FHIR PIT

FHIR PIT integrates patient clinical data with public environmental exposure sources using geocodes and timestamps to produce anonymized, binned feature tables (ICEES) for individual-level spatiotemporal environmental health research.

Key Features:

• Spatiotemporal integration: Integrates clinical and environmental exposure data using geocodes and timestamps at variable temporal resolutions (e.g., hourly to yearly).
• PHI anonymization: Removes personally identifiable information (PHI), including geocodes and timestamps, to anonymize datasets.
• Feature binning and ICEES output: Processes integrated data into binned feature variables and produces ICEES (Integrated Clinical and Environmental Exposures Service) tables for downstream analysis.
• Modular transformation pipeline: Implements a series of transformation steps or building blocks that can be linked into customizable workflows to accommodate new data types.
• Individual-level correlation: Enables correlation of environmental factors with clinical outcomes at the individual level.

Scientific Applications:

• Environmental exposure–health association studies: Supports studies linking environmental exposures to health outcomes at the individual level.
• Individual-level determinants of health: Facilitates analyses of individual-level determinants of health and disease using integrated spatiotemporal datasets.
• Airborne pollutant and asthma research: Applied to study airborne pollutant exposures and their association with asthma exacerbations, including analyses of racial disparities.
• Privacy-preserving downstream analyses: Produces ICEES tables to enable privacy-preserving downstream research inquiries.

Methodology:

Integrates datasets using geocodes and timestamps (variable resolution, e.g., hourly to yearly); removes PHI including geocodes and timestamps; bins features to create ICEES tables; composes workflows from modular transformation steps or building blocks.