Activating Social Determinants of Health Data to Address Obesity

Obesity, a condition associated with multiple comorbidities, lower life expectancy, increased costs, and negative stigma, poses a significant problem for millions of Americans in the coming decades. Carrying a considerable price tag in terms of personal and societal cost, obesity imposes additional financial burdens on patients, employers, and the healthcare system as a whole. Previously overlooked, obesity is now recognized as an urgent public health concern and a treatable condition.

THE PICTURE OF OBESITY

Obesity is defined as abnormal or excessive fat accumulation that presents a risk to health. Only classified as a disease in 1997 by the World Health Organization, obesity is expected to impact nearly half of all adults in the United States by 2030, and 25% of all adults are expected to have severe obesity. Obesity is typically diagnosed through BMI, which reflects only the ratio of height and weight. BMI is an imperfect metric that does not distinguish between weight from fat, bone, or muscle, and thus may not accurately indicate a patient’s health status. It does however, provide insight into the relative risks patients with obesity have in developing other comorbidities. An individual with obesity isn’t necessarily unhealthy or even sick, however data shows that the condition raises the likelihood of developing comorbidities such as hypertension or type 2 diabetes, which can affect the long-term health of an individual.

CHALLENGES TO ADDRESSING OBESITY

While new obesity treatments offer hope, they also run the risk of perpetuating problematic views and approaches. The lack of awareness about the holistic health of a person is driven by limited contextual data that focuses only on a handful of metrics, rather than on the whole person and the nuances of their lives. Social determinants of health (SDoH) data offers a critical lens into understanding key drivers of obesity – most notably that the disease is not driven by a patient’s individual diet and exercise choices, but by a combination of their lifestyle choices, environment, and genetics. Cultural and environmental data can provide health care providers with contextual data points about social factors impacting health (e.g., insurance, access to transportation), which can account for up to 80% of modifiable health outcomes. SDoH data provides insight into the ability of a patient to support a positive health status that isn’t contained in clinical data captured during a visit to their doctor’s office.

Low hanging opportunities to leverage SDoH data into actions include decision aids and flags in EHR systems prompting clinicians to provide advice on addressable obesity issues and log obesity data for more robust care planning. Further, SDoH data can mitigate biases against obese patients and the view that their weight is a result of “willpower” issues. To avoid stigmatization and over-prescribing, personalized care plans utilizing SDoH are one critical piece in effective management. As obesity-related factors become better studied, analyzed, and understood, data like SDoH will increase in importance due to the insight they provide into an individual’s capacity and ability to act on recommended treatments and the likelihood of long-term results through the design of personalized programs.

While SDoH data is crucial to understanding the holistic health of an individual, it’s not enough. Physicians and providers have indicated that simply giving insights doesn’t help address obesity.

THE COLLABORATIVE APPROACH TO OBESITY TREATMENTS

Increasing collaboration between different healthcare stakeholders can empower the actionability of providers to address obesity by creating unified clinical, commercial, and real-world data sets to support a more comprehensive assessment of factors contributing to obesity. Actioning on obesity requires an understanding of the disease holistically, from how it affects other clinical risk factors to what strategies fit a particular patient. This holistic knowledge can best be obtained through partnerships with a variety of different stakeholders: providers who understand the various clinical risks, data companies with SDoH data, and life science companies with insight into prescription interventions.

This collaboratively sourced data can be leveraged to: identify underserved obese populations and recommend programs to assist them in addressing their obesity, assist community stakeholders assisting obesity patients navigating the healthcare system, and encourage the development of physical infrastructure that supports healthy communities. This data is essential for accurately assessing the impact of obesity and gaining valuable insights into suitable approaches for addressing wide-spread obesity in a personalized manner.

Collaboration can also be utilized to establish a comprehensive, data-driven view of the financial implications of obesity at both an individual and a societal level. Data and tools that provide insights into the long-term impact of obesity will also reduce overall downstream costs in the healthcare system.

ACTIONING COLLABORATION FOR OBESITY

Collaboration with healthcare stakeholders is crucial in transforming data from merely interesting insights into actionable decision points. This collaborative approach towards driving action helps effectively communicate the value of data insights to stakeholders and highlights the potential consequences of inaction, emphasizing the importance of taking timely and appropriate measures.

11TEN brings forward deep experience in driving actionable insights from SDoH datasets and bringing together partners with the right expertise to develop solutions. Through our demand-driven innovation methodology, 11TEN helps companies understand how to drive better outcomes and novel uses with their SDoH data or learn more about areas where SDoH data can help solve critical business challenges.