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Artificial Intelligence and Healthcare – FAQ’s
Healthcare professionals envision that AI technology will streamline services and increase how quickly the healthcare system can react to ensure that the right people are seen at the right time in accordance with their medical needs, and that medical claims and other administrative and workflow tasks can be optimized.
Current examples of AI in action can be found in robotic-assisted surgery, medical claims analysis, virtual observations, chronic care management, and just about any area where an abundance of high-quality data can improve patient outcomes and industry efficiencies. For instance, rather than a pathologist viewing thousands of images to find the few that may be problematic, the system does the initial cut, freeing the pathologist to focus on the problematic slides. Exciting new AI-based applications have recently been introduced to screen for diabetic retinopathy as well.
Another example is chronic condition management program using Machine Learning: a recently implemented a system that identified diabetes patients who could benefit from additional monitoring, then analyzed the data collected from monitoring kits provided to those patients.
The conducted a study in Oxford providing patients with complex respiratory needs with a tablet and probe which measured heart rate, blood oxygen levels, and more daily and reported this back to the clinical team at the local hospital.
Over time, the AI system behind the app and system learned about the patient and their vital signs and learned to predict when certain drops in heart rate/blood oxygen levels meant that the patient required intervention from the medical team.
During the time the trial was running, hospital admissions dropped by 17% for the group of participants as the app allowed the patient and clinical team to schedule appointments when the health of the individual began to deteriorate, instead of emergency hospital visits.
Think of it this way: 2+2 will always equal 4, so the results of a device based on 2 plus 2 equaling 4 does not change, no matter how much data it looks at. But what if a device that adds 2 plus 2 on Day 1 “teaches” itself calculus by Day 5?
AI requires an enormous amount of data to “learn” and if that data is protected under HIPAA, either patients have to consent to its use as an input, or the protected health data will have to be de-identified before being fed into the system, or the regulations will have to be amended to permit its direct use.
The implementation of artificial intelligence in healthcare may entail transfers of data between the EU and U.S.: for example, if the hospital is in the UK but the technology being used is based in the U.S. This creates problems for UK hospitals and medical practitioners subject to GDPR and the U.S. companies processing the data of EU citizens.
- On Friday, May 29, 2020
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