| | November 20179CIOReviewpatient in need without prompting and takes appropriate action. This type of system, because it can identify other triggers, can be applied in a variety of places around the hospital to solve an array of challenges, from ensuring that medication is stored at the proper temperature to predicting whether or not a patient will be readmitted, and for how long. Getting stakeholders within the health system to how else this technology can be applied and wherein both the short and long-term. In order to capitalize on machine learning, health systems must also analyze their organizational workflow and how human resources currently interact with technology. When machine learning technology is implemented, it will constantly gather and aggregate data, and make predictions and decisions based on that information. Some of that information will need to be transmitted to the people working in the hospital, but there will need to be ongoing discussions about how that notification happens. Is it through a vibrating bracelet? Does there need to be a wearable device mandated with a display to explicitly state what is occurring? These questions will need to be addressed head-on and collaboratively with a variety of stakeholders, from providers to technology companies. While traditionally, partnerships between technology innovators and health systems are still in their infancy, creating and deepening those relationships will be vital for the future of patient care.The healthcare field has always been a proving ground for new technologies­from FDA-cleared wearable trackers that monitor and assist in the treatment of Parkinson's disease, to therapies that use a person's living tissue to create a medicine individualized to them, technology and health care are inextricably linked. But, in order to truly realize the promise of machine learning, hospitals and health systems need to evolve to capitalize on this new technology. It starts by understanding the current technology systems in place within the hospital and continues by evaluating how the hospital's systems and workflow support the connection between human resources and technology. Machine learning will revolutionize the way we provide care for patients­we need to be ready for it. Machine learning's ability to continually absorb information and improve itself as it gains access to more data and experiences is being used across industries to tackle some of today's biggest challenges
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