Evidence map›Paper›PMID 32947116›Full record

ArticleInternational journal of medical informatics2020

Using sexual orientation and gender identity data in electronic health records to assess for disparities in preventive health screening services.

Chris Grasso, Hilary Goldhammer, Russell J Brown, B W Furness

Open access · greenAbstract read
In one paragraph

Article in International journal of medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 3 pooled it
5.6field-weighted citation impact, top 4% of its field
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

32 citing papers in PubMed, 3 syntheses or guidelines pooled it, 67 citations in OpenAlex.

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  4. Exploring Gender Differences in Receipt of the 5As for Smoking Cessation for Recently Diagnosed Cancer Patients (ECOG-ACRIN EAQ171CD).Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
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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

4 authors at 3 institutions in 1 country.

Chris GrassoThe Fenway Institute, Fenway Health, 1340 Boylston St., Boston, MA 02215, United States. Electronic address: cgrasso@fenwayhealth.org.
Hilary GoldhammerThe Fenway Institute, Fenway Health, 1340 Boylston St., Boston, MA 02215, United States. Electronic address: hilagoldham@gmail.com.
Russell J BrownNational Association of Community Health Centers, 7501 Wisconsin Ave., Suite 1100W, Bethesda, MD 20814, United States. Electronic address: rbrown@nachc.com.
B W FurnessCenters for Disease Control and Prevention, Division of STD Prevention, 899 North Capitol Street, NE, Fourth Floor, Washington, DC 20002, United States. Electronic address: bff0@cdc.gov.
Fenway Health · USCenters for Disease Control and Prevention · USNational Association of Community Health Centers · US

Funding

Intramural CDC HHS CC999999OSTLTS CDC HHS U38 OT000223
6 · The paper itself

Abstract

backgroundLesbian, gay, bisexual, transgender, and queer (LGBTQ) populations have an increased risk of multiple adverse health outcomes. Capturing patient data on sexual orientation and gender identity (SOGI) in the electronic health record (EHR) can enable healthcare organizations to identify inequities in the provision of preventive health screenings and other quality of care services to their LGBTQ patients. However, organizations may not be familiar with methods for analyzing and interpreting SOGI data to detect health disparities. PURPOSE: To assess an approach for using SOGI EHR data to identify potential screening disparities of LGBTQ patients within distinct healthcare organizations.

methodsFive US federally qualified health centers (FQHCs) retrospectively extracted three consecutive months of EHR patient data on SOGI and routine screening for cervical cancer, tobacco use, and clinical depression. The screening data were stratified across SOGI categories. Chi-Square and Fisher's Exact test were used to identify statistically significant differences in screening compliance across SOGI categories within each FQHC.

resultsIn all FQHCs, cervical cancer screening percentages were lower among lesbian/gay patients than among bisexual and straight/heterosexual patients. In three FQHCs, cervical cancer screening percentages were lower for transgender men than for cisgender (i.e., not transgender) women. Within each FQHC, we observed statistically significant associations (P < 0.05) between SOGI categories and at least one screening measure. The small number of transgender patients, and limitations in EHR functionality, created challenges in interpretation of SOGI data.

conclusionsTo our knowledge, this is the first published report of using SOGI data from EHRs to detect potential disparities in healthcare services to LGBTQ patients. Our finding that lesbian/gay and transgender male patients had lower cervical cancer screening rates compared to heterosexual, bisexual, and cisgender women, is consistent with the research literature and suggests that using SOGI EHR data to detect preventive screening disparities has value. EHR functionality should allow for cross-checking gender identity with sex assigned at birth to reduce errors in data interpretation. Additional functionality, like clinical decision support based on anatomical inventories rather than gender identity, is needed to more accurately identify services that transgender patients need.

Indexed as

Gender IdentityUterine Cervical NeoplasmsEarly Detection of CancerElectronic Health RecordsFemaleHumansMalePreventive Health ServicesRetrospective StudiesSexual Behaviorelectronic health recordfederally qualified health centergender identityhealth disparitiesLGBTsexual orientationSOGI data

Identifiers

PMID32947116
PMCPMC9719729
OpenAlexW3048026046

What OpenQuestion holds

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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.