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Data Standards Key for EHR Documentation of Gender Minority Patients

A health system implemented SOGI EHR documentation protocols, but a lack of data standards limits the usability of SOGI data across the care continuum.

As healthcare organizations look to sexual orientation and gender identity (SOGI) EHR documentation to improve health equity for gender-minority patients, a lack of national data standards limits data usability across the care continuum, according to a study published in JAMIA.

Geisinger, an integrated health system located in rural Pennsylvania, modified its Epic EHR system to enable the collection and use of SOGI-related information.

In particular, the health system added four new data elements:

  • Gender identity, which refers to how individuals perceive themselves
  • Birth sex, which documents anatomic and/or physiologic characteristics
  • Affirmation history, which documents transition steps for transgender patients
  • Organ inventory, which documents organ history for transgender patients

The health system also configured the EHR to ensure inclusive documentation for existing data elements such as legal sex, pronouns, correct name, marital status, and emergency contacts.

Geisinger modified clinical decision support tools in the EHR to ensure the correct use of the updated data elements. For instance, wherever the EHR used a patient’s sex, Geisinger configured the system to map to legal sex, gender identity, or birth sex, based on the context.

Clinician training focused on the clinical needs of the LGBTQ+ community, including what data to collect and how to use that information when ordering and interpreting tests, prescribing medications, and tracking health maintenance. Educational programming also focused on cultural awareness and unconscious bias.

The study authors noted challenges in developing effective staff training and allocating sufficient time. Ultimately, they found that interactive trainings where staff practiced using preferred pronouns and asking sensitive questions were the most effective.

Prior to training, some staff reported reluctance asking SOGI-related questions, often noting that these topics might make patients uncomfortable. The study authors noted that training that demonstrated the incorrect way to ask a patient about their SOGI information, followed by how to appropriately ask sensitive questions, have helped alleviate staff concerns.

Geisinger’s initial approach to collecting SOGI information relied on face-to-face discussions during clinic encounters. Several studies have indicated that integrating self-reported SOGI information yields high satisfaction for most patients, the researchers said. A recent study recommended integrating SOGI questions alongside other demographics information, such as race/ethnicity and employment, as this helps normalize the information gathering.

Geisinger is currently developing a patient self-reporting questionnaire which will be available via the health system’s patient portal and via tablet in private healthcare settings. The “About Me” questionnaire includes questions about gender identity, birth sex, sexual orientation, pronouns, race, ethnicity, preferred language, and veteran status.

Geisinger’s implementation used standard data values and documentation forms in its EHR. However, a lack of national SOGI data standards hinder data usability across the care continuum.

“The lack of standards makes it difficult for data such as gender identity, birth sex, correct name, or pronouns to be exchanged reliably among systems,” the study authors noted.

“The lack of standards also makes it difficult to benchmark performance in data collection and use,” they added. “The result is that even though individuals may provide information, and have it stored accurately in one system, it may not always be used to provide respectful, inclusive services across the continuum of care.”

National data standards for SOGI data could be around the corner. A new study outlined a conceptual HL7 model for clinical EHR documentation that aims to more accurately record patients’ sex and gender within the EHR. 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 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 HL7 researchers concluded.

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