AIM-AHEAD Year 4 Research Fellowship - Project 2187 Dataset

Project Title: Causal ML for Syndemic Risk Quantification & Impact Forecasting Project Awardee: Ebele Mogo This dataset is derived from OCHIN Community Health Database - AIM-AHEAD Year 4 and implemented as a set of views. It includes adults aged 18 and older with at least one ambulatory or telehealth visit between 2015 and 2024, focusing on patients with co‑occurring cardiometabolic conditions including diabetes, hypertension, and obesity. The dataset include patient demographics (sex, age, race, ethnicity, language, payer, federal poverty level, ZIP/ZCTA, and homelessness status), visit‑level data, provider and care site characteristics, vital signs (blood pressure, BMI, height, weight), condition diagnoses (cardiometabolic, mental and behavioral health, and selected Z‑codes), laboratory results (HbA1c and lipid panels), medication exposures (antidiabetic, antihypertensive, and cardiovascular agents), procedures related to cardiometabolic care and behavioral health, and comprehensive patient screening data capturing social and behavioral drivers of health. If you are interested in learning more about this dataset and understanding access requirements, we recommend you reach out to the named Project Awardee and/or OCHIN at AI-DataConsult[at]ochin.org