Jul 27, 2022
Inside Cigna's Data-Driven Approach to Health Equity

A health disparity is an avoidable and unfair difference in health status between segments of the population. Health disparities negatively affect groups of people who have experienced greater obstacles to health based on their race, ethnicity, education, literacy, income level, language, culture, age, sexual orientation, gender identity/expression, disability or geographic location. Health equity, in turn, is the attainment of the highest level of health for all people.

That is why, for nearly 15 years, Cigna has promoted the identification of health disparities and influenced the development of solutions that result in improved outcomes among our customers, our workforce, and in the communities we serve.

We do this by utilizing a variety of data sources and tools that allow us to analyze customer populations to understand their potential health disadvantages. For example, our proprietary Social Determinants of Health Index (SDI) helps us identify communities of Cigna customer populations whose overall health status and utilization of care are negatively impacted by social determinants of health (SDOH) and where additional resources may need to be deployed to reduce barriers to optimal health. We also use the index to identify customers who are at increased risk for poor health and health care utilization, based on where they live, and who might need personalized solutions to achieve better health and affordability.

“The insights drawn from this analysis can lead to client-specific recommendations such as benefit changes, program enhancements, and targeted communications and assist customers in maximizing exposure to community resources. We handle the diverse needs of our customers by utilizing data sources, programs, services, training, pilots, and more.”Dr. Neema Stephens, national medical director for health equity at Cigna

To better understand the SDI and how it helps us drive health equity, we sat down with Dr. Stephens, who spoke to what the index is, how it works, and the impact it has helped us make.

What is the SDI?

The SDI is a composite score that operationalizes a set of SDOH factors at the census tract level in the United States. The score can range from 0-100, with a higher number denoting a higher exposure to SDOH-related obstacles. We also have a categorical characterization of the numerical score denoting low, medium, high, and very high exposure to SDOH-related obstacles.

What types of measures does the SDI take into account?

The SDI is composed of 22 measures, which fall into six domains of SDOH: economy, education, culture, health, infrastructure, and food access. The SDI itself is proprietary, but the measures in each domain are sourced from publicly available data from sources such as the U.S. Census and U.S. Department of Agriculture. The index is not meant to depict an individual's actual situation, as the data is sourced at the neighborhood level, not at the individual level.

How do we use the SDI?

We use the SDI in a variety of ways, such as market identification, pilot design and evaluation, and to inform the creation of new products and services.

For example, we leverage SDI to produce clinical insights that help us prioritize customer interventions within pilot design and monitoring, and as part of program evaluations and enhancements. We also use the index to identify geographic areas with an increased risk of facing SDOH-related obstacles that negatively impact health outcomes and health care utilization. For example, the SDI was used as an initial criteria, along with identified health disparities in diabetes-related outcomes (diagnosis, management, and utilization) to identify Houston as the primary initial site for a pilot program involving community health workers. It was also used as part of the criteria to identify markets where significant racial/ethnic disparities existed in pre-term birth rates, and we are now assessing the effectiveness of interventions designed to reduce these disparities.

We leverage the SDI to better understand the needs of our customers and design and implement multi-pronged pathways for interventions in collaboration with providers and clients. SDOH is a key strategic goal embedded into our value-based care programs in partnership with Cigna Accountable Care (CAC) groups. For example, provider groups are incentivized to proactively screen for SDOH needs. In addition, Cigna gives provider groups SDI-related insights on their patient population so doctors can better understand the potential needs of their patients.

With our employer clients, we use geospatial analytics tools in conjunction with the SDI to help them understand the potential health disadvantages their employee cohorts may have based on their geographic location. The insights drawn from this analysis can lead to client-specific recommendations such as benefit changes, program enhancements, targeted communications, and assists clients in building healthy work cultures.

How does the SDI help you to do this?

Our predictive models include a proprietary algorithm with an array of inputs such as customers’ demographic information, claims information, clinical information, imaging, laboratory, prescriptions, biometrics, and program participation data. 

We add the SDI to predictive models to improve their ability to identify and prioritize customers at increased risk for poor health outcomes and utilization, then deploy additional support and resources to them.

Can you provide a few examples?

Absolutely. The Moment Model is a suite of predictive models that predicts chronic disease deterioration up to one year in advance. The models were developed in 2020 by Cigna’s digital and analytics data science teams in partnership with clinical experts. The models leverage diverse clinical data, SDOH data, and machine learning/artificial intelligence to predict an individual’s future health and pair high-risk customers with personalized recommendations for high-value interventions and actions.

By including SDI in the Moment modeling process, we found that SDI was a top predictor of risk in 20 models. As an example, there was an elevated risk of heart attacks and strokes for individuals living in higher SDI areas, and by identifying this increased risk we were able to prioritize clinical and social needs interventions for these individuals.

How are we using the SDI to assess how SDOH-related needs are impacting health care utilization?

We have analyzed utilization data by SDI categories – across an array of health and health care utilization-related outcomes – and can see that those who reside in a high or very high SDI census tract have a disadvantage compared to those who reside in low SDI census tracts. This data is then leveraged in a number of ways, such as to inform pilot design and prioritization, solution enhancements, and new solution development.

That’s so interesting. Can you provide an example?

Yes. We found, for example, that customers that do not receive behavioral outpatient care or those who have a low number of visits (i.e. one or two visits) were more likely to be living in high SDI areas. They also were more likely to have a household income of less than $50,000. To help address this, we have begun work around network expansion and innovative patient navigation approaches to get people to the right care, including virtual/digital, at the right time with fewer barriers.

For example, we are helping customer navigate care by introducing options that are free or low cost, such as Happify and employee assistance plans (EAPs) for behavioral health clients or by leveraging their EAP. We will continue to drive our customers to cost-effective behavioral solutions that are clinically appropriate.

Besides leveraging the SDI, how else do you asses customer needs?

We’re leveraging SDOH screening and assessments. Aside from using the SDI derived from secondary data sources to help us understand the social context of where our customers reside, programs like Medical and Behavioral Case Management collect primary data by screening and assessing for unmet health-related social needs of customers.

So, for example, when a customer is referred to medical and behavioral case management, the case manager conducts an immediate health needs assessment (IHNA) in the first interactions. The IHNA includes a SDOH-related screening and assessment that is captured within TruCare, a case management platform.

If the customer expresses an SDOH-related need such as transportation, caregiving, housing, or food insecurity, then the case manager uses the findhelp.org platform. Findhelp.org is the nation’s leading social care network technology, it is a search engine with information on 55,000+ community-based organizations across the nation that address SDOH-related needs. The customer shares their ZIP code with the case manager, who then conducts a search to tend to the needs identified.

In 2021, Cigna’s case managers conducted approximately 158,000 SDOH screening/assessments, and 48% of those who were assessed indicated that they had at least one SDOH-related need. In 2021, there was also a significant increase in findhelp.org utilization vs. 2020 where searches, interactions, and connections were up 186%, 294%, and 256% respectively.

Cigna is Committed to Health Equity

For more than a decade, Cigna has promoted the identification of health disparities and influenced the development of solutions that result in more equitable health among our customers, our workforce, and in the community.

Learn more