Healthcare’s Data Imperative: Social Determinants of Health

The coronavirus has touched every part of the country with a staggering American death toll approaching 100,000, but the virus invaded the country unequally. Why? A recent New York Times article explored the answer: population density

“Nearly a third of Americans live in one of the 100 most densely populated counties in the United States — urban communities and adjacent suburbs — and it is there the virus has taken its greatest toll, with an infection rate three times as high as the rest of the nation and a death rate four times as high.”

Just like how where you live can increase or decrease your chance of exposure to the virus it can also have a larger impact on your overall health and wellbeing. Neighborhood walkability and poverty level are strongly linked to where you live. Factors like these shape our lives daily, affecting how we experience the world, the choices we make and, ultimately, how healthy we are.

These factors contributing to our health and wellbeing are referred to as Social Determinants of Health. They can overwhelm and counteract even the best medical care, with 68% of Americans facing challenges in at least one social determinant risk category. 

However, insight into these outside conditions would allow the healthcare system to begin delivering care based on the analysis of past and present data. The ability to identify a pattern of change that happened with one population and apply that to a larger population. Ultimately we could not only improve individual and population health but also advance health equity.

Medical care, while vital, only influences 20% of a person’s health. The other 80% of health is related to over 400 social and economic attributes that populate six broad determinant categories: economic stability, education, social and community context, healthcare system and neighborhood. Many healthcare providers are blind when treating patients because they don’t know which of these forces are impacting patients’ health and wellbeing beyond what an MRI scan or blood test might tell them. This makes it difficult for providers to holistically treat patients and for health plans to accurately cover their beneficiaries’ healthcare costs. 

Wealthier but not Healthier

The world is growing wealthier, but not necessarily healthier. Despite rising life expectancy and improvements in medicine, a modern health crisis is simultaneously occurring due to rising rates of obesity and chronic diseases. In 2018, the US spent $3.6 trillion –  18% of our GDP on healthcare. By 2028, national health spending is projected to reach $6.2 trillion, growing the health share of the economy to 20%. All the investments made in healthcare haven’t brought the necessary societal shifts to encourage habits that could prevent chronic conditions from developing. 

How healthy is the U.S. population? And how can we become healthier? The answers lie in the Social Determinants of Health. Social determinants can provide insight to health-related needs of patients beyond medical care and, if effectively utilized, avoid adverse effects. And while the success of any care strategy depends largely on the targeted response, the opportunity to help people improve their overall quality of life can provide positive health outcomes – and payments.

Digitally Transforming an Old Concept

The notion of improving health by addressing social determinants is not new, yet efforts to leverage them are. With 68% of patients facing a social determinant challenge in at least one category and only 22% discussing these issues with their physician, this disparity highlights an opportunity to insert technology into the conversation about how to improve patients’ health. 

Turning Unstructured into Structure

How do you incorporate Social Determinants of Health into standard operating practices? In the “gazigabits” of data that exist, studies indicate as much as 80% to 90% of data is unstructured. Social Determinants of Health commonly appear as unstructured data, with the lack of consistency making it difficult to convert into a structured data format easily searchable by programming languages. 

Z-codes are a relatively new occurrence in healthcare, bringing a structured approach to data. Added to the ICD-10 code structure that classifies patient records, Z-codes were designed to provide a means to capture and record factors that influence health. As Z-codes gain convention in the healthcare system, social determinants will easily be identifiable. Still, most data regarding social determinants remains unstructured. Data must be analyzed and translated into a computable format used in medical assessments to assist providers in identifying all treatment options, including care strategy that addresses issues related to social determinants.  If no process is present to bring these data into mainstream practice, it is left solely to the healthcare professional to manually scan free form text, open and review PDF files, or visibly access x-rays to deliver a diagnosis. 

Platform integrations or analytic technologies such as machine learning can help organizations collect and interpret data to drive powerful insights. Thanks to the advancement of Artificial Intelligence (AI), organizations can transform available data into a form that is readily accessible by healthcare professionals. AI uses advanced algorithms to identify patterns in unstructured data and translate it into a structured format of diagnoses, treatment directives, ICD codes, and social determinant information. As the algorithm is “taught,” it becomes better and better at correctly classifying and organizing records. Data that was once unstructured can now be displayed in the primary section of the patient record, rather than relegated to the endnotes. This prominent positioning makes it easier to make decisions and initiate preventive action against unnecessary complications.

Social Determinants of Health in Action 

Today, health plans and providers are partnering with organizations to address social determinant barriers and improve outcomes for the 44 million beneficiaries of the U.S. Medicare program. Made possible by the CHRONIC Care Act, health plans and providers are allowed to offer chronically ill enrollees non-medical services for social needs that affect health. Considering 80% of older adults have at least one chronic disease, and 77% have at least two, this is an important step for Medicare. Medicare innovations to address social determinants include:

  • Exercise:  SilverSneakers, an innovative community-based fitness program designed for older adults, under contract with Medicare Advantage plans works with older adults at risk to improve balance and mobility. 
  • Food Security: The Commonwealth Care Alliance’s Medicare Advantage Special Needs Plan developed the “Senior Care Options” program to provide beneficiaries access to weekly meal deliveries. 
  • Transportation: ChenMed, a physician-led Medicare Advantage plan, helps patients keep their appointments by providing patients with courtesy “door-to-doctor” transportation services.
  • Social Isolation: Tech startup Papa provides  “grandchildren on-demand” to seniors. College students who work with Papa visit with seniors and assist with chores and errands. 

Action Not Reaction

Our work and conversations with forward-thinking leaders in the industry reveal that data and technology are available to build a case for action, to illuminate target populations and leverage emerging technologies that amplify efforts of improving health through social determinant strategies. What’s needed? A careful decision-making process that uses predictive data analytics and allows decision makers to better navigate current and pending health challenges for patients. By making decisions based on data, systems can decrease money and time spent on ineffective interventions. 

The ultimate objective of healthcare is to keep patients healthy. Understanding and incorporating comprehensive social determinants into treatment will enable providers to more holistically treat patients, decrease costs, increase profitability, and improve outcomes.

The truth is that providers alone can’t improve patient health, but our systems and processes can. Action from healthcare stakeholders, not reaction, is required to rethink the future of what it takes to keep us healthy.

Nilesh Patil, chief data strategy officer, oversees Data Management and BI practice at emids. He is a focused business and technology expert with extensive experience developing enterprise information technology strategies and road maps, information architecture, standardized business metrics and analytical infrastructure. This comprehensive technology is designed to deliver vital information to industry organizations in innovative and insightful ways. Nilesh also serves as a valued advisor to multiple healthcare CIOs, CTOs and CAOs on their organizational initiatives, and plays a crucial role in assisting with developing actual blueprints and executing implementation. His skillset as a respected innovator and technology guru lends itself well in leading emids’ platform to help healthcare organizations realize their diverse analytics visions. Be sure to connect with Nilesh on LinkedIn.

Dean Thompson, consulting director, is a recognized critical thinker and big picture visionary. His innate ability to understand complexity within any business unit and utilize evolving technologies allows him to create efficiencies imperative to the creation of competitive advantages for customers. He is emids’ lead data scientist and oversees data analytics for emids Health Technology Solutions (HTS) business unit. Dean has maintained a successful career in C-level sales, marketing and business management. He maximizes results and brings his business experience and technical data analytics knowledge to the team. His passion for economics and statistics coupled with his technical skillset and data science experience allows him to bring revenue-generating and valuable high-level solutions. Be sure to connect with Dean on LinkedIn.

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