Can Claims-Based Data Be Used to Recruit Black and Hispanic Subjects into Clinical Trials?

Objective Evaluate the accuracy of an algorithm at identifying ethnic minorities from administrative claims for enrollment into a clinical trial. Data Sources/Study Setting Claims data from a health benefits company. Study Design We compared results of a three‐step algorithm to self‐reported race/et...

Full description

Saved in:
Bibliographic Details
Published inHealth services research Vol. 47; no. 2; pp. 770 - 782
Main Authors Palacio, Ana M., Tamariz, Leonardo J., Uribe, Claudia, Li, Hua, Salkeld, Ellen J., Hazel-Fernandez, Leslie, Carrasquillo, Olveen
Format Journal Article
LanguageEnglish
Published United States Blackwell Publishing Ltd 01.04.2012
Health Research and Educational Trust
Blackwell Science Inc
Subjects
Online AccessGet full text
ISSN0017-9124
1475-6773
1475-6773
DOI10.1111/j.1475-6773.2011.01316.x

Cover

More Information
Summary:Objective Evaluate the accuracy of an algorithm at identifying ethnic minorities from administrative claims for enrollment into a clinical trial. Data Sources/Study Setting Claims data from a health benefits company. Study Design We compared results of a three‐step algorithm to self‐reported race/ethnicity. Data Collection/Extraction Methods Using the algorithm, we identified subjects with high probability of being minority and ascertained self‐reported race/ethnicity. Principal Findings We identified 164 subjects as likely minority based on our algorithm. Of these, 94 completed the survey and 87 identified themselves as black or Hispanic. The positive predictive value of the algorithm was 93 percent (CI: 85–97). Conclusions Claims data can be used to efficiently identify minorities for participation in clinical trials.
Bibliography:Appendix SA1: Author Matrix.
National Institute on Minority Health and Health Disparities/NIH - No. RC1MD004327
istex:1F008ED45B07E1EF4972862FB71C8E81C2D2ACA6
ArticleID:HESR1316
ark:/67375/WNG-L8DSPFNZ-7
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0017-9124
1475-6773
1475-6773
DOI:10.1111/j.1475-6773.2011.01316.x