The new frontier: Beyond clinical care to holistic patient well-being
MetroHealth moves to embrace social determinants of health and combine factors with advanced analytics to meet patients’ individual needs.
For many patients, the barriers to achieving quality healthcare stretch beyond the clinic. Reliable transportation, affordable quality nutrition, dependable utilities, full comprehension of their medications and other factors limit their ability to maintain wellness.
Awareness of these barriers and actions to address them are just as critical to an individual’s health as access to their complete clinical history and should be considered when designing a treatment plan. Yet, astonishingly, a significant majority of healthcare providers only perceive a mere fragment — often fewer than 20 percent — of this intricate puzzle that constitutes a patient's life.
For example, Cheryl Smith, a 62-year-old Cleveland resident, has dedicated 40 years of her life to being an airline gate attendant. With the juggling act of managing work, family and mounting health challenges, her life’s path has been rocky. Decades of quick fixes in her diet led to battles against Type 2 diabetes, hypertension and a newly declared adversary — rheumatoid arthritis. An unexpected, severe health dip during one of her shifts culminated in a problematic ER visit, adding to her already growing medical expenses.
What if her healthcare providers had a complete 360-degree view into her life? Treatment plans could have been more tailored, strategic and effective.
MetroHealth’s Institute for H.O.P.E. realizes the importance of social determinants of health (SDoH). MetroHealth is identifying patient and employee needs through SDoH screening, making it the foundation for care redesign that addresses the root causes of undesirable outcomes and inappropriate health system utilization.
MetroHealth teamed with the EY organization to pilot and validate an innovative approach to improving patient and employee experience using smart health analytics. MetroHealth and EY used advanced analytics to understand patients’ needs holistically, proactively identify and stratify risk, and predictively locate patients needing intervention and guidance on proper utilization of the health system.
The goal was to provide intentional and timely care through improved and augmented data insights, including SDoH. EY, in collaboration with MetroHealth, refined and validated models and generated additional data points with a high level of confidence, moving toward MetroHealth’s goal to proactively identify high-risk patients.
The healthcare landscape
America brims with stories just like Cheryl’s. Recognizing this glaring reality, there’s a seismic shift underway in healthcare toward value-based care and overarching health equity. Effective from Jan. 1, 2023, new and revised requirements to reduce healthcare disparities apply to organizations in the Joint Commission’s hospital accreditation programs.
The shift toward value-based care models encourages a focus on outcomes rather than incentivizing overutilization. Identifying social, behavioral and clinical risk facilitates personalized care and targeted interventions, both of which improve outcomes.
To succeed in value-based care, healthcare organizations need to rapidly acquire and scale a mix of organizational, care management and technology capabilities. This pilot focused on providing technological capability through insights about a patient’s risk factors at the point of care.
With the right use of analytics, health systems can intervene to address social determinant risk and prevent a health crisis, reducing the strain on nursing and clinician resources. Early identification of high-risk patients through analytics supports more preventative and precise care.
Action vs. reaction
MetroHealth is focused on improving the health of communities through the proactive identification of high-risk individuals, including high utilizers. Through forward-thinking initiatives like the Food as Medicine project, the focus sharpens toward laser-precise, high-impact interventions.
While it has obtained some information from Epic’s SDoH tool, one of the goals of teaming with EY was to reduce reliance on care coordinators surveying patients and look at other real-time data sources to reveal more timely identification of a patient’s SDoH risks.
The pilot has preliminarily increased the amount of data and insights currently available about individual patients related to social determinant needs. Operationalizing these models would further augment the data and insights available about patient risk stratification and high utilizer risk.
During the pilot, EY teams and MetroHealth collaborated to predict health risks related to social determinant challenges and high utilization within the next year for MetroHealth’s 65-plus population. EY worked with MetroHealth to determine the appropriate electronic medical records, inclusive of SDoH survey data, to utilize for the models. Public records data for each individual powerfully augmented existing SDoH data.
After analysis, the data was incorporated into the two models that were validated during the pilot — a social and clinical risk stratification model, and a high-utilizer prediction model.
The social and clinical risk stratification model was broken up by social determinant components (for example, transportation) and then aggregated for a composite score. Each patient received a prediction score for each model, which can be used by the provider to proactively intervene where appropriate.
Real-world applicability
The factors that achieved high levels of prediction, 70 percent recall, in the pilot were food security, employment, financial security and access to utilities. The two with minimally acceptable levels of prediction were access to transportation and mental health. The one SDoH factor that was not statistically significant – access to housing – is expected to produce significant results with more data.
The pilot showed that providers can identify the specific SDoH risks their patients have, as well as stratify their patients by composite social and clinical risk scores. The high-utilizer model achieved 98 percent accuracy for predictability.
If Cheryl’s provider was employed by MetroHealth with access to this solution, prior to her appointment they would have seen that her overall SDoH risk score is trending upward and that she has indicated unmet needs in economic stability and transportation. They would also have seen that she is a predicted high utilizer.
This information, gathered without any input from the patient, would enable the provider to give better care, including recommendations such as financial counseling, rideshare options and preventative care programs.
For someone like Cheryl, this isn’t just a model — it’s a lifeline. Medical professionals could trace her rising SDoH risks, pinpoint obstacles in her financial and mobility spheres, and architect interventions well in advance.
Having access to this data and these insights ultimately improves outcomes and the value provided to patients while helping address health disparities.
Aloha McBride is the EY Global Health Leader and Nabil Chehade, MD, is executive vice president and chief clinical transformation officer at The MetroHealth System. The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.