GE HealthCare and Mass General Brigham have co-developed an artificial intelligence (AI) enabled algorithm to predict missed care opportunities (MCOs) such as failures to schedule follow-up visits and late arrivals.
The collaboration is part of the companies’ ten-year pledge made in 2017 to implement AI across various diagnostic and treatment standards.
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The initial application is for the schedule predictions dashboard of Radiology Operations Module, a digital imaging tool designed to optimise scheduling while reducing operating expenses.
Through MCO predictions, the algorithm seeks to simplify administrative operations and facilitate urgent, inpatient or walk-in appointments.
In preliminary assessments, the algorithm predicted MCOs precisely at rates of up to 96%, with minimal false positives.
Mass General Brigham chief data science officer Keith Dreyer said: “Utilising operational AI and machine learning can bring providers together and streamline data sets.
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By GlobalData“The strategic use of AI offers great potential for the future of healthcare and we’re proud to be at the forefront of the movement.
“This technology has the potential to reduce burnout and allow physicians to spend more time with patients, which may ultimately lead to better outcomes.”
GE Healthcare chief AI officer Parminder Bhatia said: “Amid the vast sea of data and the heavy tasks that divert healthcare providers from patient care, our collaboration with Mass General Brigham is groundbreaking.
“Through the fusion of distinctive datasets and cutting-edge machine learning methods, harnessing the synergy of clinical and technical proficiency, we are ushering in unprecedented healthcare advancements.”
The two companies cited a report by Mercer that projected a shortfall of more than 29,000 nurse practitioners, 95,000 nursing assistants, around 446,000 home health advisors and 98,700 medical and lab technologists and technicians in the US by 2025.
In these cases, health organisations will need to make use of technology to help address some of these issues.
