Examining social determinants of health through data analytics can lay the foundation for evidence-based care.
With the shift from fee-for-service to value-based care, there is added financial pressure for health systems to reduce emergency department admissions and curb ED overuse.
A thorough analysis done by Morning Consult reveals a strong relationship between ED usage and 28 indicators called social determinants of health (SDOH). How a state performs in terms of education, employment, and poverty is linked to how often its citizens use the ED and how patients fare after being discharged.
It’s clear that social and economic factors affect health outcomes, mortality, and chronic disease progression, but the struggle to create a system that addresses those is an ever-present problem.
Gathering the Information
Statistics show that clinical care influences only 10 to 20% of a patient’s health outcome and the rest depends upon SDOH. With these numbers, providers must pay attention to the role played by life circumstances. Connections exist between food insecurity and diabetes outcomes, poverty and vaccination rates, and more. Society is an interwoven, complex system that requires integrated and complicated, solutions.
To improve SDOH, it can be helpful to collect, organize, and understand pertinent data. Many HCOs have been integrating SDOH queries into their admission routines, both for emergency departments and inpatient units. One example is the CMS Accountable Health Communities (AHC) Health-Related Social Needs (HRSN) Screening Tool. Adding these tools to existing electronic health record (EHR) documentation to capture SDOH data is a great start. However, while EHRs store some of this data in discrete form, there is also a wealth of valuable unstructured data locked away in case notes.
Clinicians, case managers, and social workers are documenting stories that converge to form a common thread in communities. How can this unstructured data be turned into actionable information? d2i is meeting the challenge through increased efforts in capturing both structured and narrative EHR data and combining it to tell the story.
SDOH data is spread out across multiple EHR formats and other data is contained in systems, such as community health resources and EMS records, so getting a complete picture may seem daunting. d2i understands these challenges.
Providing Insight and Measuring Progress
Most providers are aware of particular SDOH problems in their communities through anecdotal evidence they encounter every day. d2i helps quantify and stratify these issues, providing the platform for identifying and acting on the highest impact insights.
Large-scale datasets and studies, such as AHRQ’s Medical Expenditure Panel Survey (MEPS), ongoing since 1996, have provided a lot of the baseline data that has helped form our current understanding of SDOH. As health care organizations across the country start to gather more data and mobilize strategies for improvement, capturing comparative numbers will be critical to gauge success.
Future evidence-based strategies for SDOH are being formed as HCOs begin to discover what works best. The data foundations laid now will form the basis of future success for patient outcomes, medical spending, community relationships, and public health. Contact d2i to learn how its data analytics solutions can help you lay those foundations.