Do you know how our environment affects our health? In reality, there are many contributing factors to a person’s overall health beyond medical conditions. To truly understand a patient’s journey and to be able to treat them with the proper care, it’s important for those in the healthcare industry to consider additional factors beyond a healthcare setting’s four walls that impact a person’s overall health and quality of life.
Medical care is estimated to account for only 10-20 percent of the modifiable contributors to healthy outcomes for a population1. The other 80 to 90 percent are sometimes broadly called the SDoH: health-related behaviors, socioeconomic factors, and environmental factors. SDoH are undeniably valuable in patient care analytics and optimization. First, we will define what constitutes an actionable SDoH and why having this information matters. Then, we’ll address how the healthcare industry can capitalize on SDoH and the role data can play in helping them do so.
The World Health Organization (WHO) defines social determinants of health as “conditions in which people are born, grow, work, live, and age.”2 These conditions refer to attributes and behavior outside of the clinical setting. These forces include economic systems, social norms/policies, and political systems. All of these can impact a person’s health and influence patient outcomes based on the care they receive.
With SDoH, it’s important to consider how these circumstances affect the inequities of a society–most notably, an unfair distribution of money, power, and resources across a community, or on a larger national/global scale. According to the Healthcare Information and Management Systems Society (HIMSS), SDoH has been shown to have a “greater impact on population health and individual well-being than factors such as biology, behavior and medical care.”3 This is primarily a result of the fact that the health inequities caused by SDoH impact not only a person’s overall health but also their access to quality care.
While the WHO has broader definitions of what constitutes a SDoH, the U.S. Department of Health and Human Services broke down these factors into five domains as part of their “Healthy People 2030” objectives:4
Healthy People 2030, U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion
These five domains are not siloed issues and are often correlated to one another. For example, the lower a person’s education the less likely they are to make a livable income, which ultimately impacts their economic stability.
Knowing, and more importantly understanding, a person’s SDoH is critical in fighting back against existing health disparities and inequities and for providing the necessary patient care. After all, health is more than just vital signs and lab result numbers.
For example, a person who lives in an area that lacks access to grocery stores with healthy food is less likely to eat a balanced, nutritious diet. As a result, their risks of conditions such as heart disease, diabetes, and obesity increase. All of these health issues lead to lower life expectancy, and it stems from SDoH.
However, it isn’t enough to just “know” these determinants exist. It’s critical to also understand them. Simply telling a person to “make healthier food choices” does not qualify as quality care if they do not have access to healthy food in the first place. Instead, it requires partnering with public health organizations and caregivers to find realistic and sustainable solutions to address each patient’s particular SDoH and define elements of a winning care plan.
The Covid-19 pandemic renewed the emphasis on implementing interventions to improve socio-environmental conditions associated with SDoH. Since most organizations have an incomplete picture, leveraging demographic, access to care (like transportation, school, foodbanks , YMCA, etc.), community help resources (auntbertha.com) and economic data are the foundation for addressing social determinants.
SDoH impacts all the stakeholders in our healthcare ecosystem. To gain a better perspective on how to approach these conditions, it’s important to consider each individually, as well as how they operate today.
The following are the key players to take into account:
Traditionally, these have been the only stakeholders to consider. However, in recent years, a new player has emerged: tech giants and digital start ups. This reflects a growing trend of providing a connected, frictionless, patient experience leveraging data and artificial intelligence tools.
Without a full picture of an individual–including their SDoH–healthcare organizations are unable to provide the highest quality of patient care and experience. Looking at major digital native organizations like Amazon, Uber and Netflix it’s easy to see why high customer expectations have transferred to healthcare.
In today’s world, patients want price transparency, in-home solutions, simple payment, online appointment schedule, etc. By taking into account that patient’s SDoH, such as their income or literacy background, organizations are more easily able to craft a patient experience that benefits them and meets them where they are at.
Thankfully, there is no shortage of data in healthcare. It just matters whether or not organizations are willing to invest in having the right data to help streamline the healthcare journey not only for patients, but for providers and payers as well.
Just because there is an abundance of data for organizations to access does not mean that data comes without challenges. HIMSS highlights one area of concern as a “lack of standardization in what variables define the social determinants of health and the appropriate screening tools to track these variables.”6 For example, what constitutes a neighborhood being “safe” or “unsafe”? That definition changes based on location and the person being asked.
Another key challenge for the healthcare industry to overcome to fully address SDoH includes “disparate and siloed data from multiple sources across industries, agencies and organizations in the public and private sectors, each with its own structures,” as well as “stakeholders that are not subject to HIPPA regulations.”7
With disorganized and unstandardized data, it is clear that the first step is to utilize technology to synthesize data sources of different kinds to address inconsistencies.
In the public sector, permissibly-sourced data by nature is normalized, stable, and offers comprehensive coverage. These attributes have been architected and perfected based on decades of actionable, profitable use by marketers from all walks of life. They offer full national coverage at the individual, household, and census level. They are readily available to be combined with clinical and claims data to provide a dimensional view of the patient and present opportunity to improve operational efficiency. For example, if you know your patient’s SDoH, you gain insight into their ability and propensity to pay which can inform collection strategies.
Public sourced SDoH attributes are plentiful, and these elements do not have the pitfalls of unstructured data. Your data team can count on these sources to arrive in the same format time after time. Quality is high because these attributes are multi-sourced and frequently updated to insure accuracy. This data provides proven, reliable predictors in the modeling and AI/ML applications to help drive process improvements and improve the overall patient experience.
The final solution to addressing SDoH and improving healthcare access and quality for all involves a multiple stakeholder approach from the patient to the provider to the healthcare organization. However, it all starts with standardization of data and leveraging non-clinical data to create a more clear patient picture. Data that includes SDoH provides healthcare organizations with actionable information to optimize patient outcomes, mitigate risk and ultimately reduce costs.
SDOH data enrichment can be facilitated through the data anonymization platforms like Datavant, Health Verity, Definitie Health or Prognos Health. Your collaborators at Snowflake, AWS, DataBricks can help facilitate your access to the SDOH elements or call us!
With over 25 years of data industry experience, Lisa owns a deep knowledge and understanding of actionable data and predictive outcomes. She is passionate about architecting data-driven solutions that fit customer needs and helping them exceed their business goals. She owns avid listening skills, has an insatiable sense of curiosity, and loves to network with like-minded professionals.