Getty Images

Researchers Create Gender-Inclusive HL7 Model, EHR Documentation

Researchers, including ONC Deputy National Coordinator Steven Posnack, have created an HL7 model for gender-inclusive clinical EHR documentation.

Leveraging health IT data standards through a gender-inclusive HL7 model for EHR documentation could help improve care delivery for gender-marginalized patients and boost health equity, according to a new study published in JAMIA.

A single recorded administrative sex or gender value is often assumed to be all a clinician needs to understand a patient's clinical sex and gender identity. However, researchers noted that a binary value does not represent the full spectrum of gender and sex.

“The current representation of patient sex and gender information in interoperable clinical systems poses major challenges for organizations intent on improving outcomes for sex- and gender-marginalized people,” they wrote.

The study authors created a conceptual HL7 model for clinical EHR documentation that aims to more accurately record patients’ sex and gender within the EHR in pursuit of health equity for gender-marginalized patients.

The HL7 Gender Harmony Logical Model has five major elements: gender identity (GI), sex for clinical use, recorded sex or gender (RSG), name to use (NtU), and pronouns.

The researchers explained that GI is an individual's personal sense of being a man, woman, boy, girl, or something else. The model states that GI is something that is determined by the individual themselves and cannot be assigned.

The RSG element is used to identify sex values or gender values that are specified administrative documents such as identity cards or insurance cards. By characterizing these sex or gender values as “recorded” and documenting the context of use, EHR systems avoid repurposing administrative sex and gender data for clinical care.

SFCU is a summary sex classification element based on clinical observations like organ survey, hormone levels, and/or chromosomal analysis. This element gives end-users the option to refer to specific clinical reports to clarify the value selection for assumption-free clinical care.

Allowed values for SFCU include Male, Female, and Specified. The value “Specified” is preferable to the term “Other” found in many value sets because it is explicit and non-stigmatizing, the researchers explained.

Additionally, the researchers noted that based on discussions with members of the intersex community during model development, the phrase “Intersex” is not included in the allowed values because the phrase is specific, overly revealing, and can be over-interpreted.

The SFCU element also allows users to specify different values for the same patient based on specific clinical uses. For instance, SFCU can be used to justify instrument set-up based upon an organ inventory observation or hormonal levels, the researchers explained.

The NtU element indicates the name that the patient wishes to use in healthcare interactions.

“This element will have benefits beyond those of gender-inclusive care: people with Americanized names, people with very long names, and people with preferred names will be able to inform clinicians of those names without having to change their legal name,” the study authors wrote.

Lastly, the pronouns element identifies the English language third-person personal pronoun determined by the patient for use in healthcare interactions, clinical notes, and written instructions to caregivers.

The HL7 community of standards has begun to work with the researchers to incorporate the proposed changes into each of the existing HL7 standards; V2, CDA, and FHIR. Ultimately, the implementation of the health IT data standards will boost care delivery for gender-marginalized patients, the researchers noted.

“When these improvements are implemented based on standards accompanied by certification expectations, exchange of these data between healthcare organizations will improve the patient experience by reducing requirements for data re-entry and improving the reliability of sex and gender information made available to clinicians, enabling quality care relationships for gender-marginalized people from intake,” the researchers concluded.

Next Steps

Dig Deeper on Health IT optimization

Cloud Computing
Mobile Computing