Implementation of Gender Identity and Assigned Sex at Birth Data Collection in Electronic Health Records: Where Are We Now?

Laboratory Informatics Approaches to Improving Care for Gender- Diverse Patients

Improving care for gender-diverse (GD) patients necessitates developing informatics tools and approaches to support optimal laboratory testing. This requires increased functionality and standardization of laboratory information system/electronic health record and data collection processes. Data tailored to accommodate immediate clinical care and clinical decision support (CDS) also have an impact on interoperability and downstream data needs for patients. Informatics tools can shape the clinical care experience for GD patients by careful design of laboratory-patient interactions.

Factors Associated with Completeness of Sex and Gender Fields in Electronic Health Records

Purpose: Our purpose was to understand the completeness of sex and gender fields in electronic health record (EHR) data and patient-level factors associated with completeness of those fields. In doing so, we aimed to inform approaches to EHR sex and gender data collection. Methods: This was a retrospective observational study using 2016-2021 deidentified EHR data from a large health care system. Our sample included adults who had an encounter at any of three hospitals within the health care system or were enrolled in the health care system's Accountable Care Organization. The sex and gender fields of interest were gender identity, sex assigned at birth (SAB), and legal sex. Patient characteristics included demographics, clinical features, and health care utilization. Results: In the final study sample (N = 3,473,123), gender identity, SAB, and legal sex (required for system registration) were missing for 75.4%, 75.8%, and 0.1% of individuals, respectively. Several demographic and clinical factors were associated with having complete gender identity and SAB. Notably, the odds of having complete gender identity and SAB were greater among individuals with an activated patient portal (odds ratio [OR] = 2.68; 95% confidence interval [CI] = 2.66-2.70) and with more outpatient visits (OR = 4.34; 95% CI = 4.29-4.38 for 5+ visits); odds of completeness were lower among those with any urgent care visits (OR = 0.80; 95% CI = 0.78-0.82). Conclusions: Missingness of sex and gender data in the EHR was high and associated with a range of patient factors. Key features associated with completeness highlight multiple opportunities for intervention with a focus on patient portal use, primary care provider reporting, and urgent care settings.

Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study

A person's phenotypic sex (i.e., endogenous expression of primary, secondary, and endocrinological sex characteristics) can impact crucial aspects of genetic assessment and resulting clinical care recommendations. In studies with genetics components, it is critical to collect phenotypic sex, information about current organ/tissue inventory and hormonal milieu, and gender identity. If researchers do not carefully construct data models, transgender, gender diverse, and sex diverse (TGSD) individuals may be given inappropriate care recommendations and/or be subjected to misgendering, inflicting medical and psychosocial harms. The recognized need for an inclusive care experience should not be limited to clinical practice but should extend to the research setting, where researchers must build an inclusive experience for TGSD participants. Here, we review three TGSD participants in the Family History and Cancer Risk Study (FOREST) to critically evaluate sex- and gender-related survey measures and associated data models in a study seeking to identify patients at risk for hereditary cancer syndromes. Furthermore, we leverage these participants' responses to sex- and gender identity-related questions in FOREST to inform needed changes to the FOREST data model and to make recommendations for TGSD-inclusive genetics research design, data models, and processes.

A Holistic Framework for the Evaluation of Kidney Function in a Gender-Diverse Landscape

The most commonly used equations to estimate glomerular filtration rate incorporate a binary male-female sex coefficient, which has important implications for the care of transgender, gender-diverse, and nonbinary (TGD) people. Whether "sex assigned at birth" or a binary "gender identity" is most appropriate for the computation of estimated glomerular filtration rate (eGFR) is unknown. Furthermore, the use of gender-affirming hormone therapy (GAHT) for the development of physical changes to align TGD people with their affirmed gender is increasingly common, and may result in changes in serum creatinine and cystatin C, the biomarkers commonly used to estimate glomerular filtration rate. The paucity of current literature evaluating chronic kidney disease (CKD) prevalence and outcomes in TGD individuals on GAHT makes it difficult to assess any effects of GAHT on kidney function. Whether alterations in serum creatinine reflect changes in glomerular filtration rate or simply changes in muscle mass is unknown. Therefore, we propose a holistic framework to evaluate kidney function in TGD people. The framework focuses on kidney disease prevalence, risk factors, sex hormones, eGFR, other kidney function assessment tools, and the mitigation of health inequities in TGD people.

Impact of sex used for assignment of reference intervals in a population of patients taking gender-affirming hormones

Background

Gender-affirming hormone therapy with either estradiol or testosterone for transgender persons can significantly impact chemistry and hematology laboratory tests. The sex used for assignment of reference intervals (RIs) in the electronic health record (EHR) will influence normal/abnormal flagging of test results.

Objective

To analyze common non-hormonal laboratory tests with sex-specific RIs ordered in patients with sexual orientation/gender identify (SOGI) field differences (one or more differences between legal sex, sex assigned at birth, and gender identity) in the EHR at an academic medical center in midwestern United States.

Methods

We utilized a previously characterized data set of patients at our institution that included chart review information on gender identity and gender-affirming therapy. We focused on the subset of these patients that had orders for 18 common laboratory tests in calendar year 2021.

Results

A total of 1336 patients with SOGI field differences (1218 or 91.2% identifying as gender-expansive; 892 or 66.8% receiving estradiol or testosterone as gender-affirming therapy) had a total of 9374 orders for 18 laboratory tests with sex-specific RIs. Hemoglobin, creatinine, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, and high-density lipoprotein were the most frequently ordered tests. For patients taking estradiol, 128 of 970 (13.2%) creatinine and 39 of 193 (20.2%) hemoglobin measurements were within the RI for one sex but not the other. For those taking testosterone, 119 of 531 (22.4%) creatinine and 49 of 120 (40.8%) hemoglobin measurements were within the RI for one sex but not the other. Values above the cisgender female RI but within the cisgender male RI were common for hemoglobin, alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase in patients taking testosterone.

Conclusions

Clinicians should be aware of the potential impact of gender-affirming therapy on laboratory tests and what sex/gender is being used in the EHR to assign RIs.

Identifying and Characterizing the Transgender and Nonbinary Population Presenting to Pediatric Psychiatry Emergency Services

Transgender and nonbinary (TGNB) individuals have an increased risk of certain mental health outcomes, such as depression and suicide attempts. This population skews younger in the United States and prior studies have not included TGNB patients for the entire pediatric age range in an emergency department (ED) setting. The present study aimed to examine gender identity documentation in the electronic health record and then use that information to identify and further characterize the pediatric TGNB population presenting to a psychiatric emergency service. Preliminary findings include a greater percentage of TGNB patients compared to non-TGNB individuals who had repeat visits to the ED for high acuity psychiatric concerns. A larger portion of TGNB patients also had at least one evaluation that included suicidal ideation. These results call for increased attention on the quality of mental healthcare for TGNB youth both inside and outside of the ED.

Sexual and Gender Minority Status and Suicide Mortality: An Explainable Artificial Intelligence Analysis

Objectives: Suicide risk is elevated in lesbian, gay, bisexual, and transgender (LGBT) individuals. Limited data on LGBT status in healthcare systems hinder our understanding of this risk. This study used natural language processing to extract LGBT status and a deep neural network (DNN) to examine suicidal death risk factors among US Veterans. Methods: Data on 8.8 million veterans with visits between 2010 and 2017 was used. A case-control study was performed, and suicide death risk was analyzed by a DNN. Feature impacts and interactions on the outcome were evaluated. Results: The crude suicide mortality rate was higher in LGBT patients. However, after adjusting for over 200 risk and protective factors, known LGBT status was associated with reduced risk compared to LGBT-Unknown status. Among LGBT patients, black, female, married, and older Veterans have a higher risk, while Veterans of various religions have a lower risk. Conclusion: Our results suggest that disclosed LGBT status is not directly associated with an increase suicide death risk, however, other factors (e.g., depression and anxiety caused by stigma) are associated with suicide death risks.

Analysis of Inclusive Gender, Sexuality and Sexual Orientation Data Elements in Academic Electronic Health Records

Findings from an analysis of three vended academic electronic health records used in health science education are presented in this article. The quality assurance project examined the lexical and semantic fit and content coverage of gender, sexuality, and sexual orientation data elements within the academic electronic health records. A semantic comparative content analysis using a cognitive walkthrough was conducted as a means of comparing the ideal set of gender, sexuality, and sexual orientation data elements with those found in the three vended academic electronic health records. The results indicated a need for alignment to the research literature, expert consensus, and technical standards similar to what is expected for electronic health records used in clinical practice because of a lack of ideal state data elements. The findings align with ongoing issues with bias and disparities seen in the care of the lesbian, gay, bisexual, and transgender population and a lack of diverse, inclusive media and teaching technologies in health science education. The quality project and findings can inform academic electronic health record vendors on how they can create more inclusive systems and bring awareness to healthcare educators about the potential for implicit and explicit bias in their teaching technologies.

Database quality assessment in research in paramedicine: a scoping review

BACKGROUND

Research in paramedicine faces challenges in developing research capacity, including access to high-quality data. A variety of unique factors in the paramedic work environment influence data quality. In other fields of healthcare, data quality assessment (DQA) frameworks provide common methods of quality assessment as well as standards of transparent reporting. No similar DQA frameworks exist for paramedicine, and practices related to DQA are sporadically reported. This scoping review aims to describe the range, extent, and nature of DQA practices within research in paramedicine.

METHODS

This review followed a registered and published protocol. In consultation with a professional librarian, a search strategy was developed and applied to MEDLINE (National Library of Medicine), EMBASE (Elsevier), Scopus (Elsevier), and CINAHL (EBSCO) to identify studies published from 2011 through 2021 that assess paramedic data quality as a stated goal. Studies that reported quantitative results of DQA using data that relate primarily to the paramedic practice environment were included. Protocols, commentaries, and similar study types were excluded. Title/abstract screening was conducted by two reviewers; full-text screening was conducted by two, with a third participating to resolve disagreements. Data were extracted using a piloted data-charting form.

RESULTS

Searching yielded 10,105 unique articles. After title and abstract screening, 199 remained for full-text review; 97 were included in the analysis. Included studies varied widely in many characteristics. Majorities were conducted in the United States (51%), assessed data containing between 100 and 9,999 records (61%), or assessed one of three topic areas: data, trauma, or out-of-hospital cardiac arrest (61%). All data-quality domains assessed could be grouped under 5 summary domains: completeness, linkage, accuracy, reliability, and representativeness.

CONCLUSIONS

There are few common standards in terms of variables, domains, methods, or quality thresholds for DQA in paramedic research. Terminology used to describe quality domains varied among included studies and frequently overlapped. The included studies showed no evidence of assessing some domains and emerging topics seen in other areas of healthcare. Research in paramedicine would benefit from a standardized framework for DQA that allows for local variation while establishing common methods, terminology, and reporting standards.

Assessing Baseline Knowledge and Usage Patterns of Sexual Orientation/Gender Identity Affirming Electronic Health Record Modules Within a Urology Division at a Single Tertiary Care Institution

OBJECTIVE

To evaluate how sexual orientation and gender identity (SOGI)-affirming electronic health record (EHR) modules (which enable seamless location and documentation of patient SOGI data) are being used by providers/staff within a urology practice.

MATERIALS AND METHODS

All 120 patient-facing providers/staff at a tertiary urology program were offered a 39-question Qualtrics-based survey, which assessed respondents' cultural competency, baseline knowledge of SOGI EHR modules, and SOGI module usage patterns. Cultural competency was assessed using the LGBT-Development of Clinical Skills Scale (LGBT-DOCCS).

RESULTS

96 qualified providers/staff completed the survey (response rate, 89%). Only 25% of respondents received training on finding/collecting SOGI data in the EHR. Respondents possessed high levels of LGBTQ attitudinal awareness (M=6.38/7) but low clinical preparedness (M=4.32/7), in large part due to perceived inadequate training to work with LGBT patients. Major drivers of clinical preparedness were respondent role and number of LGBT patients seen in the past year. While respondents uniformly report ease finding SOGI data, all providers/staff (particularly physicians) rarely use formal SOGI documentation tools. Few respondents partook in SOGI EHR training; those that did were significantly more likely to use formal SOGI documentation tools.

CONCLUSION

This study revealed that providers/staff possess high general LGBTQ cultural competency and ability to find relevant SOGI data in the EHR, while also highlighting limited training in SOGI-affirming EHR tools and low usage of formal documentation tools. This framework could be a roadmap for evaluating SOGI-affirming EHR use by urology practices as such features increase in popularity.

Assessing the accuracy of electronic health record gender identity and REaL data at an academic medical center

BACKGROUND

Collection of accurate patient race, ethnicity, preferred language (REaL) and gender identity in the electronic health record (EHR) is essential for equitable and inclusive care. Misidentification of these factors limits quality measurement of health outcomes in at-risk populations. Therefore, the aim of our study was to assess the accuracy of REaL and gender identity data at our institution.

METHODS

A survey was administered to 117 random patients, selected from prior day admissions at a large academic medical center in urban central New York. Patients (or guardians) self-reported REaL and gender identity data, selecting from current EHR options. Variables were coded for the presence or absence of a difference from data recorded in the EHR.

RESULTS

Race was misreported in the EHR for 13% of patients and ethnicity for 6%. For most White and Black patients, race was concordant. However, self-identified data for all multiracial patients were discordant with the EHR. Most Non-Hispanic patients had ethnicity correctly documented. Some Hispanic patients were misidentified. There was a significant association between reporting both a race and an ethnicity which differed from the EHR on chi square analysis (P < 0.001). Of those who reported an alternative ethnicity, 71.4% also reported an alternative race. Gender identity was missing for most patients and 11% of the gender-identity entries present in the EHR were discordant with the patient's self-identity. Preferred language was 100% concordant with the EHR.

CONCLUSIONS

At an academic medical center, multiracial and Hispanic patients were more likely to have their demographics misreported in the EHR, and gender identity data were largely missing. Healthcare systems need strategies that support accurate collection of patients' self-reported ReAL and gender identity data to improve the future ability to identify and address healthcare disparities.

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

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.

Words matter: The language of difference in human genetics

Diversity, equity, and inclusion efforts in academia are leading publishers and journals to re-examine their use of terminology for commonly used scientific variables. This reassessment of language is particularly important for human genetics, which is focused on identifying and explaining differences between individuals and populations. Recent guidance on the use of terms and symbols in clinical practice, research, and publications is beginning to acknowledge the ways that language and concepts of difference can be not only inaccurate but also harmful. To stop perpetuating historical wrongs, those of us who conduct and publish genetic research and provide genetic health care must understand the context of the terms we use and why some usages should be discontinued. In this article, we summarize critiques of terminology describing disability, sex, gender, race, ethnicity, and ancestry in research publications, laboratory reports, diagnostic codes, and pedigrees. We also highlight recommendations for alternative language that aims to make genetics more inclusive, rigorous, and ethically sound. Even though norms of acceptable language use are ever changing, it is the responsibility of genetics professionals to uncover biases ingrained in professional practice and training and to continually reassess the words we use to describe human difference because they cause harm to patients.

Transgender Individuals and Digital Health

PURPOSE OF REVIEW

The goal of this review is to assess the use of digital technologies to promote the health and well-being of transgender and gender diverse (TGD) people.

RECENT FINDINGS

TGD individuals experience numerous health disparities, including low uptake of HIV prevention strategies, such as pre-exposure prophylaxis, increased HIV incidence, and suboptimal HIV-related outcomes. These health disparities are the result of widespread intersectional stigma on the basis of gender identity, gender expression, socioeconomic class, race, and ethnicity, which negatively impact access to general medical and transgender-specific health care. TGD individuals often delay or avoid essential medical services due to fear of discrimination. Clinicians frequently lack training, competence, and skills in transgender medicine, further exacerbating the health disparities faced by TGD people. Digital technologies have been used to improve research and clinical care for TGD populations through various modalities; telemedicine, telehealth and mHealth. Digital health technologies, including HIT-enabled clinical decision support, telehealth, telemedicine, and mHealth, offer innovative ways to improve health care access, improve quality of care, and reduce health disparities for TGD populations, including and beyond HIV outcomes, through enhanced care delivery, clinician education, and enhancing social support networks.

Sex trouble: Sex/gender slippage, sex confusion, and sex obsession in machine learning using electronic health records

False assumptions that sex and gender are binary, static, and concordant are deeply embedded in the medical system. As machine learning researchers use medical data to build tools to solve novel problems, understanding how existing systems represent sex/gender incorrectly is necessary to avoid perpetuating harm. In this perspective, we identify and discuss three factors to consider when working with sex/gender in research: "sex/gender slippage," the frequent substitution of sex and sex-related terms for gender and vice versa; "sex confusion," the fact that any given sex variable holds many different potential meanings; and "sex obsession," the idea that the relevant variable for most inquiries related to sex/gender is sex assigned at birth. We then explore how these phenomena show up in medical machine learning research using electronic health records, with a specific focus on HIV risk prediction. Finally, we offer recommendations about how machine learning researchers can engage more carefully with questions of sex/gender.

Special Section on Inclusive Digital Health: Notable Papers on Addressing Bias, Equity, and Literacy to Strengthen Health Systems

OBJECTIVE

To summarize significant research contributions on addressing bias, equity, and literacy in health delivery systems published in 2021.

METHODS

An extensive search using PubMed and Scopus was conducted to identify peer-reviewed articles published in 2021 that examined ways that informatics methods, approaches, and tools could address bias, equity, and literacy in health systems and care delivery processes. The selection process comprised three steps: (1) 15 candidate best papers were first selected by the two section editors; (2) external reviewers from internationally renowned research teams reviewed each candidate best paper; and (3) the final selection of three best papers was conducted by the editorial committee of the Yearbook.

RESULTS

Selected best papers represent studies that characterized significant challenges facing biomedical informatics with respect to equity and practices that support equity and literacy in the design of health information systems. Selected papers represent the full spectrum of this year's yearbook theme. In general, papers identified in the search fell into one of the following categories: (1) descriptive accounts of algorithmic bias in medical software or machine learning approaches; (2) enabling health information systems to appropriately encode for gender identity and sex; (3) approaches to support health literacy among individuals who interact with information systems and mobile applications; and (4) approaches to engage diverse populations in the use of health information systems and the biomedical informatics workforce CONCLUSIONS: : Although the selected papers are notable, our collective efforts as a biomedical informatics community to address equity, literacy, and bias remain nascent. More work is needed to ensure health information systems are just in their use of advanced computing approaches and all persons have equal access to health care and informatics tools.

Pediatric sexual orientation and gender identity data collection in the electronic health record

The systematic documentation of sexual orientation and gender identity data in electronic health records can improve patient-centered care and help to identify and address health disparities affecting sexual and gender minority populations. Although there are existing guidelines for sexual orientation and gender identity data among adult patients, there are not yet standard recommendations for pediatric patients. In this article, we discuss methods that pediatric primary care organizations can use to collect and document sexual orientation and gender identity information with children and adolescents in electronic health records. These recommendations take into consideration children's developmental stages, the role of caregivers, and the need to protect the privacy of this information. We also focus on the current limitations of electronic health records in capturing the nuances of sexual and gender minority identities and make suggestions for addressing these limitations.

Sexual Orientation and Gender Identity Data Reporting Among U.S. Health Centers

INTRODUCTION

Sexual orientation and gender identity data collection is necessary to address health inequities. This study examines sexual orientation and gender identity data reporting among community health centers.

METHODS

Using the 2016-2019 Uniform Data System for 1,381 community health centers, trends in reporting of sexual orientation and gender identity data were examined. Multivariable logistic regression was used to assess associations between community health center characteristics and whether sexual orientation and gender identity data were available for ≥75% of a community health center's patients in 2019. Data were analyzed in 2021.

RESULTS

In 2016-2019, the percentage of community health centers with sexual orientation and gender identity data for ≥75% of patients increased from 14.9% to 53.0%. In 2019, community health centers were more likely to have this data for ≥75% of patients if they were in nonmetro counties (OR=1.48, 95% CI=1.04, 2.10 versus metro), were in the South (OR=2.27, 95% CI=1.57, 3.31) or West (OR=1.91, 95% CI=1.27, 2.88 versus the Northeast), and had more patients aged between 18 and 39 years (OR=1.04, 95% CI=1.02, 1.07), between 40 and 64 years (OR=1.04, 95% CI=1.02, 1.06 vs <18 years), or veterans (OR=1.10, 95% CI=1.01, 1.20). This was less likely among community health centers serving 10,000-20,000 patients (OR=0.70, 95% CI=0.52, 0.95) and >20,000 patients (OR=0.44, 95% CI=0.32, 0.61 vs <10,000) and community health centers with more patients of American Indian/Alaskan Native (OR=0.98, 95% CI=0.97, 0.99) or unknown race (OR=0.92, 95% CI=0.86, 0.97 versus White).

CONCLUSIONS

Collection of sexual orientation and gender identity data by community health centers has increased substantially since 2016, although gaps remain.

Sex and Gender Equity in Prehospital Electrocardiogram Acquisition

INTRODUCTION

Research in cardiac care has identified significant gender-based differences across many outcomes. Women with heart disease are less likely both to be diagnosed and to receive standard care. Gender-based disparities in the prehospital setting are under-researched, but they were found to exist within rates of 12-lead electrocardiogram (ECG) acquisition within one urban Emergency Medical Services (EMS) agency.

STUDY OBJECTIVE

This study evaluates the quality improvement (QI) initiative that was implemented in that agency to raise overall rates of 12-lead ECG acquisition and reduce the gap in acquisition rates between men and women.

METHODS

This QI project included two interventions: revised indications for 12-lead acquisition, and training that highlighted sex- and gender-based differences relevant to patient care. To evaluate this project, a retrospective database review identified all patient contacts that potentially involved cardiac assessment over 18 months. The primary outcome was the rate of 12-lead acquisition among patients with qualifying complaints. This was assessed by mean rates of acquisition in before and after periods, as well as segmented regression in an interrupted time series. Secondary outcomes included differences in rates of 12-lead acquisition, both overall and in individual complaint categories, each compared between men/women and before/after the interventions.

RESULTS

Among patients with qualifying complaints, the mean rate of 12-lead acquisition in the lead-in period was 22.5% (95% CI, 21.8% - 23.2%) with no discernible trend. The protocol change and training were each associated with a significant absolute level increase in the acquisition rate: 2.09% (95% CI, 0.21% - 4.0%; P = .03) and 3.2% (95% CI, 1.18% - 5.22%; P = .003), respectively. When compared by gender and time period, women received fewer 12-leads than men overall, and more 12-leads were acquired after the interventions than before. There were also significant interactions between gender and period, both overall (2.8%; 95% CI, 1.9% - 3.6%; P < .0001) and in all complaint categories except falls and heart problems.

CONCLUSION

This QI project resulted in an increase in 12-leads acquired. Pre-existing gaps in rates of acquisition between men and women were reduced but did not disappear. On-going research is examining the reasons behind these differences from the perspective of prehospital providers.