title: Geography and geographic information systems in family medicine research.
abstract: Understanding spatial relationships between determinants and outcomes of health care is important as the concept of population-based health care gains acceptance. A wide range of tools for understanding these spatial relationships is available to the family medicine researcher through the use of Geographic Information Systems (GIS). The power of GIS lies in its ability to display the spatial distribution of a health-related predictor or outcome. These maps can then be used to either generate or test hypotheses that would not have otherwise occurred to the investigator without visualizing the spatial relationships. The type of GIS application used is dependent on the type of data the researcher has and the research question. The three most common types of data are point or event data, lattice data, and geostatistical data. Point or event data can be displayed using a technique known as geocoding. Lattice data is most commonly displayed as shaded or colored areas where the shading represents rates or counts. Geostatistical data provides counts or numbers at a given location. The analytic techniques used for analyzing spatial data depend on the type of data. Maps tell powerful stories and display relationships that may not be obvious using other techniques.
authors.affiliation: Department of Family and Community Medicine, University of Texas Health Sciences Center-San Antonio, 78229-3900, USA. parchman@uthscsa.edu
authors.forename: Michael L
authors.initials: ML
authors.lastname: Parchman
authors.forename: Robert L
authors.initials: RL
authors.lastname: Ferrer
authors.forename: K Stephen
authors.initials: KS
authors.lastname: Blanchard
mesh_terms: D004781:Environmental Exposure / Q000032:analysis; D004812:Epidemiologic Methods; D005194:Family Practice; D005260:Female; D005317:Fetal Growth Retardation / Q000453:epidemiology; D006801:Humans; D007256:Information Systems; D020407:Internet; D008377:Maps as Topic; D011247:Pregnancy; D012107:Research Design; D019371:Topography, Medical; D014481:United States / Q000453:epidemiology