SDoH Explorer

Healthcare Analytics • Healthcare Systems

Challenge

Understanding the intersections between healthcare outcomes and socio-economic factors to impact healthcare outcomes across the U.S. is critical for improving patient care and health equity. Our Major client needed an analytics-driven approach to explore these social determinants in interaction with their patients claims datasets, in particular by enabling the integration of a comprehensive dataset to explore items such as education and income, and other socio-economic factors affecting healthcare utilisation and outcomes, while also explicitly pinning greater focus on different demographics and geographic locations.

Our Approach

To build an intuitive and scalable solution, we identified and categorized key socioeconomic factors (income, healthcare insurance availability, education) and interactive filtering mechanism, enabling users to explore the impact of various SDoH factors dynamically. Mapped the distribution of socioeconomic condition codes across the United States using detailed demographic trends to understand how gender age, and state-level factors influence healthcare access and claims patterns. Finally using this payer data to uncover key insights across different providers, identifying the trends based on sub-grouping basis across different geographies and geographic locations.

Results

The tool revealed intuitive disparities in how SDoH factors affect healthcare utilization across different age groups, genders, and states. Family-related issues emerged as the leading SDoH condition associated with healthcare claims. Women were significantly more likely to report SDoH-related conditions compared to men, highlighting a need for further intervention and support mechanisms.

Business Value

By providing a scalable and interactive analytics platform, the SDoH Explorer allowed healthcare agents and decision-makers to gain actionable insights into the socio-economic drivers of healthcare disparities. The ability enabled stakeholders to make data-driven decisions on policy, resource allocation, and patient care strategies.