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GE HealthCare and Mass General Brigham Collaborate on an AI Algorithm to Predict Missed Care Opportunities
In preliminary tests, the AI-enabled algorithm was able to correctly predict the missed care opportunity (MCO) at rates of up to 96%1. CHICAGO--(BUSINESS
About this update from Ge Healthcare Technologies Inc.
[{"type":"text","content":"\n\nIn preliminary tests, the AI-enabled algorithm was able to correctly predict the missed care opportunity (MCO) at rates of up to 96%1.\n\n\n\n CHICAGO--(BUSINESS WIRE)--\nGE HealthCare and Mass General Brigham announced, as part of its initial collaboration, the co-development of an artificial intelligence (AI) algorithm that will help increase operations effectiveness and productivity. The first innovative AI application from the collaboration is the schedule predictions dashboard of Radiology Operations Module (ROM), a digital imaging tool that helps optimize scheduling, reduce cost, and free providers from administrative burden, allowing more time for the clinician-patient relationship. ROM is commercially available to healthcare institutions.\n\n\nThe actionable insights driven by AI and machine learning are designed to help improve both departmental and enterprise-wide productivity and administrative efficiency. By 2025, the U.S. is estimated to have a shortage of approximately 446,000 home health aides, 95,000 nursing assistants, 98,700 medical, and lab technologists and technicians, and more than 29,000 nurse practitioners, according to a report conducted by industry market analytic firm Mercer. Health systems will need to rely on technology to help solve some of these challenges.\n\n\n\"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,” said Parminder Bhatia, Chief AI Officer of GE HealthCare.\n\n\nOperational AI-enabled tools can address challenges that often pose a threat to patient care such as cost of care, and hospital inefficiencies. When a patient misses an appointment, fails to schedule a follow up or is late, also known as missed care opportunities (MCO), the impact can be significant. The co-developed algorithm is intended to predict MCO and late arrivals, which could help increase flexibility and streamline administrative operations, improve patient satisfaction, and better accommodate urgent, inpatients, or walk in appointments. In preliminary tests, the algorithm was able to predict the missed...