Evidence map›Paper›PMID 41657753›Full record

ArticleJournal of clinical and translational science2026

An open-source application for self-service, Health Insurance and Portability Accountability Act-compliant geocoding.

Harpreet Gill, Kevin Power, Catherine Jackson, Jared Johnson, Matthew Llewelyn, Kushal Vallambhatla, Natalie Kane, Jeffrey Thompson, Kelechi Anuforo, Cole Brokamp and 1 more

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Harpreet GillResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Kevin PowerResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Catherine JacksonResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Jared JohnsonResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Matthew LlewelynResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Kushal VallambhatlaResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Natalie KaneResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.
Jeffrey ThompsonThe University of Kansas Medical Center, Kansas City, KS, USA.
Kelechi AnuforoThe University of Kansas Medical Center, Kansas City, KS, USA.
Cole BrokampDepartment of Pediatrics, The University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Mark HoffmanResearch Informatics, Children's Mercy Kansas City, Kansas City, MO, USA.ORCID https://orcid.org/0000-0003-3140-6524

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: DeGAUSS is a privacy-preserving application that ingests addresses and generates output that includes latitude, longitude, census tract, deprivation index and drive times to major hospitals. The application uses a complex command line interface and a container management platform to perform analysis. Our objective was to develop a user-friendly DeGAUSS-based application that simplifies place-based analysis. We also enabled automated geomarker generation by providing an API modality to DeGAUSS. Methods: We developed a self-service platform based on the DeGAUSS application. The application was linked to user authentication platforms. The self-service application can be implemented as an API, enabling high-volume geocoding transactions. We surveyed active users for feedback. Results: The self-service geomarker application was deployed at Children's Mercy and the University of Kansas Medical Center. During the period evaluated, more than 2 million addresses were geocoded for 24 users through the user interface and more than 15 million addresses through the API. Users expressed high satisfaction with the system. All respondents used the census block group feature and the core geocoding. Most respondents, 60%, used the deprivation index and 30% used the drive time feature. Population health and social determinants of health were the most common uses (80% each) followed by health equity analyses (70%). Conclusion: Population health and social determinants of health research require access to precise geographic information about patients or research subjects. The self-service geomarker capability enables users who may not be comfortable with a command line interface to generate geocoded addresses in support of their research and analysis.

Indexed as

Geocodingsocial determinants of healthsoftwarespatial analysis

Identifiers

PMID41657753
PMCPMC12873486

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.