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Abstract
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Proceedings of the 14th World Conference on Injury Prevention and Safety Promotion (Safety 2022)
Background Few injury data sources contain information spanning the pre-to-post-injury period, inhibiting research on underlying risk factors for and long-term outcomes of injuries. We developed the NJ-SHO warehouse--a unique and comprehensive data source that integrates state-level administrative databases to support critical, high-priority research in injury prevention.
Methods We obtained full identifiable data from seven administrative databases from the US state of New Jersey: (1) driver licensing; (2) traffic citations; (3) traffic crashes; (4) birth certificates; (5) death certificates; (6) hospital discharges (emergency department, inpatient, outpatient); and (7) emergency medical services, as well as (8) health records from 200K children who were patients of the Children's Hospital of Philadelphia network and (9) census tract-level indicators. We iteratively executed a probabilistic linkage using LinkSolv 9.0 (2004-2019) and evaluated the quality of the linkage process.
Results The NJ-SHO includes 82.8M records for 20.3M NJ residents. We will discuss (1) development of the NJ-SHO and our approach to intentionally structure the warehouse so it contains rich individual-level childhood data spanning the pre-to-post-injury period for leading injury mechanisms (e.g., crashes, poisonings, firearms, self-injurious behaviors); (2) linkage evaluation results; (3) several unique features of the warehouse--including determination of race/ethnicity, addresses geocoding, coding injury severity, and identification of multiple events for an individual (e.g., hospitalizations); and (4) potential uses of 'big data' sources such as the NJ-SHO.
Conclusions The NJ-SHO warehouse is one of the most comprehensive and rich injury data warehouses to date. It is primed to support collaborative studies on high-priority injury topics.
Language: en |