How social determinants of health are reshaping risk management in healthcare

In healthcare, the traditional tools for risk management—claims data, clinical history, age, and gender—only tell part of the story. To understand why patients get sick, why costs spike, and why outcomes vary widely between seemingly similar populations, we need to look beyond the exam room.

That’s where social determinants of health (SDOH) come in. These are the nonmedical factors, such as housing, income, food access, transportation, education, and social support that influence as much as 80% of health outcomes, according to recent data.

For actuaries, underwriters, and payors, a deeper understanding of SDOH is driving a shift in risk management models. No longer a fringe concept or public health talking point, SDOH has become a strategic asset for understanding, pricing, and managing risk. Here's how SDOH contributes, impacts, and plays into their risk management processes.

What traditional risk models miss

In the past, the traditional methods of determining and evaluating risk in healthcare often relied on clinical diagnoses and a patient’s claims history. These factors do a decent job predicting cost and utilization based on known clinical data. However, they assume the playing field between all patients is level. It’s not.

Take two patients with the same diagnosis—say, hypertension. One has a steady job, stable housing, and easy access to a pharmacy. The other works two jobs, struggles with housing insecurity, and lives in a food desert. On paper, they look the same. In reality, one is far more likely to end up in the ER.

These non-medical factors are powerful drivers of health outcomes and can significantly exacerbate existing conditions or lead to new ones. Without SDOH, the risk profile is inherently incomplete and can lead to underestimating or miscalculating true risk, incorrectly priced premiums, and underfunded care coordination, leading to higher costs and potentially worse outcomes down the road.

How actuaries use SDOH to improve financial planning

Actuaries are the architects behind financial risk models in healthcare. Their job is to anticipate cost trends, forecast utilization, and ensure that pricing, reserves, and contracts are aligned with expected risk.

For these folk, the value of SDOH lies in what it reveals about population health risks that clinical and claims data can’t fully explain. With rising pressure to predict healthcare costs more accurately, and design financial models that support equity and efficiency, actuaries are turning to SDOH to fill in the gaps.

Refine cost forecasting

One of the key ways actuaries use SDOH is to refine cost forecasting at the population level. By layering in data on housing instability, food insecurity, or transportation barriers, often at the ZIP code or census level, they can build more realistic projections of healthcare utilization and spending, especially for Medicaid, Medicare Advantage, or employer-sponsored populations. These insights help inform not just pricing but also reserve setting and capital planning.

Improve predictive risk models

SDOH also improves the performance of predictive risk models. Traditional inputs like age, gender, and chronic conditions still matter, but SDOH variables often explain why two patients with identical diagnoses follow very different cost trajectories. Adding context like housing status or access to transportation makes models sharper, more responsive, and better aligned with actual outcomes.

Model ROI of non-clinical interventions

Finally, when healthcare organizations invest in non-clinical interventions like meal delivery, rideshare programs, or housing support, actuaries are the ones modeling the ROI. They analyze whether these programs reduce avoidable ED visits or hospitalizations, and whether the downstream savings justify the upfront cost. In this way, SDOH isn’t just a tool for risk scoring—it’s part of the financial strategy.

Underwriters use SDOH for smarter risk selection and pricing

For healthcare underwriters, the job is to assess risk, set appropriate premiums, and ensure that coverage terms align with the actual needs and cost potential of a population. Traditionally, this process relied heavily on historical claims data, demographics, and clinical trends, but underwriters are increasingly turning to SDOH data to uncover risk signals the old models may have missed.

Similar to actuaries, underwriters also analyze SDOH trends at the population level to gain a clearer view of the external factors that influence healthcare utilization. Unemployment rates, housing quality, transportation access, and education levels are all valuable insights when underwriting employer groups or government health plans.

For example, an employer group operating in a region with high housing instability or food insecurity might be more prone to chronic condition complications and emergency care overuse, even if their claims data appears average. By integrating SDOH into the risk selection process, underwriters can make more accurate pricing decisions, structure benefits more strategically, and identify where to recommend care management programs or social support services.

SDOH are becoming a cornerstone of health insurer strategies

Health plans and insurers, as payors, are constantly striving to manage costs, improve member health, and ensure access to quality care. They are increasingly integrating social risk data into their processes to design smarter networks, fund more targeted interventions, and manage rising costs at the root.

One of the most impactful uses of SDOH among payors is in identifying members who are at risk of poor outcomes despite having minimal claims history. By incorporating SDOH data, payors can flag individuals who may fall through the cracks of traditional risk models. This allows care teams to intervene earlier with case management, social support, or community resource referrals before minor issues become major medical events.

In network design and benefit structuring, SDOH data plays a growing role. For example, in areas where access to care is limited by transportation or provider shortages, payors may prioritize telehealth coverage or partner with mobile health units. If food insecurity is high in a given region, they may support nutrition benefits or community-based care programs through value-based contracts.

Lastly, SDOH is informing how payors measure and incentivize health equity. Many are aligning their performance metrics, provider payments, and quality scores with outcomes that reflect the impact of social and economic conditions—not just clinical care. This means tracking things like preventable hospitalizations, follow-up care rates, and disparities in maternal health, often segmented by social risk factors. As a result, payors are shifting from reactive cost management to proactive health strategy, potentially leading to healthier members, better engagement, and a more resilient system overall.

The future of risk management is holistic

Ultimately, the true power of integrating social determinants of health into risk management lies in its ability to humanize healthcare. By recognizing that a person's health is intrinsically linked to their life circumstances, actuaries can build fairer models, underwriters can make more informed decisions, and payors can design more compassionate and effective programs.

Of course, high-quality data is critical for risk management professionals to do their jobs effectively. Our Atlas All-Payor Claims dataset offers powerful insights that can help you deepen your understanding of a specific population or geographic area. In addition, our Population Intelligence product has data on millions of unique consumers, including SDOH-modeled data to help you build, customize, segment, and analyze audiences across your market.

To learn more about either of these solutions and how they can help you get clarity in the complex healthcare landscape, start a free trial with Definitive Healthcare today.