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464 Catalyzing advancements in injury prevention research: development of a statewide data warehouse
  1. Allison Curry1,2,
  2. Melissa Pfeiffer1,
  3. Kristina Metzger1,
  4. Lawrence Cook3
  1. 1Children’s Hospital of Philadelphia, Philadelphia, USA
  2. 2University of Pennsylvania, Philadelphia, USA
  3. 3University of Utah, Salt Lake City, USA


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.

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