Project

Residential Mobility in Electronic Health Records

Active

Electronic health records contain longitudinal patient address histories, a largely untapped, population-scale data source for studying residential mobility and spatial health inequity.

Jan 1, 2024

Health systems collect patient addresses as a routine byproduct of clinical care, updating them at every visit. In collaboration with Barbara Entwisle at the Carolina Population Center, this project asks what that administrative record can tell us about how people actually move.

Two papers are in preparation. The first examines the stability and instability of patient address records across a large clinical population over time, characterizing what address changes in EHR data represent and under what conditions they proxy true residential moves. The second evaluates EHR-derived address histories as a new source of data on residential mobility, benchmarking them against traditional survey-based approaches. Both are targeted for Demography. This work was presented at the Population Association of America Annual Meeting, Washington, DC (2025).

Related Publications

Geographically Skewed Recruitment and COVID-19 Seroprevalence Estimates: A Cross-Sectional Serosurveillance Study and Mathematical Modelling Analysis

BMJ Open

Tyler Brown, Pablo Martinez de Salazar Munoz, Abhishek Bhatia, Bridget Bunda, Ellen K. Williams, David Bor, James S. Miller, Amir Mohareb, Julia Thierauf, Wenxin Yang, Julian Villalba, Vivek Naranbai, Wilfredo Garcia Beltran, Tyler E. Miller, Doug Kress, Kristen Stelljes, Keith Johnson, Dan Larremore, Jochen Lennerz, A. John Iafrate, Satchit Balsari, Caroline Buckee, Yonatan Grad

Objectives Convenience sampling is an imperfect but important tool for seroprevalence studies. For COVID-19, local geographic variation in cases or vaccination can confound studies …

Jan 2023 · PDF · Project

Reengineering a Machine Learning Phenotype to Adapt to the Changing COVID-19 Landscape: A Study from the N3C and RECOVER Consortia

medRxiv

Miles Crosskey, Tomas McIntee, Sandy Preiss, Daniel Brannock, Yun Jae Yoo, Emily Hadley, Frank Blancero, Rob Chew, Johanna Loomba, Abhishek Bhatia, Christopher G. Chute, Melissa Haendel, Richard Moffitt, Emily Pfaff, N3c Consortium, the RECOVER EHR Cohort

Background In 2021, we used the National COVID Cohort Collaborative (N3C) as part of the NIH RECOVER Initiative to develop a machine learning (ML) pipeline to identify patients …

Jan 2023 · PDF · Project

Identifying Who Has Long COVID in the USA: A Machine Learning Approach Using N3C Data

The Lancet Digital Health

Emily R. Pfaff, Andrew T. Girvin, Tellen D. Bennett, Abhishek Bhatia, Ian M. Brooks, Rachel R. Deer, Jonathan P. Dekermanjian, Sarah Elizabeth Jolley, Michael G. Kahn, Kristin Kostka, Julie A. McMurry, Richard Moffitt, Anita Walden, Christopher G. Chute, Melissa A. Haendel, Carolyn Bramante, David Dorr, Michele Morris, Ann M. Parker, Hythem Sidky, Ken Gersing, Stephanie Hong, Emily Niehaus

Jan 2022 · PDF · Project

Regulatory Sandboxes: A Cure for mHealth Pilotitis?

Journal of Medical Internet Research

Abhishek Bhatia, Rahul Matthan, Tarun Khanna, Satchit Balsari

Mobile health (mHealth) and related digital health interventions in the past decade have not always scaled globally as anticipated earlier despite large investments by governments …

Jan 2020 · PDF · Project