Download PDF
Appl Clin Inform 2023; 14(05): 833-842
DOI: 10.1055/a-2148-6414
Research Article

POINT: Pipeline for Offline Conversion and Integration of Geocodes and Neighborhood Data

Kevin Guo
1   School of Medicine, Vanderbilt University, Nashville, Tennessee, United States
,
Allison B. McCoy
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Thomas J. Reese
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Adam Wright
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Samuel Trent Rosenbloom
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Siru Liu
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Elise M. Russo
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Bryan D. Steitz
2   Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
› Author Affiliations Funding This work was funded by the National Institute on Aging (grant no.: R01AG062499).
› Further Information
Also available at
   Permissions and Reprints

Abstract

Objectives Geocoding, the process of converting addresses into precise geographic coordinates, allows researchers and health systems to obtain neighborhood-level estimates of social determinants of health. This information supports opportunities to personalize care and interventions for individual patients based on the environments where they live. We developed an integrated offline geocoding pipeline to streamline the process of obtaining address-based variables, which can be integrated into existing data processing pipelines.

Methods POINT is a web-based, containerized, application for geocoding addresses that can be deployed offline and made available to multiple users across an organization. Our application supports use through both a graphical user interface and application programming interface to query geographic variables, by census tract, without exposing sensitive patient data. We evaluated our application's performance using two datasets: one consisting of 1 million nationally representative addresses sampled from Open Addresses, and the other consisting of 3,096 previously geocoded patient addresses.

Results A total of 99.4 and 99.8% of addresses in the Open Addresses and patient addresses datasets, respectively, were geocoded successfully. Census tract assignment was concordant with reference in greater than 90% of addresses for both datasets. Among successful geocodes, median (interquartile range) distances from reference coordinates were 52.5 (26.5–119.4) and 14.5 (10.9–24.6) m for the two datasets.

Conclusion POINT successfully geocodes more addresses and yields similar accuracy to existing solutions, including the U.S. Census Bureau's official geocoder. Addresses are considered protected health information and cannot be shared with common online geocoding services. POINT is an offline solution that enables scalability to multiple users and integrates downstream mapping to neighborhood-level variables with a pipeline that allows users to incorporate additional datasets as they become available. As health systems and researchers continue to explore and improve health equity, it is essential to quickly and accurately obtain neighborhood variables in a Health Insurance Portability and Accountability Act (HIPAA)-compliant way.

Keywords

social determinants of health - geographic mapping - census tract - personalized medicine

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by VUMC Institutional Review Board.


Supplementary Material



Publication History

Received: 02 May 2023

Accepted: 03 August 2023

Accepted Manuscript online:
04 August 2023

Article published online:
18 October 2023

© 2023. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany