Learn: Leadership, Culture, Governance, and Equity
September 16, 2021
September 15, 2021
September 14, 2021
August 25, 2021
August 18, 2021
July 29, 2021
Using Data Science for Effective COVID-19 Capacity Planning
COVID-19 is causing many hospitals and health systems to face resource and capacity restrictions, making the accurate estimation of COVID-19 requirements crucial. Carle Health needed the ability to anticipate the impact COVID-19 would have on its organization and community. After analyzing national COVID-19 capacity planning resources, Carle chose a model that was customized for its organization. Carle leveraged its analytics platform, using local data and infection rates to forecast the impact of COVID-19 locally. The organization now has critical insight into when surges will occur and can determine if it has enough available resources.
Understanding Population Health Management: A Diabetes Example
Managing individual cases of diabetes require actively involving patients in their care plan, enabling each patient to monitor and understand key data, such as A1c readings, and adjust lifestyle or other factors affecting overall health. Managing diabetes across larger populations, however, is best done through the use of a data and analytics platform that can aggregate data from multiple sources and provide actionable insights. Specifically, a data platform can identify patients who aren’t up to date on tests and those at high risk for other complications, uncover variations in diabetes care across an organization, and more.
AI Can Advance Health Equity
Health technology and augmented intelligence (AI) can significantly improve or worsen health equity. Recently, there has been a growing concern that AI is increasing disparity. ChristianaCare set a goal to reduce avoidable health disparities. The organization faced many challenges, including inconsistent collection, storage, and use of personal characteristics such as race, ethnicity, and language. Using its data platform and Healthcare.AI™, ChristianaCare now has a single “source of truth” for personal characteristics data. By treating health equity as a goal with the same commitment and focus as it would for other clinical, operational, or financial improvement efforts, the organization is purposefully using AI to achieve health equity.