Capturing complete and accurate data on sexual orientation and gender identity (SO/GI) is essential to ensuring LGBTQIA+ patients receive the care they need and deserve. It impacts everything from the provision of appropriate care at the patient level to our ability to address health disparities, discrimination, and oppression throughout the health care system.
The National Association of Community Health Centers is working on tools to support health centers in improving the collection of SO/GI data so that “health centers can identify opportunities for more culturally and medically adept LGBTQIA+ services.”
Validation using data analytics is key to this effort. With the right reports, health centers can identify patient records missing SO/GI data and likely errors, using data to make smart choices about allocating resources for staff training and process improvement.
Here are some outlines of reports Relevant uses to validate SO/GI data:
Patients missing SO/GI data
Generate lists of patients with some or all SO/GI data missing:
- Check to see if SO/GI data is captured in unstructured notes fields, and add it to the structured fields
- Create care gaps to alert staff when they come in for a visit to make sure they capture the data
- Calculate the percentage of patient records missing SO/GI data by the following to see which providers, teams, and locations may benefit from training and process improvement:
- Primary care giver / team
- Primary location
- Visit provider / team
- Visit location
Potential Discrepancies in Gender Identity data
Check for possible errors in gender identity data that has been collected. For this report, pull in sex assigned at birth in addition to gender identity for the purposes of data validation. Look for the following potential discrepancies and confirm that the patient’s gender identity and sex assigned at birth are captured correctly:
|Gender Identity||Sex assigned at birth|
|Transgender Man, Transgender Male, Transgender Masculine||Male|
|Transgender Woman, Transgender Female, Transgender Feminine||Female|
For example, someone who identifies as a Transgender Man was likely assigned Female at birth, so if you see these two values for the same patient, it’s likely that one of the two data points was captured incorrectly.
Someone whose gender identity is Female and was assigned Male at birth likely identifies as a Transgender Woman.
Note: Sexual Orientation and Gender Identity for a single patient can vary over time, so different responses on different dates does not necessarily mean there is a problem with the data.
Double-check your mappings
- Make sure that you are not using or defaulting to sex assigned at birth as a stand-in for gender identity - they’re not the same thing (and UDS forbids this)
- Make sure that you are not defaulting to “straight” for patients where sexual orientation is not known
- Check to see if SO/GI data is stored in more than one place. Some EHRs only added built-in support for SO/GI data in recent years, so there is often historical data in separate structured fields. This can fill in gaps, and is worth checking as some staff may still use this legacy data
It’s important to note that sexual behavior and sexual orientation do not always align, so it’s important to collect data on sexual behavior in order to provide the best sexual health care to your patients.
Finally, patients may not identify themselves using the exact language from the UDS report. If you use additional gender identity categories in your EHR and map them to the UDS category, be sure to account for that in your validation efforts.