AI-READI
Published 2026 | Version v1
Poster Open

Standardizing Survey, Vision Care, and Cognitive Assessment Data Generalizable Framework for Mapping Research Questionnaires to the OMOP Common Data Model

Description

The AIREADI project aims to generate high-quality, ethically sourced data from 4,000 participants of diverse backgrounds across the spectrum of type 2 diabetes mellitus. The dataset consists of 47 survey instruments that capture clinical information, behavioral elements, social determinants of health, and many other data points related to participants' health status and factors influencing their disease outcomes. The heterogeneity of data sources limits interoperability. We developed a reproducible framework for harmonizing survey instruments into the Observational Medical Outcomes Partnership (OMOP) Common Data Model for the AIREADI study.

Abstract

The AIREADI project aims to generate high-quality, ethically sourced data from 4,000 participants of diverse backgrounds across the spectrum of type 2 diabetes mellitus. The dataset consists of 47 survey instruments that capture clinical information, behavioral elements, social determinants of health, and many other data points related to participants' health status and factors influencing their disease outcomes. The heterogeneity of data sources limits interoperability. We developed a reproducible framework for harmonizing survey instruments into the Observational Medical Outcomes Partnerships (OMOP) Common Data Model for the AIREADI study.

Files

Hong_AMIA_Poster_Standardizing_Survey__Vision_Care__and_Cognitive_Assessment_Data_for_AI-READI_Research.pdf

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Additional details

Related works

Is described by
Other: https://posters.science/discover/24356 (URL)

Funding

National Institutes of Health
Bridge2AI:Salutogenesis Data Generation Project 7OT2OD032644-02

Dates

Submitted
2026-07-29
Submitted to Zenodo through Posters.science
Other
2024-10-23
Poster presentation date