As part of a 10-year research collaboration, GE HealthCare and Mass General Brigham are introducing the first of their joint AI innovations for more efficient patient scheduling.

The Radiology Operations Module (ROM) is a digital scheduling dashboard that predicts changes in appointments and scheduling tasks. The first application of this solution detects so-called missed care opportunities, where patients are late, fail to schedule a follow-up, or miss an appointment.

In preliminary testing, the technology’s predictions were correct up to 96% of the time and had limited false positives, allowing physicians to eliminate administrative burdens and allocate more time to their patients.

The algorithm may potentially reduce costs and offset the effects of increasing labor shortages among medical professionals, which has put pressure on current workers to keep up with higher workloads in a timely manner. This includes doctors, nurse practitioners, nursing assistants, medical and lab technologists and technicians, and home health aides among others.

The companies pledged in 2017 to develop a range of AI solutions for diagnostic and treatment paradigms that support the entire patient care process.

Numerous studies support the use of AI in scheduling and its ability to reduce costs and improve quality of care. In a recent one at Duke Health, surgeons were able to save $79,000 in overtime costs over four months by utilizing three algorithm models that allowed them to predict the length of time required for procedures in outpatient and inpatient care settings 13% more accurately. It also facilitated a decrease in medical errors.

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