Athena: OHDSI database for OMOP codes

When you look through a person’s electronic health record (EHR), you will notice it contains different codes that document various aspects of a person’s health care including diagnosed medical conditions, procedures undergone, drugs prescribed, etc. Each code is part of a medical “vocabulary.” One complication health care researchers can run into is that there are multiple classification systems used to code these different aspects of health care, each with its own unique vocabulary. You may even see multiple classification systems used within one person’s EHR. For example, the condition type 2 diabetes may be recorded as ICD-9 code 250.00 at one doctor’s office or ICD-10 code E11 at another.

When All of Us receives a participant’s EHR, all of the codes (called “source codes”) are re-assigned a standard vocabulary code. For type 2 diabetes, this might be SNOMED 44054006. By changing, or mapping, all of the source codes to standard codes, the EHR can be more easily categorized and searched by researchers. However, all of the source codes are retained after being re-assigned a standard code so that data can still be searched for using the original codes.

Athena is a searchable database maintained by the Observational Health Data Sciences and Informatics (OHDSI) that is available to researchers to help identify codes and match them to their standard Observational Medical Outcomes Partnership (OMOP) equivalent. Within Athena, a researcher can search for a condition of interest (e.g., gestational diabetes) and find its Domain ID, Concept IDs for related concepts (e.g., gestational diabetes mellitus), and a visual hierarchy showing ancestors (e.g., diabetes mellitus during pregnancy) and descendants (e.g., postpartum gestational diabetes).  If you are interested in learning more, OHDSI has a video tutorial about Athena found here: https://www.youtube.com/watch?v=2WdwBASZYLk 

(Additional Source: https://ohdsi.github.io/TheBookOfOhdsi/StandardizedVocabularies.html)

 

Please review our All of Us Research Program Data Access Framework for further information.

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