Treating the Invisible: Why Data Matters in Health Care

An estimated 1.1 million Americans are living with HIV, a deadly but treatable disease that affects subgroups like LGBTQ and homeless populations at higher rates. However, when these populations are missing from health data, it poses a challenge: How do you treat someone you can’t see?

According to USC Suzanne Dworak-Peck School of Social Work Department of Nursing professor Theresa Granger, PhD, MN, ARNP, FNP, NP-C, finding and treating homeless youths can be tricky even though they are so closely linked to one another.

“That youth social network is very tight, and it’s very effective,” said Granger, a specialist in health interventions for homeless youth. “But as the provider, it’s really difficult to access those networks because a lot of youth, for a lot of different reasons, won’t open up and talk to you about what their network is and what it looks like.”

A lack of information isn’t just a problem for providers serving homeless populations. LGBTQ people, Native Americans and other communities are consistently under- or misrepresented in national datasets, creating barriers to both their care and widespread solutions.

What Data Is Missing on Minority Populations?

Federally funded surveys like the U.S. Census and the American Community Survey (ACS) provide necessary and fundamental insight about the population but don’t always include questions that garner specific, in-depth information.

In 1990, for example, the Census Bureau included “unmarried partner” as a relationship option for the first time. Nearly 30 years later, the 2020 Census will offer more specificity with a “same-sex” option.

The Census also separates race and ethnicity questions, forcing Hispanic and Latino respondents to choose a race from a list that is not necessarily representative of their reality. As a result, “some other race” is the third-most selected answer to the Census question “What is Person 1’s race?” while 97 percent of people who choose this answer are actually Hispanic.

How Does More Data Improve Quality of Care?

The inability to accurately define populations can make it difficult to identify the specific health problems people face.

Social determinants of health (SDOH) are the circumstances that surround every person’s life. They are unavoidable and sometimes uncontrollable, and they are largely responsible for health discrepancies between, and among, populations.

Factors like social exclusion, employment conditions and urbanization can contribute to negative health outcomes that are disproportionately experienced by specific groups of people.

Kevin Ard, medical director at the National LGBT Health Education Center, said data creates a better understanding of health discrepancies and can be a necessary trigger for meaningful action against them.

“Information that we get from population-based surveys about health really guides the health maintenance and health prevention priorities of this country,” Ard said.

The Youth Risk Behavior Survey was the first of its kind to ask high-schoolers about their sexual orientation and the sex of their partner. Findings pointed to higher rates of sexual assault, depression and drug use among LGBTQ youth — population-level proof of the health discrepancies affecting a vulnerable population.

Another area where data could lead to wide-scale change is among the homeless youth that Granger works with. She noted that even within the population, social determinants vary and the solutions require change at an infrastructure level.

“Rural youth are geographically isolated, and there really aren’t the resources that you have in the larger urban areas,” she said. “A lot of homeless rural youth continually have unmet needs. And to meet them, they have to try and figure out how to travel great distances to access those resources.”

At the individual patient level, data can create more positive health outcomes through more accurate medical interventions and standards. For example, the CDC has specific guidelines for care of LGBTQ patients, and the National Health Care for the Homeless Council offers resources for adapted clinical measures for patients who are homeless.

Data can also help improve patient interactions with providers. In Granger’s experience with LGBTQ youth, small changes and thoughtful engagement have resulted in positive ripple effects. She recommends asking questions like:

What pronoun do you prefer?

How do you want to be addressed?

How would you like to be examined?

These are small adjustments medical offices can make to their intake process that will better serve patients. Providers can also improve the patient experience by training staff on vocabulary and cultural competency.

Lastly, Ard said data matters when it comes to measuring patients’ successes.

“Unless we know where things stand now in terms of our patients’ quality of care and satisfaction with care, there’s no way we can improve,” he said.

What Can Be Done to Help Data Collection?

At the most basic level, descriptive data is needed to learn more about minority populations and the health discrepancies they experience. Recommended improvements to federally funded surveys like the Census and the ACS include adding questions about sexual orientation and transgender status, as well as reformatting race and ethnicity questions to better capture minority populations.

Sexual orientation and gender identity (SOGI) data can help pinpoint major health disparities for LGTBQ populations just by adding questions about things like sexual orientation and transgender status. Recommended changes from the Census Bureau highlight the ways surveys can better capture the racial-ethnic populations in the United States.

One way to find these links between SDOH and underrepresented populations is through individual-level data collection spearheaded by clinicians. Granger does this in her practice, but she recognizes the challenges and intricacies of trying to do so.

Due to HIPAA, she advises against directly reaching out to find patients in the community. She instead leans on a grassroots, boots-on-the-ground approach that utilizes the work of organizations.

“Often, we’ll tell the outreach workers, ‘We’re looking for this person. Please help us find her.’ And then these outreach workers will help us,” Granger said.

Once patients are within a provider’s care, there are some simple ways to make the data collection process smoother:

1 Keep patients informed about why you’re asking questions. Use informational pamphlets and FAQs to help patients understand the goals behind data collection and ease any concerns about personal questions.

2 Integrate questions naturally into the established appointment process. Find a flow that works best for the office, such as asking that patients answer questions at intake or at the beginning of their appointment with the provider.

3 Collect and track data in a meaningful way. Asking the right questions means little if there is nowhere to record the answers. For providers who use electronic medical records, make sure to incorporate questions into the system in a way that ensures answers are captured accurately and efficiently.

Population-specific data on environmental factors is also needed to find new links between minority communities and health disparities. The following are examples of questions that will prompt patients and help providers understand more about the unique social determinants people face:

Have you experienced discrimination, microaggressions or marginalization?

Are you interacting with peers?

Do the people close to you know about your food or housing insecurity?

Data collected from these questions can help identify the experiences that are specific to certain communities and the negative health outcomes that result. Despite the added time, Granger said that including these processes is for the betterment of all patients’ experiences.

“We’re just trying to create the best possible scenario for everybody,” she said, “and make sure that everybody is included and that everybody gets the same level of care.”

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Citation for this content: Nursing@USC, the online FNP program from the University of Southern California