Employee productivity is directly related to employee health, providing employers strong financial incentives
to deploy preventative health programs. One of the most challenging & costly chronic conditions is coronary
artery disease (CAD). Most employers spend a significant portion of overall benefits (40-45%) managing &
treating symptoms and risk factors associated with CAD. Each CAD event (heart attack, angina) and related
procedures (stents, CABG) costs the employer $125k in direct medial and productivity costs. These CAD events
are also the number 1 cause of death in the United States. Self-insured employers, which provide health
coverage to 100M individuals in the US, bear the costs of CAD directly. Therefore, any cost-effective approach
able to reduce CAD incidence in employee populations, particularly through early interventions would have
significant societal and economic benefits.
geneXwell provides this opportunity by targeting the delivery of our world-class digital preventative cardiology
program to those employees most at risk for CAD and most likely to benefit from lipid lowering therapy. As part
of ordinary employee health risk assessment, employees provide screening samples for clinical and genomic
analysis. Standard demographic and biometric risk factors are combined with a genetic risk estimate, resulting
in a personalized CAD risk score per employee. The addition of genetic risk both improves risk stratification as
compared to standard clinical guidelines and, more importantly, identifies the nature of risk and the most effective
interventions. This strategy is validated and supported by the research of our co-founders at The Scripps
Research Translational Institute. In the employee setting, this comprehensive risk modeling is used to stratify
the employee pool into risk tiers, and analytics run to determine the cost vs benefit of lifestyle vs therapeutic
intervention strategies for each risk tier. This information is then summarized and displayed via intuitive
visualization tools that allow employees to evaluate the benefits of prevention behaviors and health interventions.
Dynamic visualizations tools will allow collaboration, shared decision making and visibility across all
stakeholders. Revenue will be generated through Software as a Service and risk share models to employers.
Phase I will target the extension of our established baseline risk model to the data available in an employer
health setting, we will develop a prototype employee visualization interface, and conduct a usability study. First,
we will build on our existing, validated polygenic CAD scoring model. We will develop and deploy a CAD risk
score personalized with genetic, demographic, and clinical factors to produce individualized CAD risk scores for
employees. A risk reducer interface will be developed to integrate prevention strategies and anticipated health
benefits to drive employee behavioral change. Next, a prototype employee mobile platform will be developed
with focus on data synchronization across multiple domains and sources, as well as dynamic, intuitive
visualization tools, developed and informed by behavioral science expertise, to guide complex behavioral health
decision making by employees. Once the prototype platform has been integrated at the system level and passes
verification and validation testing, it will be deployed in a usability study with employees to validate interpretability.