Supporting Social Determinants of Health Strategies with AI

The social determinants of health have become a household term in the healthcare industry’s vernacular, with leaders and organizations aiming to address these influences to provide more comprehensive care.

Patients’ wellness is primarily impacted by factors outside healthcare facilities, so having access to social determinants data has become a critical part of care delivery.

“Our health isn’t taking place in the doctor’s office – it’s where we live, where we work, and where we play,” Amy Andrade, former assistant vice president of research at Meharry Medical College and founding director of Meharry Medical College’s Data Science Center, said during a recent episode of Healthcare Strategies, an Xtelligent Healthcare Media podcast.

“You have to step back and look at those influences. If providers and health systems don’t have access to this information, then they’re not seeing the true picture of what’s influencing health. You can’t just look at it in a siloed fashion.”

Barriers like a lack of data standards and costly datasets can hinder an organization’s ability to access social determinants information, Andrade noted. However, developing an approach for more holistic patient care will be necessary for every entity looking to improve patient and population health – whether the data is complete or not.

“You have to have a vision for data. It’s all about the data,” Andrade said.

“Health systems, small or large, need to have a data plan in place. They have the clinical data, and now they need to think about how they’re going to use the socioeconomic data. If you’ve got 75 percent of the information, you’ve got to just jump in. You can’t wait perfect it, because then you’ll miss that opportunity.”

Defining where the biggest challenges lie within an organization or patient population is an essential part of these data plans. Advanced tools like AI and machine learning can help leaders get to the underlying reasons for these challenges.

“You’ve got to look at your particular health system and what’s plaguing you. For instance, in urban areas it’s the prevalence of underlying chronic diseases. In other places, it may be cancer,” Andrade said.

“The second step is, you’ve got to ask yourself why. If you peel back the onion, you’ll get to the root cause. So now you have these large amounts of data, and that’s where AI comes in.”

Ultimately, building an AI model that meets the needs of your organization will likely be a process of a trial and error, Andrade said.

“It takes some time, because each model performs differently depending on the data that you have. It is the quantity of data that comes in and the artificial intelligence intersecting with the information you have available,” she said.

Listen to the full podcast to hear more details about how AI and machine learning can help support social determinants of health strategies. And don’t forget to subscribe on iTunes, Spotify, or Google Podcasts.