Quality of automatic geocoding tools: a study using addresses from hospital record files in Temuco, Chile

• Autor(a) principal: Maria Elisa Quinteros
• Data de Publicação: 2022
• Outros Autores: Carola Blazquez, Felipe Rosas, Salvador Ayala, Ximena Marcela Ossa García, Juana Maria Delgado-Saborit, Roy M. Harrison, Pablo Ruiz-Rudolph, Karla Yohannessen
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Cadernos de Saúde Pública
• Texto Completo: https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/8030
• topic: Geographic Mapping; Residence Characteristics; Spatial Analysis; Mapeamento Geográfico; Características de Residência; Análise Espacial; Mapeo Geográfico; Características de la Residencia; Análisis Espacial

Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America.