Machine training future of health IT

Image removed.In the next three years, the healthcare industry will have to focus as much on training machines as on training people, according to a new report from Accenture.

document.addEventListener("googletagEvent", function() { googletag.cmd.push(function() { googletag.display('ad-slot_1__mobile'); }); });

Eighty-four percent of healthcare executives agree or strongly agree that their industry will need to focus on using algorithms, intelligent software and machine learning as well as human workforce training. Eighty-three percent foresee provider organizations needing to manage intelligent machines to keep up with the surge in clinical data, according to an announcement.

Intelligent machines will also manage data from various disparate sources, such as diagnostic tests, Internet-connected devices, genomics and medical records. Forty-one percent of those polled said their data volume has grown more than 50 percent in the past year.

The survey included 601 doctors, 1,000 consumers and 101 healthcare executives.

The report highlights emerging technology trends, including:

  • The Internet of me: An era of personalized healthcare defined by meaningful and convenient individual healthcare experiences
  • Outcome economy: Where hardware will be relied on to help produce results
  • The platform (r)evolution: Health IT platforms will aggregate data from various sources to provide a holistic, real-time view of an individual's health
document.addEventListener("googletagEvent", function() { googletag.cmd.push(function() { googletag.display('ad-slot_2__mobile'); }); });

Currently, scientists at Carnegie Mellon University and the University of Pittsburgh use artificial intelligence in their quest to provide individualized treatments. Their project takes data from electronic health records, diagnostic imaging, prescriptions, genomic profiles, insurance records and even wearable devices to create healthcare plans not only by disease, but also for specific types of people.

Separately, researchers are using machine learning and natural language processing in a project at Cincinnati Children's Hospital Medical Center. The project uses a computerized algorithm to combine structured and unstructured data to improve medication reconciliation and detect discrepancies between medication orders and patient adherence.

To learn more:
- here's the report overview
- read the announcement