A UVA Health proposal to reduce hospital readmissions was among 25 submissions chosen - from more than 300 applications - for a national competition seeking ideas on how artificial intelligence can improve healthcare.
The UVA Health data science team will compete alongside proposals from organizations that include IBM and Mayo Clinic in the first Centers for Medicare & Medicaid Services Artificial Intelligence Health Outcomes Challenge. UVA's project seeks to not only predict which patients are at risk for being readmitted to the hospital multiple times, but suggesting a personalized plan to prevent those readmissions.
Artificial Intelligence is a vehicle that can help drive our system to value - proven to reduce out-of-pocket costs and improve quality. It holds the potential to revolutionize healthcare: imagine a doctor being able to predict health outcomes - such as a hospital admission - and to intervene before an illness strikes. The participants in our AI Challenge demonstrate that such possibilities will soon be within reach. We congratulate the 25 innovators who have been selected to continue, and we look forward to seeing what else they have in store." Seema Verma, CMS Administrator Predicting and preventing readmissions
An analysis by the UVA Health data science team developing the proposal found that 3% of patients at UVA account for 30% of readmissions within 30 days of being discharged from the hospital. Most of those return hospital visits occur within 12 months of the first admission, so being able to predict which patients are at risk for multiple readmissions is vital.
One challenge is that not all readmissions can be stopped; published research estimates that less than one-third of readmissions within 30 days of discharge from the hospital are actually preventable. For example, elderly patients are at higher risk for readmissions, but there's nothing that can be done about a patient getting older. Related Stories
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