Leveraging operational AI and ML has the potential to unite providers and optimize the consolidation of data sets.
During initial testing, the AI-driven algorithm demonstrated the ability to accurately forecast missed care opportunities, with success rates as high as 96%.
AI and machine learning insights strategically improve productivity and administrative efficiency at both departmental and enterprise levels.
In 2017, GE HealthCare and Mass General Brigham embarked on a ten-year partnership focused on AI innovation in diagnostics and treatments.
and Mass General Brigham have unveiled the joint development of an AI algorithm. This algorithm is designed to enhance operational efficiency and productivity in healthcare.
The maiden AI application stemming from this collaboration is the 'schedule predictions dashboard' integrated into the Radiology Operations Module (ROM), a digital imaging tool readily available for deployment by healthcare institutions.
Its primary objective encompasses the optimization of scheduling procedures, cost reduction, and alleviating administrative burdens placed on healthcare providers. By doing so, ROM liberates valuable time, permitting clinicians to invest more of their efforts into fostering and strengthening the clinician-patient relationship.
Amid a vast sea of data and the demanding responsibilities that often divert healthcare providers from patient care, Parminder Bhatia, Chief AI Officer of GE HealthCare
, described the collaboration with Mass General Brigham as groundbreaking. He added that they combine unique datasets and utilize cutting-edge machine learning techniques, harnessing the synergy of clinical and technical expertise to usher in unprecedented advancements in healthcare.
Keith Dreyer, DO, Ph.D., Chief Data Science Officer, Mass General Brigham, remarked,
This technology has the potential to reduce burnout and allow physicians to spend more time with patients, which may ultimately lead to better outcomes.
[Source: Business Wire]
Operational AI-enabled tools can tackle challenges that frequently jeopardize patient care, including the cost of healthcare and inefficiencies within hospitals. When a patient misses an appointment, neglects to schedule a follow-up, or arrives late, collectively called missed care opportunities (MCO), the repercussions can be substantial. The algorithm developed in collaboration is designed to forecast MCO and late arrivals. This initiative aims to enhance operational flexibility, streamline administrative processes, elevate patient satisfaction, and more effectively accommodate urgent, inpatient, or walk-in appointments.
GE HealthCare, a global leader in medical technology, pharmaceutical diagnostics, and digital solutions, focuses on delivering integrated solutions, services, and data analytics to enhance hospital efficiency, support clinicians, improve therapy precision, and promote patient well-being. With over a century of service to patients and healthcare providers, the company advances personalized, connected, and compassionate care through imaging, ultrasound, patient care solutions, and pharmaceutical diagnostics.