Geisinger Advances in CMS Artificial Intelligence Challenge
For its proposal to reduce adverse events, Geisinger will advance to Stage 1 of the CMS Artificial Intelligence Health Outcomes Challenge.
Source: Thinkstock
By Jessica Kent
- CMS has selected Geisinger and EarlySign, a machine learning company, for their joint proposal in the agency’s Artificial Intelligence Health Outcomes Challenge. The partnering organizations are among 25 others advancing to Stage 1 of the competition.
Launched in March 2019, the CMS AI Health Outcomes Challenge provides an opportunity for innovators to show how AI tools can predict unplanned hospital admissions and adverse events. This could lead to the use of more AI tools in CMS Innovation Center payment and service delivery models. More than 300 organizations submitted AI innovations to the challenge.
Geisinger and EarlySign’s proposal, Reducing Adverse Events and Avoidable Hospital Readmissions by Empowering Clinicians and Patients, seeks to apply AI and machine learning algorithms to Medicare administrative claims data.
Researchers expect that this could result in the development of models that predict unplanned hospital and skilled nursing facility admissions within 30 days of discharge, as well as adverse events like respiratory failure, postoperative pulmonary embolism, deep vein thrombosis, or sepsis.
"Approximately 4.3 million hospital readmissions occur each year in the U.S., costing more than $60 billion, with preventable adverse patient events creating additional clinical and financial burdens for both patients and healthcare systems," said David Vawdrey, PhD, Chief Data Informatics Officer at Geisinger.
"Together with our partner EarlySign, we have forged a dynamic team that is rapidly developing novel solutions to achieve the Quadruple Aim of improving the patient experience of care, improving the health of populations, reducing cost, and improving clinical care provider satisfaction."
CMS launched the AI Health Outcomes Challenge in partnership with the American Academy of Family Physicians and Arnold Ventures. The competition engages experts from all industries to leverage the power of AI to improve healthcare processes and patient outcomes.
“The Artificial Intelligence Health Outcomes Challenge is an opportunity for innovators to demonstrate how artificial intelligence tools – such as deep learning and neural networks – can be used to predict unplanned hospital and skilled nursing facility admissions and adverse events,” CMS Administrator Seema Verma said when announcing the challenge.
“For artificial intelligence to be successful in healthcare, it must not only enhance the predictive ability of illnesses and diseases, but also enable providers to focus more time with patients. The power of artificial intelligence will truly be unleashed when providers understand and trust the data and predictions.”
The challenge takes place in three stages. CMS will announce the Stage 2 finalists in April 2020, and final awardees and grand prize winner in September 2020. CMS and its partners will award the grand prize winner up to $1 million, and a runner-up will receive $230,000.
With their joint proposal, Geisinger and EarlySign expect to make strides in leveraging AI for healthcare.
"Geisinger's experience and substantial unified data architecture (UDA) is the perfect complement to EarlySign's proprietary data repository and suite of AI tools, enabling the rapid development and validation of effective machine learning models," said EarlySign CEO Dr. Jeremy Orr.
"These models are designed to integrate seamlessly with current clinical workflows as a decision support tool that can help improve patient outcomes and decrease healthcare costs."
