Five ways to leverage socioeconomic data
As value-based care becomes more prevalent within the healthcare industry, so does the need to deliver higher quality care at a lower cost. As healthcare organizations look to curb costs and operate more efficiently, there’s growing evidence pointing to the importance of understanding and addressing social determinants of health. Socioeconomic factors and healthcare utilization have an evidenced correlation — it’s estimated that social determinants of health (SDOH) account for 50% – 60% of all health outcomes1.
Based on statistics like these, it’s important for healthcare organizations to gather and leverage socioeconomic data in order to manage care more effectively and better predict risk. Data can be gathered from various sources including directly from the patient, via Census or other publically available or proprietary sources.
Some of the most common ways organizations use SDOH data include:
1. Risk stratification – Healthcare organizations use socioeconomic data as one of a few sources to determine what level of risk a patient is for utilization — low risk, moderate risk, rising risk, high risk, etc. In addition to using their own clinical and claims data, adding socioeconomic data provided by a third party can enhance risk scores built in-house. As a result, organizations are able to build comprehensive models to segment populations and better manage health outcomes.
2. Predictive analytics – Utilizing these enhanced scores built on various sources of data can help to identify potential high-risk individuals and help organizations implement non-traditional treatments proactively. This information can help reduce:
- Readmission risk
- Emergency department utilization
- Medication non-adherence
3. Social needs referrals – Armed with the right information and tools, care managers can make social needs referrals to community-based organizations, such as:
- Food banks
- Transportation assistance
- Temporary housing assistance
- Job training programs
- Financial aid assistance
4. Individual care interventions – Individual-level datasets can inform care managers of specific socioeconomic needs the healthcare organization can directly address. For example, if an individual doesn’t have a car, free rides can be offered to and from the physician’s office to ensure they can make their appointment.
5. Community-level interventions – Aggregated data sets can be leveraged to identify which specific neighborhoods would benefit most from community interventions to address SDOH. For example, a hospital could open a food pharmacy or offer nutrition education sessions in a food desert.
TransUnion Healthcare’s Social Determinant Risk Attributes delivers individualized (evidence-based data from 90,000+ sources and matched at patient level) and aggregated (neighborhood data down to the ZIP + 4 level) socioeconomic datasets.
For more information on our offerings and how it can enhance your SDOH efforts, visit transunion.com/sdoh-risk-attributes.