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.
(PUBLIC HEALTH RELEVANCE) Suicide is a major preventable public health challenge. Close to 48,000 people in the United States died by suicide in 2017 and rates have increased 33% since 1999. This study will utilize a data warehouse developed in Maryland to improve suicide risk identification and prevention.
