Going Beyond the Chart – Understanding Social Determinants of Health

Updated on February 9, 2023
patient care

It’s often said, “Diagnosis is the first step toward healing.” From that perspective there is great news! The healthcare industry has been diagnosed with providing inconsistent care to patient populations of varying cultural and socio-economic backgrounds. That means we’re on the road to recovery, right? Unfortunately, this diagnosis comes with a complex and uncharted treatment plan. 

One key element of providing great care to patients of all backgrounds is understanding the core problem better. That is where Social Determinants of Health (SDOH) come in. These critical drivers of wellness go beyond the data collected in a standard medical chart but are directly linked to over 50% of health outcomes! 

Chances are if you are in a healthcare role, you are already familiar with the social determinants of health. Hopefully you are even already developing an action plan of how to take this information and make real changes. Many organizations find this step to be the most challenging. “Taking action” can often include assembling a committee to review how social determinants of health are affecting their direct patient population. Some are even being proactive enough to collaborate with other institutions to gather best practices. But these steps, although positive, can’t drive better outcomes unless a real plan emerges. 

Where to start: Driving dramatic change starts with gaining a complete understanding of the situation. High-level zip code overviews, which highlight residents that may struggle with housing, access to food and transportation are great. But, they are not granular enough to generate custom solutions to the challenges different health and wellness organizations face. 

Get specific: To go a layer deeper, we need to start with the end in mind. Outline the exact outcomes you are struggling with or that are falling below your expectations. Whether it is a large population struggling with diabetes, opioid addiction, or maternal and infant risk, make sure you are clear on the problem, or problems you are targeting. Attempting to ‘boil the ocean’ is what keeps many organizations in analysis paralysis, consumed by data without a clear path out.

Fill data gaps: Identify the data gaps that exist in your current analysis that may connect to these specific problems. Does your data scale for the specific geographic areas you support, or is it thinner locally, with insights derived from national averages? Does your data have depth on all social determinants of health, or does it focus on one area, like census collected data points? 

One common data gap that exists in many organizations is behavioral data. A complete analysis will include commonly captured elements like income, education, or access to food, but will expand to include behaviors as well.  

Behavioral data like alcohol and tobacco use, and attitudes toward fitness and adherence have shown to impact outcomes by 30%. These data points are often ignored in data analysis because they either seem unattainable or lack the depth to be productive in complex analyses. Fortunately, predictive data on these more nuanced factors is now available at scale. 

Don’t begin analysis without having a complete dataset in place. Starting without all the elements that make up a complete SDOH data set – including demographics, personal care habits, utilization and adherence likelihood as well as overall health and lifestyle factors like diet and sleep quality – may lead to false conclusions and may keep you from finding the more powerful answers. 

Give yourself a finish line. To put it in running terms, establish what you hope to achieve from completing a 5k. Then advance to a 10k, and eventually a marathon. Establishing a “finish line” doesn’t mean you won’t run again, it’s just a milestone to celebrate what has already been achieved, and establishes when you should pause to identify the next challenge or milestone.

Many healthcare organizations become stuck in committee or analysis mode. While these findings and discussions are an important part of the process, without a proper finish line valuable insights may never convert into action. Healthcare teams integrating SDOH intelligence into the early stages of research and analysis, have a clearer path to the finish line. Just like any treatment plan, the SDOH-driven goal must be specific, the right components available, and milestones established. With a solid plan in place, driving better outcomes for all patients is within reach.

Christine Boley AnalyticsIQ
Christine Boley

Christine Boley is Head of Health Partnerships for predictive data innovator, AnalyticsIQ. Christine has over a decade of experience in the data and analytics space and has worked with industry leaders across verticals like healthcare, pharma, non-profits, and more. Christine lives in Central Florida with her family, dogs, and cats – a house full of love!