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geneXwell: Multidimensional Omic Risk Models and Dynamic Visualizations to Drive Positive Change in Employee Behavioral Economics

geneXwell：多维组学风险模型和动态可视化推动员工行为经济学的积极变化

基本信息

批准号：
10325942
负责人：
AASHUTOSH MISRA
金额：
$ 1.67万
依托单位：
GENEXWELL INCORPORATED
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-21 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10325942
关键词：
Algorithms Apple Area Behavior Behavioral Behavioral Sciences Biometry Cardiology Cause of Death Chronic Clinical Collaborations Complex Coronary Arteriosclerosis Coupled Data Data Analyses Decision Making Diagnostic Disease Disease Outcome Early Intervention Economics Employee Employee Health Ensure Event Fast Healthcare Interoperability Resources Genetic Genetic Risk Genomics Goals Guidelines Health Health Benefit Health Care Costs Incidence Individual Institutes Intervention Intuition Life Style Lipids Measures Medial Modeling Modernization Modification Myocardial Infarction Nature Phase Policies Population Predictive Analytics Prevention Prevention strategy Privacy Privatization Procedures Process Productivity Relative Risks Reporting Research Research Support Risk Risk Assessment Risk Estimate Risk Factors Running Sampling Social Marketing Source Stents Structure Surveys System Testing Theory of Change Therapeutic Intervention Translational Research United States Ursidae Family Vision Visualization Visualization software base behavior change behavioral economics behavioral health care systems clinical risk cost cost effective cyber security digital disorder risk effective intervention empowered encryption experience financial incentive improved insight mobile computing personalized health care programs prototype response risk sharing risk stratification screening shared decision making software as a service symptom management symptom treatment targeted delivery usability user centered design verification and validation

项目摘要

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.

员工的生产力与员工的健康直接相关，这为雇主提供了强有力的经济激励