We are at a turning point, at the meeting between modern medicine and rapidly advancing data analytics.
On one hand, the use of analytical systems holds the promise for amazing revolutions in care, particularly when it comes to preventative medicine and expanding healthcare access to more people. On the other hand, the amount of data needed to bring about these achievements are monumental and carries real concerns about ethical data-collection as well as protecting patient privacy.
How can data on health disparities and the social determinants of health (SDOH) be utilized in an ethical manner? What pitfalls exist, and how can they be avoided? These questions abound, and the industry is only beginning to scratch the surface in finding the best ways to address them.
I. Utilization of Health Disparities and Social Determinants of Health Data
2021 became a watershed year in advancing health-related data collection. On July 9, the Office of the National Coordinator for Health Information Technology updated its standardized list of data elements that hospitals can collect and share. Gender identity, sexual orientation, and SDOH data could now be collected, giving long-needed recognition that these were important health determinants. SDOH, in this context, includes information such as socioeconomic status, occupation, and location.
Hospitals and clinics are not required to obtain this information but are encouraged to.
However, this runs into privacy issues, as well as other patient concerns. Those in minority groups - such as black or LGBT+ communities - are often hesitant to share personal information which, in the past, could be used against them. Studies have suggested that, overall, one in six people withhold personal information in healthcare settings, with that number going as high as two-thirds when looking at specific marginalized populations.
This is an issue because those populations are, far too often, suffering from health disparities in terms of access to care, as well as the quality of care.
II. The Ongoing Problem of Health Disparities
For decades, the healthcare industry has recognized that there are significant disparities between the quality of care afforded to certain groups, and not to others. Data has repeatedly shown, for example, that black people have higher rates of infant mortality and pregnancy-related deaths, compared to white people. Likewise, the struggles of LGBT+ people receiving equal care have been well-documented back to the initial AIDS outbreak in the 1980s.
The same is true for insurance rates. Consistently, Native Americans, Hispanics, Black people, and those of Pacific Island descent are uninsured far more often than other groups. This, by itself, limits their access to modern healthcare systems.
In addition, these disparities create unfortunate domino effects. Lack of proper care in minority groups leads to life-long issues, such as higher rates of mental illness, and lower quality-of-life among older people in these populations. Health inequalities lead directly to larger-scale social inequalities.
The silver lining here is that the COVID-19 outbreak has brought these issues to the forefront. Responsible healthcare simply cannot allow racism and other forms of discrimination to continue marginalizing specific groups. A pandemic knows no racial, gender, or sexual boundaries and will spread and transmit between everyone. Preventative care and harm reduction require new techniques which identify these underserved populations and enables proactive steps to actively provide better health care to them.
The use of data on health disparities and the social determinants of health is key to making this happen - if there is enough buy-in among both healthcare providers and these under-served populations.
III. The Need for SDOH Data Is Real
Improved use of data is a very real solution to these issues, one which is already seeing measurable benefits. It is well-known, for example, that cardiovascular disease can be predicted based on a variety of personal and lifestyle factors. However, marginalized groups - particularly black communities - have higher rates of heart disease than other populations. Studies have already shown that by incorporating SDOH data into these analyses, at-risk marginalized people can be more accurately identified, and their risk of heart disease reduced accordingly.
This is just one example. As data collection grows and machine-learning systems continue to become "smarter," more and more risk factors will be concretely determined. This, in turn, will lead to ever-better preventative care - if there is sufficient buy-in.
In the aggregate, two changes are needed.
First, hospitals, clinics, and other healthcare providers need to see and understand the benefits which come from incorporating data on health disparities and the social determinants of health. The more operations that are collecting and sharing this data, the more quickly advances will come.
Secondly, there must be deliberate, sensitive, and concerted outreach to marginalized communities. In many cases, their fears of data abuse are rooted in real historical events - such as the AIDS crisis, or the Tuskegee experiments. They need to be convinced of the beneficial nature of data collection and cooperate willingly.
Learn More About Health Disparities & Social Determinants of Health
Socially Determined believes these advances to decrease healthcare disparities are possible and continue to provide healthcare organizations with full visibility into social risk. Through Social Risk Intelligence™, these organizations get a better understanding of what’s driving care gaps and can take proactive action to help the communities and people they serve who need it the most. Contact us to learn more.