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Evaluating external validity in randomized controlled trials (RCTs) is crucial for reducing health disparities. This study used geographic information systems to show RCT participants were often oversampled in high-diabetes density areas, highlighting location as a key factor.

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Area of Science:

  • Health Services Research
  • Epidemiology
  • Biostatistics

Background:

  • Assessing the external validity of randomized controlled trials (RCTs) is essential for their translational impact in reducing health disparities.
  • Traditional methods for post hoc external validity assessment are limited, especially when probabilistic sampling is not used.
  • A Type 2 diabetes RCT was utilized to demonstrate a novel methodology for evaluating external validity.

Purpose of the Study:

  • To introduce and evaluate a geographic information system (GIS) based method for assessing the external validity of RCTs.
  • To determine if RCT participants are representative of the broader community, particularly in relation to health disparities.
  • To establish location as a proxy for high-risk populations in evaluating RCT generalizability.

Main Methods:

  • Utilized a geographic information system (GIS) combined with county death certificate records (2009-2013) and electronic medical records (2013-2014) to map community-wide diabetes prevalence.
  • Employed chi-square goodness of fit tests to compare the distribution of RCT participants across diabetes density areas against a simple random sampling model.
  • Visualized diabetes prevalence using color-coded density maps.

Main Results:

  • Diabetes prevalence, identified through both death certificates and electronic medical records, showed similar spatial distributions.
  • The simple random sample model did not adequately represent the distribution of diabetes prevalence in the population (p<0.0001 for both data sources).
  • RCT participants were found to be disproportionately oversampled in areas with higher diabetes density.

Conclusions:

  • Geographic location is a reliable indicator strongly associated with health disparities.
  • Location serves as a practical and measurable proxy for identifying high-risk, underserved communities.
  • The GIS-based approach provides an effective method for examining the external validity of RCTs in the context of health disparities.