USING GEOGRAPHICAL INFORMATION SYSTEMS (GIS) FOR TARGETING RECRUITMENT IN DEMENTIA STUDIES

• Published in: Innovation in aging Vol. 1; no. suppl_1; p. 520
• Main Authors: Scerpella, D.L., Marx, K.A., Burke, K., Gitlin, L.N.
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 01.07.2017
• Subjects: Abstracts
• ISSN: 2399-5300; 2399-5300
• DOI: 10.1093/geroni/igx004.1841

Recruiting sufficient numbers of individuals with dementia and/or their family caregivers is critical for advancing effective treatments and assuring generalizability and statistical power in randomized trials. Recruitment is one of the most expensive and time consuming aspects of dementia trials. A tool that may assist in recruitment is Geographic Information Systems (GIS). GIS applications provide a technology for connecting individual’s data to their environment, allowing researchers to visually inspect the distribution of numerous variables across a location. Currently, there is no robust location data for people with dementia or their caregivers, yet existing data sets may be useful. This paper presents results of a post hoc analysis of families recruited for a randomized trial in the USA to demonstrate the power of GIS and effective use of existing data sets. Using US Census Bureau data, a grouping analysis of selected risk factors (age, education, gender, income) for dementia was performed in ArcGIS. Age alone was the most robust factor overlapping with 48% (N=165) of enrolled trial participants. However, the combination of risk factors predicted 52% of existing locations of participants. We found that by increasing the geographic area considered by one half-mile, we improved the reach to 76% of enrolled participants. By utilizing government survey data and identifying specific demographic and health risk factors associated with dementia, GIS can be used to identify localized areas in a community where these attributes are concentrated. Using this information, a more targeted recruitment approach may be possible, prospectively resulting in potential cost savings.