ezADI

ezADI simplifies linking large health datasets to the Area Deprivation Index (ADI) by performing batched geocoder mapping on inputted addresses, constructing Federal Information Processing Series (FIPS) codes, and merging these data with ADI scores.

Key Features:

• Batched Geocoder Mapping: Performs geocoding on inputted addresses in batches to enable efficient processing of large health datasets.
• FIPS Code Construction: Constructs Federal Information Processing Series (FIPS) codes from geocoded address data.
• ADI Score Merging: Merges geocoded data with Area Deprivation Index (ADI) scores to facilitate social determinants of health (SDOH) analysis.

Scientific Applications:

• SDOH and Health Outcome Association Studies: Enables assessment of associations between neighborhood-level social determinants of health and health outcomes, as demonstrated in a study of 1,105 individuals with sickle cell disease (SCD) in Tennessee showing significant associations between higher ADI scores and increased hospital utilization (rho = 0.093, p = 0.002) and longer lengths of stay (rho = 0.069, p = 0.021).
• Retrospective Medical Record Linkage: Facilitates linking retrospective clinical datasets to external SDOH datasets when social determinants variables are not collected in routine clinical practice.
• Neighborhood-Level Intervention Targeting: Identifies areas with high neighborhood disadvantage that could be targeted with interventions and resources to improve SDOH.

Methodology:

The R package performs batched geocoder mapping on inputted addresses, constructs Federal Information Processing Series (FIPS) codes, and merges these data with ADI scores.