As the healthcare industry moves toward digital maturity, it faces complex data challenges. The urgent call for greater interoperability, the need to streamline data capture and analysis, and the need to uphold patient privacy regulation are all thorny issues that must be addressed.
One of the challenges in healthcare in which data could play a significant role is health inequity. Understanding the causes of health inequity is the first step in addressing it properly. To that end, it is imperative for healthcare organizations, community social services, and health plans to identify and analyze key social determinants of health (SDoH).
Role of SDoH in healthcare and health inequity
The U.S. Department of Health and Human Services defines social determinants of health as “the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.”
SDoH plays a significant role in overall health, with healthcare researchers asserting that social determinants have a 15 percent impact on a person’s longevity, compared to health care itself at just 10 percent, based on research sponsored by the U.S. National Institutes of Health (NIH) and multiple other sources.
(Source: New England Journal of Medicine)
Samantha Artiga, Vice President and Director of the Racial Equity and Health Policy Program at KFF, notes regarding SDoH: “Addressing social determinants of health is not only important for improving overall health, but also for reducing health disparities that are often rooted in social and economic disadvantages.”
Challenges in collecting, sharing, and leveraging SDoH data
Addressing SDoH issues in any meaningful way starts with data collection with an end goal of analysis, knowledge and actionable insights. However, there are significant challenges to overcome. First, there is a lack of consensus among the various stakeholders as to what constitutes a social determinant of health. Rubrics may vary from organization to organization, or from state to state.
Then, there is the lack of standardized, validated SDoH measures. The absence of uniform collecting and reporting methodologies limits the ability of healthcare organizations and community social services to create and implement a strong strategy to address SDoH deficiencies. Trying to leverage non-standardized data for analysis can lead to erroneous hypotheses based on inaccurate “apples to oranges” comparisons.
Further challenges include technical obstacles in sharing SDoH data across multiple organizations with disparate systems that lack interoperability, difficulties in extracting pertinent SDoH data from EHRs, administrative burden , and the imperatives that come with maintaining the appropriate level of patient privacy to remain compliant with regulatory requirements.
A recent IDC Perspective report sums the situation up nicely, noting: “Integrating SDoH data is difficult and requires skills and technology not typically available within most healthcare organizations.”
Building your SDoH analytics strategy
SDoH data challenges are not, however, insurmountable. You can address them with the right skills, processes, and technologies.
The IDC report offers three key recommended actions for organizations getting started with SDoH initiatives:
- Define your organization’s strategy to address health inequity and understand the resources required to execute that strategy.
- Seek assistance from third-party vendors for the services and technology required to execute and monitor performance.
- Establish private/public partnerships and infrastructure if your strategy involves community-based organizations.
Start with the end goal in mind
A solid SDoH analytics strategy starts with a focus on the use cases for your SDoH data. Why? The sheer volume and diversity of data available precludes thorough analysis of every data point for most organizations. Narrowing down your focus to where you can most likely make the biggest impact sets your organization up for success and keeps you from trying to “boil the ocean.”
Once you have determined your area of focus, you can set your strategy, allocating the needed resources to implement it.
Choose your vendor wisely
Vendors that offer SDoH analytics come in a variety of flavors. Some vendors maintain open source data and third-party consumer data, which they integrate with your clinical data to calculate a social vulnerability index.
Other vendors maintain SDoH data and provide analytic services to help you determine the most appropriate data for collection and analysis. They may also go the extra mile and interpret the data to provide insights for you.
Then, there are vendors that use fully customized SDoH data sets drawn from your organization and integrate them with your clinical and financial data.
The type of vendor you choose is largely dependent on your approach to SDoH strategy. Regardless of which vendor you select, you will need to confirm that the vendor can adequately ingest, cleanse, and integrate SDoH data with your existing systems.
Partner with the right community-based organizations
As is the case in vendor selection, thinking strategically about your end goal will help you choose the right community-based organizations with which to partner. Look for a partner with the correct infrastructure in place to work with you seamlessly.
TIBCO: your partner for SDoH analytics
TIBCO Omni-HealthData® features built-in SDoH analytics. The platform ingests publicly available SDoH data and integrates it with your internal clinical, operational, HR, cost, and survey data to deliver insights that can inform your SDoH strategy as well as your organizational strategy and vision. With easy-to-use, intuitive dashboards and data visualizations, Omni-HealthData provides a holistic view of patient needs that goes beyond clinical care and drives your organization’s capabilities in building the future of healthcare, with data.
Steven Kahn, Director, Product Management for Omni Vertical Solutions at TIBCO, is responsible for designing the industry standards-driven models of our Omni Vertical Solutions. He also leads the team responsible for defining and creating the consumption, metric and presentation views, and industry metrics we offer in the verticals. Additionally, he and his team are responsible for creating and maintaining industry reference data content we provide to customers. He has spent nearly 40 years in the IT industry in roles from programmer through enterprise architect in Fortune 100 companies. His experience includes over 14 years in Big 6 consulting firms architecting solutions in industries such as healthcare, life sciences, pharma, telecommunications, high-tech, retail, CPG, financial, and many more.
IDC, Toward Health Equity — Social Determinants of Health Analytic Approaches, Doc # US47608121, April 2021