LifeGrid: Understanding and Quantifying the Impact of Social Determinants on Chronic Disease for Predictive Health

2018 IEEE International Conference on Healthcare Informatics (ICHI)(2018)

引用 0|浏览3
暂无评分
摘要
As the US healthcare system undergoes a paradigm shift from a fee-for-service model to a more quality driven fee-for-service model, the need for customizable solutions and effective ways to predict health outcomes has become more critical. Research has continued to point to social determinants of health (SDOH) as the critical factors contributing to health problems seen among Americans. Addressing social determinants of health will help to improve health outcomes; however, understanding the disparate implications of these factors on different socioeconomic groups could also provide insight into health inequities among populations. The "LifeGrid" theory being developed at Howard University Medical School proposes that 'place' is a strong indicator of chronic disease expression and health outcomes. Expanding on this theory, a quantitative statistical approach will be used to assess the relationship between community, economic stability, and 'LifeGrid' indicators and their impact on an individual. This LifeGrid score can be effectively used to define susceptibility of chronic disease and may be used as a predictive metric in personalized health tools for identifying the relative risk of chronic disease expression.
更多
查看译文
关键词
'LifeGrid', social determinants, predictive, chronic disease, health
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要