AIM-AHEAD Year 4 PAIR - Project 2073 Dataset

Project Title: Better AI for a Strong Rural Maternal and Child Health Environment (BARE) Lab Project Awardee: Jill Inderstrodt This dataset is derived from the OCHIN Community Health Database – AIM‑AHEAD Year 4 and implemented as a set of views. It includes adults aged 18 and older with pregnancy‑related care and deliveries occurring between 2017 and 2020, supporting development and evaluation of a prediction model for preeclampsia using routinely captured clinical data. The dataset includes patient demographics (sex, age, race, ethnicity, language, payer, federal poverty level, and ZIP/ZCTA), visit‑level data across office, hospital, and telehealth encounters, vital signs (including blood pressure and weight/BMI), condition diagnoses used for pregnancy and outcome identification, laboratory results specified as model features, and selected patient screening variables noted as potential predictors. For additional information about this dataset and access requirements, please contact the Project Awardee and/or OCHIN at AI‑DataConsult[at]ochin.org.项目名称：优化农村妇幼健康环境的人工智能（Better AI for a Strong Rural Maternal and Child Health Environment, BARE）实验室 项目负责人：吉尔·因德斯特罗特（Jill Inderstrodt） 本数据集源自OCHIN社区健康数据库——AIM-AHEAD项目第4年数据，以视图集形式实现。数据集涵盖2017年至2020年间接受妊娠相关诊疗及分娩的18岁及以上成年人，用于支持基于常规采集的临床数据构建并评估子痫前期预测模型。 数据集包含患者人口统计学信息（性别、年龄、种族、民族、语言、支付方、联邦贫困线水平及ZIP/ZCTA编码）、门诊、住院及远程医疗就诊的就诊层面数据、生命体征（含血压与体重/体质指数（Body Mass Index, BMI））、用于妊娠及结局识别的病症诊断信息、指定为模型特征的实验室检验结果，以及被列为潜在预测因子的部分患者筛查变量。 如需了解本数据集的更多信息及获取要求，请联系项目负责人及/或OCHIN，联系方式：[e-mail]。