Related Experiment Video
Updated: Jan 24, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Imputing race and ethnic information in administrative health data
Yishu Xue1, Ofer Harel1, Robert H Aseltine2
1Department of Statistics, University of Connecticut, Storrs, Connecticut.
Objective:
To improve on existing methods to infer race/ethnicity in health care data through an analysis of birth records from Connecticut.
Data Source:
A total of 162 467 Connecticut birth records from 2009 to 2013.
Study Design:
We developed a logistic model to predict race/ethnicity using data from US Census and patient-level information. Model performance was tested and compared to previous studies. Five performance measures were used for comparison.
Principal Findings:
Our full model correctly classifies 81 percent of subjects and shows improvement over extant methods. We achieved substantially improved sensitivity in predicting black race.
Conclusions:
Predictive models using Census information and patients' demographic characteristics can be used to accurately populate race/ethnicity information in health care databases, enhancing opportunities to investigate and address disparities in access to, utilization of, and outcomes of care.
More Related Videos
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
11:48A Contrast of Three Inoculation Techniques used to Determine the Race of Unknown Fusarium oxysporum f.sp. niveum Isolates
Published on: October 28, 2021
Related Concept Videos
Ethnic Identity within a Larger Culture
RACE - Rapid Amplification of cDNA Ends
Data Reporting and Recording
Health Literacy
Health Information Technology and Healthcare Information System
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Concepts of Health and Illness