Patterns of gender identity data within electronic health record databases can be used as a tool for identifying and estimating the prevalence of gender-expansive people.

IF 2.5 Q2 HEALTH CARE SCIENCES & SERVICES JAMIA Open Pub Date : 2023-06-24 eCollection Date: 2023-07-01 DOI:10.1093/jamiaopen/ooad042
Nicole G Hines, Dina N Greene, Katherine L Imborek, Matthew D Krasowski
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Abstract

Objective: Electronic health records (EHRs) within the United States increasingly include sexual orientation and gender identity (SOGI) fields. We assess how well SOGI fields, along with International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes and medication records, identify gender-expansive patients.

Materials and methods: The study used a data set of all patients that had in-person inpatient or outpatient encounters at an academic medical center in a rural state between December 1, 2018 and February 17, 2022. Chart review was performed for all patients meeting at least one of the following criteria: differences between legal sex, sex assigned at birth, and gender identity (excluding blank fields) in the EHR SOGI fields; ICD-10 codes related to gender dysphoria or unspecified endocrine disorder; prescription for estradiol or testosterone suggesting use of gender-affirming hormones.

Results: Out of 123 441 total unique patients with in-person encounters, we identified a total of 2236 patients identifying as gender-expansive, with 1506 taking gender-affirming hormones. SOGI field differences or ICD-10 codes related to gender dysphoria or both were found in 2219 of 2236 (99.2%) patients who identify as gender-expansive, and 1500 of 1506 (99.6%) taking gender-affirming hormones. For the gender-expansive population, assigned female at birth was more common in the 12-29 year age range, while assigned male at birth was more common for those 40 years and older.

Conclusions: SOGI fields and ICD-10 codes identify a high percentage of gender-expansive patients at an academic medical center.

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电子健康记录数据库中的性别认同数据模式可作为一种工具,用于识别和估计性别开放人群的普遍程度。
目的:美国的电子健康记录(EHR)越来越多地包含性取向和性别认同(SOGI)字段。我们评估了性取向和性别认同(SOGI)字段与《国际疾病与相关健康问题统计分类》第 10 次修订版(ICD-10)代码和用药记录一起识别性别敏感患者的效果:该研究使用的数据集包括 2018 年 12 月 1 日至 2022 年 2 月 17 日期间在一个农村州的学术医疗中心住院或门诊就诊的所有患者。对所有符合以下至少一项标准的患者进行了病历审查:EHR SOGI 字段中的法定性别、出生时分配的性别和性别认同(不包括空白字段)之间存在差异;ICD-10 编码与性别焦虑症或不明内分泌失调有关;雌二醇或睾酮处方表明使用了性别确认激素:在 123 441 名亲自就诊的患者中,我们发现共有 2236 名患者具有性别扩张倾向,其中 1506 人服用了性别确认激素。2236名性别开放患者中有2219名(99.2%)发现了与性别焦虑症相关的SOGI字段差异或ICD-10代码,1506名服用性别确认激素的患者中有1500名(99.6%)发现了与性别焦虑症相关的SOGI字段差异或ICD-10代码,或两者均有。在性别开放人群中,12-29 岁年龄段出生时被指定为女性的情况更为常见,而 40 岁及以上年龄段出生时被指定为男性的情况更为常见:结论:SOGI 字段和 ICD-10 编码可识别出学术医疗中心的高比例性别扩张患者。
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来源期刊
JAMIA Open
JAMIA Open Medicine-Health Informatics
CiteScore
4.10
自引率
4.80%
发文量
102
审稿时长
16 weeks
期刊最新文献
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