Dec - Jan 20199To increase those numbers to something closer to 100 percent, we must be realistic about the pain points AI can solve. Budgets are tight at hospitals and health systems, and there are often more skeptics than there are believers. To prove the value of AI, focus on specific problems--whether it is workflow inefficiencies or patient experience in acute care.For example, on any given day, radiologists view thousands of medical images, many which turn out to be normal. For patients with a critical condition like collapsed lung, waiting for a doctor to sort through the normal scans can be a matter of life and death. That's why GE Healthcare is partnering with UC San Francisco to develop an algorithm based upon high quality data that aims to help detect Keith Bigelowimages with a collapsed lung and prioritize those scans both for the care team and the radiologist. Strategic deploymentFinally, as with other technologies, the key to taking advantage of AI is figuring out how it can seamlessly integrate into a provider's workflow. Would you use Google Maps if you had to open a different app to see traffic patterns versus directions? Would you like Netflix if you had to use your laptop and TV to see recommendations? By comparison, AI won't work in healthcare if it introduces yet another screen or yet another instrument. Rather, it will deliver upon the promise when it's made invisible, naturally embedded into the workflows, applications, and devices that healthcare providers already use today. For example, X-ray reject rates can be as high as 25 percent. The result is a high volume of repeated exams, which can contribute to unnecessary patient radiation dose and decreased throughput. The invisible solution is to embed an algorithm in the modality and thereby decrease the reject rates by automatically identifying and analyzing the root causes of rejected X-ray images. It's a targeted solution, seamlessly integrated into the existing workflow, that addresses multiple healthcare outcomes, including quality and costs. AI is not a doctor. AI is not a cure. AI is a tool--a means to an end--increasingly embedded in everything for the benefit of the patient. If deployed effectively, AI will change healthcare forever and improve lives around the world. And in the meantime, we have to be trusted stewards of the data and data science, we have to seek out those use cases where providers and patients welcome the efficiency, and deliver that efficiency effortlessly and invisibly. AI is not a doctor. AI is not a cure. AI is a tool--a means to an end--increasingly embedded in everything for the benefit of the patient
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