Advancing Maryland's Statewide Suicide Data Warehouse to Improve Individual and Population-level Mortality Prediction and Prevention

项目概要 2018年，NIMH资助了马里兰州自杀数据仓库（MSDW）的开发。开发MSDW的目的 是将一组不同的数据源联系起来，并使用不同层次的风险因素来预测自杀死亡。 人口目前，MSDW包括2012年至2017年约500多万马里兰州居民的数据。MSDW包含 医院和急诊出院、健康信息交换（HIE）数据、商业保险索赔、体检医师 数据、来自5个选定卫生系统的电子健康记录（EHR）数据以及基于地点的健康数据社会决定因素 涵盖住房、就业、教育、收入和犯罪等各个领域。 这项研究将利用MSDW链接的独特数据类型来改善可推广的自杀死亡预测。 患者人群。我们提出的研究将进一步扩展基础数据，并开发 MSDW。本研究的主要目的是：（1）从现有的MSDW数据源中获取更新的数据; (2)使用MSDW中存储的大量数据源来推进自杀死亡率的预测，同时控制 数据质量和潜在的模型偏差;（3）探索MSDW的各种用例，例如自杀的无监督聚类 死亡病例;（4）与外部研究人员合作，验证MSDW衍生的自杀预测模型 死亡

❖ PROJECT SUMMARY In 2018, NIMH funded the development of the Maryland Suicide Data Warehouse (MSDW). The aim of developing MSDW was to link a diverse set of data sources and use various layers of risk factors to predict suicide death on a generalizable population. Currently, MSDW includes data on ~5+ million Maryland residents spanning from 2012 to 2017. MSDW contains hospital and emergency discharges, health information exchange (HIE) data, commercial insurance claims, medical examiner data, electronic health record (EHR) data from 5 select health systems, and place-based social determinants of health data covering various domains such as housing, employment, education, income and crime. This study will leverage the unique data types linked by MSDW to improve suicide death predictions among generalizable patient populations. Our proposed study will further expand the underlying data and develop cutting-edge use cases of MSDW. The study aims to achieve a number of outcomes: (1) Acquire refreshed data from all existing MSDW data sources; (2) Use the wide array of data sources stored in MSDW to advance the prediction of suicide mortality, while controlling for data quality and potential model bias; (3) Explore various uses cases of the MSDW such as unsupervised clustering of suicide mortality cases; and, (4) Collaborate with external investigators to validate the MSDW-derived predictive models of suicide death.