According to the Centers for Disease Control, social determinants of health have a profound impact on health outcomes – much more, in fact, than the actual delivery of healthcare services.
The health of people and communities is heavily influenced by such factors as socioeconomic status, education, social network support, access to care, access to transportation and employment. Therefore, organizations that are committed to improving the health of populations should not overlook the social and economic conditions impacting the well-being of individual members.
Healthcare is continuing to shift from fee-for-service payment models to models that reward providers for delivering high-quality, cost-effective care. To achieve clinical and financial success in a value-based care world, providers need deep insights into the health of their patient populations.
For example, under many value-based arrangements, providers are penalized when a patient is readmitted to the hospital within 30 days of discharge. To minimize this risk, hospitals must identify patients who are more likely to be readmitted and proactively take measures to keep those individuals healthy.
Providers can assess risk in a variety of ways, though some methods yield more precise results than others. A care manager could simply review the patient’s discharge summary and current medical record to get a snapshot of their health status. If the organization wanted to dig deeper, they could review aggregated data that identify typical social and economic conditions for individuals living in the patient’s same ZIP code.
Ideally, however, the provider needs data that goes beyond a summary of the patient’s medical treatment and aggregated population statistics. To more accurately assess an individual’s 30-day readmission risk—or his or her risk for any adverse event—providers need social determinants of health data that is patient-specific.
For example, a patient might be at higher risk for readmission if, among other factors, she is struggling financially and unable to pay for medication. An individual may be at an increased risk for an adverse event if he fails to receive proper follow-up care because of a lack of access to reliable transportation. Or, a patient who lives alone without in-home assistance may suffer a setback if she doesn’t have anyone to verify that she is eating properly and taking medications as prescribed. When providers are able to identify at-risk patients, they can intervene early and offer solutions that address an individual’s specific needs, thus increasing the likelihood of positive outcomes.
Social determinants of health data can also help predict the impactability of services. For example, a health system that offers both telephonic follow-up and follow-up to patients’ homes might learn through the analytics that a relatively expensive home visit is the more impactful option than a less expensive follow-up phone call for a patient who is known to live alone. In contrast, the analytics also identify which patients will benefit from less expensive calls.
Mission Health Partners (MHP) is a Medicare Shared Savings Program Accountable Care Organization committed to improving the quality of healthcare for its Medicare beneficiaries and to reducing the cost of care delivery. In an effort to meet their quality of care and financial objectives, MHP adopted a social determinants model of care coordination that focuses on identifying gaps in care, including those created by socioeconomic factors.
MHP serves over 90,000 commercial and ACO members across 18 North Carolina counties. The ACO, which scored over 97 percent for quality for 2016, employs an upstream approach to reduce utilization and manage post-acute care costs. They rely heavily on analytics to identify their highest risk patients, as well as to predict which individuals would be most positively impacted by specific services. This enables MHP to not only find the patients at highest risk for an adverse event but also identify those whose outcomes would most likely be improved with specific interventions.
According to MHP’s Medical Director Rob Fields, MD, having ready-access to social determinants has helped to individualize patient care. “When high-risk patients are identified, we’re able to partner with agencies in the region to close gaps so that patients are empowered to better manage their care. This model has allowed us to drive the best outcomes in most efficient way possible.”
Traditionally organizations rely on claims and clinical data to predict population risk. MHP, however, has boosted the accuracy of its predictions by 25 percent since incorporating social determinants of health data into their analytics reporting tools. The additional precision has been instrumental in helping MHP to identify which programs and services will have the biggest impact on specific patients’ outcomes.
To achieve financial and clinical goals, providers and healthcare systems need predictive modeling tools that take into account social determinants of health. By leveraging social determinants of health data, organizations can glean expanded insights into their patients’ health and customize their care plans to be more impactful.
Organizations such as MHP are experiencing early success by incorporating social determinants of health details into their risk analysis programs. With more comprehensive information on the factors influencing patient health and outcomes, health systems are better equipped to drive quality outcomes and achieve overall success in the expanding world of value-based care.
Source: Michael Cousins, Health Data Management