard to overstate the importance of normalization solutions that can unify, clean, and organize clinical terminology.
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There are a lot of ways to say the same thing in medicine – whether that’s by using a colloquial term (heart attack), a more clinical one (myocardial infarction), or a billing code (121.9, acute myocardial infarction, unspecified). However, when looking to glean insights from healthcare data, it’s important to make sure that all of these different variations are harmonized under one clinical term so that everyone is speaking the same language.

The solution seems simple enough – just use some sort of EHR terminology translator and the problem is solved. But when it comes to medical coding terms, translation is only part of the battle.

To end up with data that’s useable, normalization is required. Within the realm of healthcare IT, data normalization refers to the practice of taking clinical information that’s in many different formats, gathered from various systems, and converting it into a singular, unified clinical language, or terminology. However, there’s still a final piece to the puzzle. In addition to preserving the information, when we normalize health data, we also fill in important blanks – like adding on the proper standardized code to a clinical term or description – when appropriate.

The end result? Data that’s complete, specific, and reliable for future analytics needs.

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