GE Healthcare has collaborated with Mass General Brigham to develop an AI algorithm aimed at predicting scheduling-related issues in healthcare. The algorithm can forecast patient appointment no-shows, missed follow-ups, and late arrivals, aiming to reduce administrative burdens and improve efficiency. The technology is initially implemented within the Radiology Operations Module (ROM), a digital imaging tool for enhancing scheduling predictions. Healthcare providers can benefit from streamlined data and actionable insights driven by AI and machine learning to optimize patient care.
GE HealthCare announced that it has codeveloped an AI algorithm with Mass General Brigham to help with scheduling predictions, including failure to show up to appointments, neglecting to schedule follow-up appointments and predicting late arrivals.
The first application of the algorithm, geared toward predicting missed care opportunities, is used within the schedule predictions dashboard of the Radiology Operations Module (ROM), a digital imaging tool that aims to reduce cost and ease administrative burden.
“Today, healthcare providers are faced with many administrative tasks that take them away from why they practice medicine in the first place – patient care and interaction,” Parminder Bhatia, chief AI officer of GE HealthCare, told MobiHealthNews via email.
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“Through our collaboration with Mass General Brigham, we’re providing streamlined data and actionable insights driven by AI and machine learning following the responsible AI tenants that can help to improve productivity and efficiency so they can focus on what matters most.”
THE LARGER TREND
Studies have shown that scheduling systems in healthcare by utilizing algorithms can provide significant results and improve the quality of care.
Last month, GE HealthCare announced the release of a smartphone-sized Portrait Mobile wireless monitoring solution, which received FDA 510(k) clearance.
Portrait Mobile is designed for in-hospital use and measures respiration rates, intending to shift the paradigm from periodic spot checks to continuous vital sign monitoring for indications of patient decline while freeing the patient from bed.
Source: MobihealthNews
