Healthcare providers, payers, community-based organizations, researchers and government agencies are on the same page: Addressing social determinants—such as homelessness, food insecurity, addiction and poverty—likely has a tremendous impact on population health.
In fact, social programs such as housing assistance, food pantries and behavioral health offerings can have a much greater impact than clinical care and medical treatments.
As population health models and value-based payment systems gain traction, healthcare organizations must be able to track, manage and measure the services patients receive outside of their hospitals, clinics and physician offices for quality reporting and effective care management.
An abundance of social services
Although access to services vary from community to community, there’s a potentially rich trove of resources for those in need. Food insecurity, for example, could be addressed by multiple services, such as senior centers that offer low-cost lunches, volunteer-run food pantries or Meals on Wheels programs. Behavioral health support could come from 12-step programs, veterans’ organizations that hold free group therapy sessions, or through other local social service agencies. Better transportation services might come in the form of reliable public transit or, in its absence, free or subsidized ride-hailing services such as Uber of Lyft.
Want to publish your own articles on DistilINFO Publications?
Send us an email, we will get in touch with you.
Ironically, the fact that there are so many possible solutions—and the fact that those services (or the lack thereof) can vary greatly from one neighborhood to another—poses a major challenge for those trying to improve population health. To truly reap the benefits of the available programs and to identify (and close) gaps in services, all these organizations must share clean, accurate and up-to-date data about the individuals they serve.
As health systems begin working more closely with behavioral health and community-based organizations, they must institute tools that can integrate information and improve data quality to galvanize their efforts. Just as there are myriad services, there is a great variety of systems being used to track these patients including a growing number of dedicated SDOH platforms such as Healthify, NowPow and Aunt Bertha.
Data quality is key
Healthcare leaders can’t address SDOH without understanding the populations they serve and without the capacity to drill down and create a comprehensive view and database of the health of individual patients. That’s impossible to do with inaccurate, incomplete or duplicative patient data. Organizations need a single source of truth; a “golden record” that links the right patient to the right data, that spans multiple systems in a standardized way.
A recent position paper from the American College of Physicians outlines strategies to address SDOH and reduce barriers to care. Among them, health information technologies to enhance the patient-physician relationship, facilitate communication across the care continuum and support improvements in patient care.
In January, the Office of the National Coordinator for Health IT (ONC) announced updates to its Interoperability Standards Advisory, including four new focus areas that address SDOH in the areas of drug use, food insecurity, access to affordable housing and transportation. “As factors like these can greatly impact one’s overall health, ensuring this information is known, and captured in clinical systems and available to providers is important,” ONC said.
With automated, robust data governance processes and tools to aggregate, link and de-duplicate information, records can cascade across the enterprise to ensure that an individual’s data from internal and external sources, including behavioral, public health and community-based organizations, is accurate and avaiable. This helps organizations to identify gaps in social needs and focus on how best to fill them.
An Enterprise Master Patient Index (EMPI), whether in the cloud or on-site, helps healthcare organizations simplify patient record matching, electronic medical record management and quality reporting more efficiently. There’s a cost-benefit too: research shows that healthcare organizations without an EMPI have an average duplicate patient record rate of 18 percent. This can cost a hospital $1.5 million annually.
Leading EMPI products come with location intelligence or geo-coding of data. This enables patients, providers, and service delivery locations to be precisely mapped and the distance between them to be used. It also enables much more granular understanding of what conditions exist where in the community and among populations.
Further, data that is clean, accurate and complete, is well prepared for analytics. Complementing extensive clinical data with SDOH data enables care managers to make more informed decisions and apply data-rich insights into a patient’s treatment plan. Data scientists can leverage their organization’s EMPI and location data to identify clinical trends, such as a high prevalence of diabetes, heart disease and other chronic conditions. That data, in turn, can inform service line offerings.
According to the CDC, data can be a catalyst for improving community health and well-being. “Understanding data on social determinants of health, such as income, educational level, and employment, can help focus efforts to improve community health.” In other words, if you don’t have reliable, accurate and accessible data to identify gaps in social services and you can’t share that data in a seamless, standardized way, how can you ever close them?
Gaining access to high-quality patient data across the community will be catalyst for improving population health. With a greater understanding of their patients and the socioeconomic barriers that place their health at risk, providers can begin to implement strategies that improve patient engagement and outcomes, reduce cost and duplication of services, and enhance clinical decision-making and coordination of care.
Source: Health Data Management