The COVID-19 pandemic elevated the healthcare system's focus on identifying and addressing social determinants of health (SDoH), or the nonmedical factors that influence someone's health and wellbeing. As efforts to advance health equity have become a top public health priority, a wide range of measurement tools to quantify, measure, and monitor SDoH have emerged. To achieve the most impact, it's important to strengthen the consistency and widespread use of these vital assessment tools.
Measurements critical in gauging impact of SDoH
Gathering and analyzing data is an instrumental aspect of health equity efforts. That's because this information can help identify where gaps exist and where resources should be directed. It also establishes accountability, explains a KFF briefing which points out:
“Without adequate data, inequities remain unseen and unaddressed."
Even as interest and commitment to assessing SDoH soars, measuring the impact of interventions remains a challenge. That's partially a result of the complex interactions between people's social determinants and their health status. Often, patients will experience multiple SDoH, making it difficult to discern the relationship between an intervention that targets one of those factors and someone's overall health.
Sharing, learning, and collaborating
Tailored interventions and best practices rely upon consistent and effective measurement. While there has been significant activity and interest surrounding the measurement efforts, coordination and consistent implementation are still a work in progress.
While a “single shared measurement system" for assessing SDoH may not be possible or practical, a shared understanding of the most commonly used indicators is helpful in evaluating impact and tracking progress, explain the authors of an article published in SSM - Population Health.
“Moving forward, more work needs to be done to share and learn from measurement strategies to advance cross-sector efforts to build healthier communities," authors wrote in the 2019 article.
SDoH measurements “an emerging industry"
Fast forward several years—and a pandemic later—and the appreciation of SDoH's critical role in health outcomes has grown tremendously.
“SDoH measure development is quickly taking the form of an emerging industry," wrote Dr. David Nash, a professor of health policy at the Jefferson College of Population Health in an article published in Medscape.
Numerous public, private, for-profit, and not-for-profit groups are creating metrics, resulting in a “measure mania" that Nash equated to healthcare's experience with quality and safety measurements. That trend could be problematic as too many measurements could deter providers from reporting them, he cautioned.
“Now is the time to be proactive in determining which SDoH measures really matter," Nash wrote.
Amidst growth, quality and quantifying issues persist
Indeed, the increased interest in SDoH has led to a proliferation of industries dedicated to identifying and addressing these unmet needs. Amid this tremendous growth, there hasn't been enough focus on the best way to approach each social determinant, explain the authors of an article published in Population Health Management.
“Moreover, little focus has been placed on rigorous evaluations of SDoH interventions employed by companies in this industry," they wrote. “Without an aligned effort between various stakeholders of all types into measurement, there is a risk of limited impact relative to both the need and to the industry's large investment and valuation."
Challenges in evaluating impact of SDoH interventions
In measuring and evaluating impact, SDoH industry organizations face several challenges, authors wrote:
- The measurements reflect an outdated expectation that there will be a cost impact in weeks or months. SDoH interventions may take more time to show up in both cost and clinical performance indicators.
- Patients often have multiple, interrelated social needs. Focusing on just 1 need may not address the intertwining social needs that require recognition and various interventions. They offer the scenario of a patient who cannot take time off work for a provider visit, afford the copay, or find childcare. Simply addressing a single need may not improve the clinical condition.
- SDoH organizations might not have access to financial or clinical outcome data, making it harder to measure or monitor impact.
- More broadly, SDoH interventions may extend beyond the healthcare industry's traditional focus on short-term cost-saving analysis.
Who is collecting SDoH data?
Another challenge: broadening the number of health systems that collect data and ensuring there is consistency in that collection over time.
Despite the heightened interest and growing availability of screening tools, just 83% of non-federal acute care hospitals are participating in SDoH data collection, according to a July-published brief from The Office of the National Coordinator for Health Information Technology (ONC). Among the hospitals that do collect the data, only 54% routinely collect it, a figure that is even lower among “lower-resourced" hospitals.
Standardizing and expanding data collection
The ONC analysis, which used data from the 2022 American Hospital Association Information Technology supplement, pointed to the value of capturing data in a standardized way. That's key for data sharing with other providers, something that can educate treatment. Among the report's other takeaways:
- Nearly three-quarters of hospitals used a structured electronic screening tool to collect social needs data.
- More than half of hospitals reported electronically receiving social needs data from outside sources, such as health information exchange organizations and other healthcare organizations.
- Hospitals used the social needs data for various purposes including informing clinical decision making, discharge planning, and referrals to social service organizations.
Collaboration critical to improving health outcomes
Amid the vast troves of data, there are people and organizations committed to collaborating in these efforts to improve consistency. In a 2023 article, the American Medical Association describes how healthcare stakeholders are working together to improve SDoH efforts.
“We recognize that collaboration is critical," said the AMA's Corey Smith, the Vice President for Informatics and Digital Products, in a recent webinar on the topic. “These problems are so foundational and so large—as it relates to data quality—that going it alone is not optimal."
A notable example is the Gravity Project, an initiative from the Robert Wood Johnson Foundation that is bringing together numerous SDoH stakeholders in an effort to develop data standards. Participants, who range from healthcare payers to technology vendors to government agencies, are working to create and implement standards for this data.
Diagnostic coding offers promise, but uptake falters
An important way in which health systems can identify patients with social risks comes via diagnostic codes known as Z codes. While the codes offer an effective way to coordinate care and tailor interventions, uptake of these codes has been slow, according to the authors of a 2023 article in The Hill. Researchers found that the use of Z codes was stalling across the board, from commercially insured patients to people using Medicare Advantage and Medicaid insurance.
Among the factors contributing to the slow update are “administrative burden, a lack of standards, a lack of provider awareness, as well as providers being ill-equipped to address these needs," authors wrote.
Technology could help integration efforts
Some of those challenges could be eased as technological tools advance. For example, a July-published JAMA Open study points to the potential of applying natural language processing to SDoH. Authors examined several different algorithms to extract information from electronic health records relating to people's housing challenges, financial stability, and employment status. Improving the ability to collect and measure SDoH could help clinicians and healthcare systems use these factors in their daily work to better understand patient populations—and their distinct social needs.
Those recent findings build on previously published literature that also describes this digital potential. According to findings published in the Journal of Public Health Informatics, integrating multiple datasets could improve population health strategies for addressing and identifying SDoH. In that study, authors reviewed multiple studies looking at how technology could be used to impact this growing field.
Among the technological tools the study referenced:
- Geocoding and using AI to translate patient addresses into SDoH data
- Combining multiple data sources for SDoH measurements, such as information from electronic health records and census data
- Using digital health technologies such as mobile health sensors and apps to gather SDoH data
Let RTI guide you
As SDoH collection and measurement efforts grow and evolve, RTI can help you navigate the changing environment and develop best practices to advance health equity. We can help you use digital tools to better understand and assess SDoH while also tailoring customized interventions that lead to improved health outcomes.