Geocoding for public health research: Empirical comparison of two geocoding services applied to Canadian cities

Abstract

The process of geocoding, particularly the street address matching process, is a commonly used technique to obtain locational information for public health research. In health care accessibility research, geocoded locations of health care providers are an essential element for measuring potential access to health care. Our objective is to compare the geocoding match rates and positional variation of two geocoding procedures by using street network and postal code datasets to geocode primary health care services in 14 cities. The first procedure uses a manually built geocoding service using DMTI Spatial (DMTI) reference datasets while the second employs an online geocoding service provided as a built-in tool in ArcGIS, with ESRI Tele Atlas reference datasets. Results for Tele Atlas postal code and DMTI multiple enhanced postal codes (MEP) reference datasets produce much higher match rates (99.4%; 98.0% respectively) than street reference datsasets; while results of Tele Atlas street dataset produce better match rates (96.5%) than the DMTI street dataset (90.0%). Geocoding methods using Tele Atlas and DMTI Street datasets produce more accurate locations than postal code and MEP reference datasets. Empirical comparison of the geocoding results based on manually built and online geocoding services highlight the need for integrated geocoding procedures for increasing match rates with reduced positional uncertainty.