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Social Determinants Of Health: Closing Health Care Gaps Through Data Analysis
by Steve Pirlot

Efforts to improve this country’s health have traditionally looked to the health care system as the key driver of healthy patient outcomes. However, today there is an increasing recognition that improving population health and achieving health equity requires a broader approach that addresses social, economic and other factors that influence health outcomes.

It’s estimated that medical care accounts for only about 10-20 percent of the modifiable contributors to healthy outcomes of a population. The other 80-90 percent are broadly referred to as “Social Determinants of Health” (SDoH).3 These risks include financial insecurity, food and housing security, social isolation, addiction, transportation issues and patient health literacy. Patients facing SDoH barriers disproportionately have:

• additional and unnecessary health care utilization
• lack of engagement with a primary-care provider or medical home
• poorer quality health outcomes

Advocate Aurora Health is working to identify and address SDoH, fully aware of how these factors impact patient health outcomes. There is a system-wide movement toward providing care that addresses patients’ physical, mental, and social needs. This approach supports our vision of providing patient-centric health care tied to value, quality and improved population health.

Linking health care and social needs with SDoH data
Advocate Aurora’s advanced data infrastructure incorporates SDoH information into predictive risk models. We include these factors to identify “at risk” patients who could benefit from specific programs and interventions. Additional priority is devoted to these patients. Data analysis helps us develop risk profiles and identify those cases where additional education, coaching, disease management and clinical integration is likely to improve patients’ health. This “whole-person” approach helps address SDoH barriers and is factored into individualized care plans.

Establishing best practices
Predictive analytics allows Advocate Aurora to analyze large amounts of aggregated health care data, drawing important insights and extracting information to improve health, while reducing costs. Sophisticated data analytics helps establish “best practices” that can have the greatest impact on population health. This is done by analyzing data from insurance and pharmacy claims, along with patients’ electronic health records.

Challenges remain
There’s been notable progress recognizing and addressing the social drivers of health, yet challenges remain. One challenge in scaling these efforts and integrating SDoH into more of our work lies in collecting a robust and accurate dataset. Fully implementing SDoH solutions requires good data, gathered from a large pool of patients. Another challenge is to create opportunities for patient-provider conversations about SDoH factors, during office visits or other patient contacts. Unfortunately, there remains a very real social stigma for many that inhibits patients from having honest conversations about their personal situation. Advocate Aurora is using front-line care managers to build relationships and approach these conversations, paving the way for all providers to better care for these patients.

Opportunities abound
It’s clear that harnessing and analyzing data presents new opportunities to help us improve health care and reduce health care disparities. Data has been shown to help bridge the gap between generating healthy outcomes and SoDH challenges. Data is also useful in connecting patients with unmet social needs with available resources —  inside and outside the health system. Advocate Aurora and its community partners are increasing their collaborative efforts in this area.

A note to employers
Employers should keep in mind that data analysis can also provide a more complete picture of the health of their employee population. Leaders are encouraged to work with their healthcare and insurance partners to better understand their organization’s population health data and identifiable risks.

Looking ahead
Today, the research is there, the interest is there, and the technology is there to address the challenges of SDoH. We are in a phase of innovation and implementation to accurately measure and overcome SoDH issues facing the communities we serve. Our successes in leveraging patient data, forging new community partnerships, reducing social barriers and engaging hard-to-reach members, are vital strategies to improve population health. These concerted efforts can yield a win-win-win scenario for all stakeholders: patients, providers, and plan sponsors.

Steve Pirlot serves as Director, Population Health Analytics at Advocate Aurora Health

3Hood, C. M., K. P. Gennuso, G. R. Swain, and B. B. Catlin. 2016. County health rankings: Relationships between determinant factors and health outcomes. American Journal of Preventive Medicine 50(2):129-135.


 
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