Conceptualization and development of the Maryland suicide data warehouse to improve mortality prediction.

Objectives: Research in suicide risk prediction often suffers from the lack of comprehensive data on patient suicide death, which differs from suicide attempt or suicidal behaviors. This study aimed to develop a population-wide multi-source harmonized data warehouse suitable for suicide death risk prediction. Materials and Methods: The Maryland Suicide Data Warehouse (MSDW) was conceived as a statewide database that addresses limitations in prior suicide research. To develop MSDW, multiple patient-level statewide data sources were linked using the statewide health information exchange infrastructure. Manner of death, the standard outcome in suicide death research, was determined by the state medical examiner. Health services data were linked from multiple data sources such as electronic health records, hospital discharge data, and administrative insurance claims. Data were structured as a common format that preserves observations at their lowest level of analysis. Data features were included based on known or hypothesized psychiatric or suicide risk factors. Results: The warehouse contains a mix of records across data sources for patient diagnoses, clinical encounters, procedures, area of residence, pharmacy fills and laboratory findings. MSDW represents 104,517 decedents reported by the OCME between 2012 and 2020, 5,059 classified as suicides. Conclusions: The MSDW is a statewide data warehouse that allows users to conduct population health research, predictive modeling and observational studies for multiple outcomes. It has multiple overlapping clinical records that improve the completeness and timeliness of data. It is a high-quality statewide data warehouse for conducting suicide prediction research and assessing risk for surveillance and intervention.