Geographic Information Systems to Assess External Validity in Randomized Trials

Margaret R. Savoca, David Ludwig, Stedman T. Jones, K. Jason Clodfelter, Joseph B. Sloop, Linda Y. Bollhalter, Alain G. Bertoni

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Introduction: To support claims that RCTs can reduce health disparities (i.e., are translational), it is imperative that methodologies exist to evaluate the tenability of external validity in RCTs when probabilistic sampling of participants is not employed. Typically, attempts at establishing post hoc external validity are limited to a few comparisons across convenience variables, which must be available in both sample and population. A Type 2 diabetes RCT was used as an example of a method that uses a geographic information system to assess external validity in the absence of a priori probabilistic community-wide diabetes risk sampling strategy. Methods: A geographic information system, 2009-2013 county death certificate records, and 2013-2014 electronic medical records were used to identify community-wide diabetes prevalence. Color-coded diabetes density maps provided visual representation of these densities. Chi-square goodness of fit statistic/analysis tested the degree to which distribution of RCT participants varied across density classes compared to what would be expected, given simple random sampling of the county population. Analyses were conducted in 2016. Results: Diabetes prevalence areas as represented by death certificate and electronic medical records were distributed similarly. The simple random sample model was not a good fit for death certificate record (chi-square, 17.63; p=0.0001) and electronic medical record data (chi-square, 28.92; p<0.0001). Generally, RCT participants were oversampled in high-diabetes density areas. Conclusions: Location is a highly reliable "principal variable" associated with health disparities. It serves as a directly measurable proxy for high-risk underserved communities, thus offering an effective and practical approach for examining external validity of RCTs.

Original languageEnglish (US)
JournalAmerican Journal of Preventive Medicine
DOIs
StateAccepted/In press - 2017

Fingerprint

Geographic Information Systems
Death Certificates
Electronic Health Records
Health
Proxy
Type 2 Diabetes Mellitus
Population
Color

ASJC Scopus subject areas

  • Epidemiology
  • Public Health, Environmental and Occupational Health

Cite this

Savoca, M. R., Ludwig, D., Jones, S. T., Jason Clodfelter, K., Sloop, J. B., Bollhalter, L. Y., & Bertoni, A. G. (Accepted/In press). Geographic Information Systems to Assess External Validity in Randomized Trials. American Journal of Preventive Medicine. https://doi.org/10.1016/j.amepre.2017.01.001

Geographic Information Systems to Assess External Validity in Randomized Trials. / Savoca, Margaret R.; Ludwig, David; Jones, Stedman T.; Jason Clodfelter, K.; Sloop, Joseph B.; Bollhalter, Linda Y.; Bertoni, Alain G.

In: American Journal of Preventive Medicine, 2017.

Research output: Contribution to journalArticle

Savoca, Margaret R. ; Ludwig, David ; Jones, Stedman T. ; Jason Clodfelter, K. ; Sloop, Joseph B. ; Bollhalter, Linda Y. ; Bertoni, Alain G. / Geographic Information Systems to Assess External Validity in Randomized Trials. In: American Journal of Preventive Medicine. 2017.
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