Data normalization: Working toward a common clinical terminology

Learn how data normalization helps unify, clean, and organize highly variable clinical terminology into useful information.
Clinical terminology and data normalization

When it comes to clinical terminology in medicine, there are a lot of ways to say the same thing – 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.

Data normalization depends on clinical terminology

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 in many different formats – from various systems – and then converting it into a singular, unified clinical language, or terminology.

However, there’s more to the puzzle. In addition to preserving information, a normalization solution – supported with a foundational layer of robust clinical terminology – can also help fill in important blanks in data with standardized codes, terms, descriptions or metadata. 

How does IMO standardize data? 

Checkout this brief video to learn more about how  IMO Precision Normalize approaches data standardization.

The benefits of normalized data

Indeed, providers and organizations require data that’s complete, specific, and reliable for future analytics needs. Data normalization not only helps ensure the volume of data from disparate sources is useful, but helps prevent a host of downstream challenges ranging from reduced reimbursement to inaccurate patient cohorts.

To learn more about IMO’s clinical terminology and comprehensive approach to data normalization:



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