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Structured vs. Unstructured Data Migration Across EHRs

By Jose Horta

Accessibility is King in Data

data key

These days consumers are accustomed to accessing their photos, books, music and movies from a variety of devices both at home and on-the-go. It’s very easy for someone to download a new e-book from their laptop, begin reading on an e-reader, pick up where they left off on their smartphone during their lunch and seamlessly switch back to their e-reader.

As hospitals acquire small family practices and large health systems take shape, being able to transfer data from Point A to Point B is a matter of life and death. Large scale data migration has always been a challenge, but it has become particularly important over the past decade with the switch to electronic health records (EHRs).

Data migration has traditionally been done using a structured approach with HL7 messaging employing an interface setup with an “old” system to deliver information to a new system. This technique has been used for many years simply because it works. Unfortunately, incomplete records are inevitable if doctors do not leave their notes in the proper designated fields. Finding those free text fields in a system and extracting the pertinent data can be a very time consuming and expensive process using HL7.

An unstructured approach to data migration is drastically changing the dynamic of accessibility. This method allows users to access data, regardless of which field it was entered. Unstructured migration allows users to pull a vast amount of data without the constraints of HL7-messaging and create reports in the same day, which cannot happen with a structured approach.

Creating a direct link between data and innovation eliminates the need for developing specific HL7-messaging queries, which saves time and money.

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by Jose Horta

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