Learn: AI and Data Science

Success Story
AI-Enabled Care Management Reduces Healthcare Spending by $32.2M

Almost four trillion dollars is spent on healthcare each year in the U.S., with most expenditures going to patients with chronic health conditions due to unnecessary visits to the emergency department (ED) and unplanned hospital admissions. UnityPoint Health sought to reduce costs by identifying patients with chronic health conditions at a higher risk for overutilizing healthcare services. By leveraging its analytics platform and augmented intelligence (AI), UnityPoint Health has been able to efficiently identify patients that could benefit from enrollment in its care management program.

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Five Ways Healthcare AI Gives You Superpowers

As healthcare decisions, data points, and options increase, time, resources, and margin of error decrease. To succeed in this environment, leaders and analysts must know where to focus and how to allocate resources and set accountability targets. With Healthcare.AI™, five super-powered assistive augmented intelligence capabilities help healthcare leaders and analysts determine values, understand context, and provide data-driven motivation to transform healthcare:

Insights
Your AI Journey Starts Here: A Four-Step Framework for Predictive Analytic Success

COVID-19疫情突出表明，卫生系统必须主动为未来的情况做好准备。组织做好准备的一种方法是使用人工智能(AI)，例如预测分析，来预测临床、运营和财务需求。虽然许多卫生系统拥有预测建模所需的历史和当前数据，但它们往往缺乏启动任何AI项目所需的分析基础和知识，更不用说预测分析之旅了。数据和分析技术为支持医疗系统成功实现人工智能奠定了基础，包括预测分析。有了适当的工具，卫生系统就可以遵循这一四步框架。

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Predicting Denials to Improve the Healthcare Revenue Cycle and Maximize Operating Margins

医疗保健财务主管们不断地在头脑风暴，通过更好的收入周期表现来增加营业利润率。这些努力往往导致收入循环负责人拒绝索赔——当支付人不为提供的服务偿还医疗系统的费用时。尽管否认是造成收入损失的常见原因，但专家认为近90%是可以避免的。有效的拒绝管理始于预防。组织可以使用收入周期表现数据，结合人工智能，来预测每个索赔生命周期中可能导致拒绝的领域。有了否认洞察力，卫生系统可以优化收入周期过程，以防止否认和增加营业利润率。

Success Story
AI-Powered Benchmarking Transforms Data into Insight, Improving Organizational Effectiveness

Healthcare organizations have a vast amount of data available. Data need to be converted into better decisions regarding organizational focus, resource allocation, and setting and driving toward appropriate targets to optimize performance. Beyond significant data integration and transformation, optimal leadership decisions require a broad perspective and cutting-edge analytics. Previously, INTEGRIS Health had high volumes of data but lacked the insight it wanted to drive performance. By leveraging a robust analytics platform, INTEGRIS Health now has more comprehensive and better-integrated data coupled with the cutting-edge analytics it needs to make critical leadership decisions and drive daily performance.