Geospatial functionality in Atlas: integration of Aegis
Authors: Gowtham Rao, Seng Chan You, Jaehyeong Cho, Andrew Williams, Robert Miller, Pavel Grafkin, Gregory Klebanov
Motivation: During the 2018 OHDSI Symposium, Washington DC USA - J Cho, SC You, K Kim, Y Soh, D Kim, RW Park - presented a software demonstration called 'Application for Epidemiological Geographic Information System (AEGIS) - An open
source spatial analysis tool based on CDM' . See AEGIS under related work.
AEGIS, was built to support 5.x version of the OMOP CDM. This version did not have latitude and longitude in location table. AEGIS developers used observation and fact_relationship table to design AEGIS using CDM 5.x. The OMOP CDM 6+ (released October 2018) has two location tables (location and location_history). The location table has fields for latitude and longitude. These new fields may be used to represent precise location of persons, providers or care_sites.
During the presentation, a decision was made to upgrade AEGIS to support CDM 6.x with new location table, and to evaluate if it was possible to integrate AEGIS like functionality, and the work of the OHDSI GIS workgroup into ATLAS.
Background: Spatial epidemiology is the description, analysis or surveillance of a populations health related factors such as medical service, diseases, in relation to other person level or area level factors like demographic, environmental exposure, behavioral determinants, socio-economic indicators, genetic and infectious risk factors. Two types of spatial epidemiology are discussed below.
Descriptive mapping, widely used in spatial epidemiology, is useful for establishing initial hypotheses about the patterns of incidence/prevalence in an area, or the correlation between exposure to specific factors and disease.
Cluster detection is a more advanced statistical method that may reveal geographic clusters, based on patterns and spatial correlation.
AEGIS is described here
Geospatial functionality in Atlas: integration of Aegis
Authors: Gowtham Rao, Seng Chan You, Jaehyeong Cho, Andrew Williams, Robert Miller, Pavel Grafkin, Gregory Klebanov
Motivation: During the 2018 OHDSI Symposium, Washington DC USA - J Cho, SC You, K Kim, Y Soh, D Kim, RW Park - presented a software demonstration called 'Application for Epidemiological Geographic Information System (AEGIS) - An open
source spatial analysis tool based on CDM' . See AEGIS under related work.
AEGIS, was built to support 5.x version of the OMOP CDM. This version did not have latitude and longitude in location table. AEGIS developers used observation and fact_relationship table to design AEGIS using CDM 5.x. The OMOP CDM 6+ (released October 2018) has two location tables (location and location_history). The location table has fields for latitude and longitude. These new fields may be used to represent precise location of persons, providers or care_sites.
During the presentation, a decision was made to upgrade AEGIS to support CDM 6.x with new location table, and to evaluate if it was possible to integrate AEGIS like functionality, and the work of the OHDSI GIS workgroup into ATLAS.
Background: Spatial epidemiology is the description, analysis or surveillance of a populations health related factors such as medical service, diseases, in relation to other person level or area level factors like demographic, environmental exposure, behavioral determinants, socio-economic indicators, genetic and infectious risk factors. Two types of spatial epidemiology are discussed below.
Descriptive mapping, widely used in spatial epidemiology, is useful for establishing initial hypotheses about the patterns of incidence/prevalence in an area, or the correlation between exposure to specific factors and disease.
Cluster detection is a more advanced statistical method that may reveal geographic clusters, based on patterns and spatial correlation.
AEGIS is described here