Unlocking health equity: The promise and challenges of integrating social determinants of health data
As the shift to value-based care continues, understanding the impact of social determinants on patient health becomes pivotal. However, the complexity of data collection and integration presents significant hurdles.
The diabetic patient’s care pattern followed an unhealthy cycle; every few months, he wound up back in a hospital’s emergency department, with dangerously high blood glucose levels. After being stabilized, the hospital gives the patient a couple months’ supply of insulin and sends him home. Within weeks, he’s back with a diabetic emergency.
The reason wasn’t some medical complexity. The patient didn’t have a working refrigerator to store the insulin. The medication lost potency before its expiration date and couldn’t restrain blood sugar levels.
This classic story is one that underscores the importance of non-medical factors in the health of people. In fact, there’s growing awareness that a variety of factors influence health to the greatest extent – medical care, while crucial in overcoming illnesses, plays only a minor role in maintaining a person’s well-being.
However, even though the importance of these social determinants of health (SDOH) are widely acknowledged as responsible for as much as 80 percent of a person’s health, the healthcare industry is only at the beginning stages of understanding the interrelationships of these factors and responding to them.
In part, it’s because of the incentives of fee-for-service healthcare – in essence, providers traditionally only get paid when they provide medical care. For providers, there’s no financial benefit to preventing illness. The insurance companies that pay for patients’ care also have not had a financial stake in the long game of maintaining beneficiaries’ health, and their information systems and work processes have been focused on claims management.
But that’s changing, as reimbursement methodologies change, value-based care takes hold and federal initiatives rebalance priorities to encourage population health and the other factors that impact overall health and wellness. And there’s rising awareness that health equity is important in ensuring access to better health for all, as well as to try to put the brakes on the nation’s soaring healthcare expenses.
Complex data challenges
Social determinants “are the conditions in environments where people are born, live, learn, work, play, worship and age,” according to a recent column published by the Office of the National Coordinator for Health Information Technology (ONC). SDOH affect health, functioning, outcomes and risks, and result in inequalities in conditions and outcomes, often because of poverty and the effects of racism.
Despite years of research pointing to the importance of social determinants, bringing data to the process has proven challenging. Meeting data collection requirements is difficult because so many factors influence health, and they lie outside the information typically recorded in electronic health records systems.
Past studies have found accountable care organizations have shown interest in meeting social determinant needs, but have struggled to integrate medical and social services, because of lack of data on patients’ social needs, as well as the lack of mature partnerships between ACOs and community-based organizations, and an overriding inability to determine a return on investment for this work.
But there’s increasing focus on addressing the determinants of health, with government agencies helping to focus attention. For example, this past March, the Centers for Medicare & Medicaid Services released an updated Framework for Health Equity to “advance health equity, expand coverage and improve health outcomes for the more than 170 million individuals supported by CMS programs,” with the intent of “identifying and working to eliminate barriers to CMS-supported benefits, services and coverage.” One of the agency’s priorities includes improving its collection and use of comprehensive, interoperable, standardized demographic and SDOH data.
Additionally, the Department of Health and Human Services is working on Healthy People 2030, which sets data-driven national objectives to improve health and wellbeing over the next decade. HHS notes that SDOH will be a key focus of the program. “In line with this goal, Healthy People 2030 features many objectives related to SDOH. These objectives highlight the importance of ‘upstream’ factors — usually unrelated to health care delivery — in improving health and reducing health disparities.” One of a more than a dozen workgroups focused on the program is working solely on SDOH.
For its part, ONC is working with federal agencies and industry stakeholders to “advance the electronic exchange and use of SDOH data.” ONC is focusing efforts on guiding the development of health standards, developing policy to overcome SDOH interoperability challenges and data use, supporting state and local governments to build infrastructures for SDOH data, and driving innovation in care delivery.
The federal efforts will help to focus more attention on health equity efforts and cross-industry collaboration. A wide range of initiatives are underway, particularly among ACOs and Medicare Advantage programs serving Medicare beneficiaries and Medicaid recipients, but it’s clear that more information and sharing is needed to achieve broad, nuanced solutions.
A whole of industry challenge
Gathering and sharing SDOH looms as a challenge because the answer to meeting social needs doesn’t rely within one industry segment – it requires participation, collaboration and data liquidity among various components, including some who have traditionally not worked together, who have been competitors or antagonists in managing healthcare.
SDOH is part of the bigger drive toward value-based care and measuring quality in care delivery, says Amol Vyas, recently named vice president and head of interoperability for the National Committee for Quality Assurance (NCQA). Federal initiatives are important to making progress on SDOH by “having a federally blessed data set, and having the information required … so the industry can work out a way of enabling exchange of those elements through data-sharing arrangements.”
The importance of having widely accessible and shareable SDOH data was among the learnings of the COVID-19 pandemic, says Pravin Pant, vice president for advanced analytics at ZeOmega, a technology provider with offerings for population health and analytics.
“We knew SDOH was important, but didn’t really feel it until COVID-19,” he explains. “Then, we really understood the disparity. Now, SDOH has become a priority because we understand that if we can manage the social risk, your clinical outcomes do change, and the best clinical outcomes become really possible.”
The key to success with SDOH is having enough well-rounded data to identify the social needs that have a downstream impact on people’s health, says Karen Iapoce, senior director of government solutions for ZeOmega and a former nurse and discharge planner. Pulling information is very important to create cohorts of a population, “having the ability to grab all that information and drive strategic programs to meet the needs of that population.”
Doing that effectively means “bringing multiple entities to the table, and that’s the conversations that health plans are having,” Iapoce adds. “It needs to be on a pure person-to-person level, to find the person I’m trying to help and then put services in place that meets what they need.”
Done well, effectively meeting SDOH insufficiencies can pay dividends with better member engagement and increased trust, as well as a wider sphere of influence, she predicts. “It’s likely that if one member of a family has food insecurity, everyone in the household is struggling with food insecurity.”
Easier said than done
But data collection and sharing to enable effective delivery of SDOH is hampered by the lack of standards, and that’s challenging for multiple reasons, says Lynda Rowe, senior advisor for value-based markets for InterSystems and co-chair of WEDI’s health equity workgroup.
On the one hand, current clinical records systems weren’t designed to gather SDOH data, in part because they were intended to capture information related to patients’ medical information for the purpose of billing for services.
“One would want to understand the data through the lens of race or ethnicity, and the problem has been we don’t capture that. What gets regulated is what we capture,” Rowe says. SDOH-related data often is noted in clinical records but is unstructured – typically in clinical notes – and thus is difficult to analyze and draw conclusions from and act upon.
“How do you report on this data, because the EHR does not support it at that level of granularity,” Lowe says. “If the provider doesn’t capture a code for food insecurity, people don’t know that it was discussed.”
But some of that data capture is now capable of being captured through the second version of the United States Core Data for Interoperability, which data classes and elements involving SDOH, specifically SDOH assessments, problems and health concerns, goals and interventions.
Additionally, the Gravity Project – an accelerator program of HL7 to develop use cases for the Fast Healthcare Interoperability Resource (FHIR) standard – is looking to build consensus on data standards to improve the sharing of information surrounding SDOH.
The Gravity initiative, launched in May 2019, is working on three concurrent workstreams – involving terminology, technical aspects of including SDOH data within clinical systems and sharing it through FHIR standards, and pilot programs that test evolving terminology and data exchange standards.
The Gravity Project reports it has more than 1,800 members, including clinical provider groups, community-based organizations, federal and state agencies, and payers, among others.
And last year, ONC launched a national Gravity Project Pilots affinity group through a partnership with HL7 and other organizations to pilot the SDOH Clinical Care FHIR Implementation Guide (SDOH CC IG) “as a way to further the development and adoption of social determinants of health (SDOH) standards.”
“Our combined efforts are expected to demonstrate how best to advance our nation’s technical infrastructure to enable SDOH interoperability as supported by ONC’s United States Core Data for Interoperability (USCDI) Version 2,” ONC noted in its blog. “The ability to use and build from established standards in real-time and as part of screening practices that help identify specific needs related to food, housing, and transportation insecurity is an important step in enabling more coordinated care and timely assistance or interventions needed to improve health outcomes.”
Efforts show the complexity of SDOH
Despite the challenges, many healthcare organizations are implementing efforts to assess SDOH concerns and then meeting these needs to improve health.
For example, Medicare Advantage plans are increasingly assessing beneficiaries’ SDOH needs and working with community-based organizations to meet those needs and improve health outcomes. Approaches being used by Medicare Advantage plans include assessing safety in the home, food insecurity, lack of access to transportation or lack of family and social support.
Medicaid is also enabling efforts to address social needs that impact health through Section 1115 waivers, as both federal and state governments have identified meeting SDOH needs as a key priority for Medicaid recipients. Rowe says waiver programs in California, New York, North Carolina and Oregon have showed creativity in designing programs. “They have demonstrated how you can use federal match dollars and get flexibility in how to use them. The thought is that if you start looking upstream at the real causes of illness, you will save money eventually.”
As more health coverage programs move to value-based care methodologies, there is likely to be more focus on the causes of diseases and preventive measures, as healthcare organizations will be looking to minimize the total cost of care for populations. That will bode well for addressing SDOH shortfalls to improve care quality and costs.
“We are just beginning to talk about quality measures and SDOH, all in the spirit of helping patients navigate care, so they can see a 360-degree view of their care,” says Vyas of NCQA. Interoperability will aid this, even though there’s a long way to go. “I think we can get to an interoperability nirvana where things will just scale up and work, whether through TEFCA or any other way we can create these data APIs and figure out a way to scale them. When trust and security becomes part of the platform, we can talk about use cases that will help patients get that 360-degree view.”
Current experiences with SDOH programs show the importance of data sharing and analytics to be able to define populations precisely and then use them to meet individuals’ needs in nuanced, tailored ways, concludes Pant of ZeOmega.
“If you want to understand a population, it has to be data driven, coming from a variety of sources. Then you can analyze it and run it through artificial intelligence and machine learning,” he says.
“Then, once you get that insight, now it can be applied to the clinical perspective and they can be converted into interventions that can be applied to health equity. That needs to be heavily data driven – not just claims and EMR data, but also from publicly available databases to know what the community looks like today, and then activate certain workflows to mitigate issues.”