Creating Accessible And Quality Healthcare

Dr Philip Payne, Director of the Institute of Informatics and Robert J Terry Professor in the Division of General Medicine and Professor of Computer Science and Engineering at the School of Engineering and Applied Science,Washington University in St Louis, sheds light on how precision medicine can help provide best healthcare through AI, machine learning and data collection

Much has been written about the promise of precision or personalized medicine. This approach to healthcare utilizes all the data we can collect about individuals to measure their characteristics, including lifestyle, genes, the biological basis for their health and wellness, and how they present during an office visit.

The biggest challenge facing us in delivering precision medicine is turning data into action. We have massive advances underway in artificial intelligence, machine learning, and the use of mobile computing and sensors, as well as any number of other data sources to help providers better understand our patients and our communities. There is a lot of information coming at us at an astonishing cadence. Now is the time when we have to turn that data into actionable insights for as many patients as possible.

To turn data into action, we must understand all levels of data, from individual behaviors and lifestyle to environmental factors, and the clinical presentation of health as well as disease. As we use this data to make better decisions for individuals, we can often improve the quality, safety, and cost of the care they receive.

Ultimately, if we can process all of this information and translate it into action, we have an opportunity to treat people when they are sick, and also to take care of them and ensure that they don’t get sick in the first place. However, there is much work to be done to ensure this information is inclusive of all people.