Right now there is still a fragmented ecosystem with thousands of medical and semi medical devices, wearables with sensors, apps, platforms. But the number of big and bigger databases collecting and platforms analysing and translating raw data into actionable is growing. Examples are the National Patient Powered Research Network (PPRN) in the US, but this is a worldwide trend.
Finding an overall trend in someones health is very different from a single data point collected at a visit to a doctor’s office, believes Mark Benden, PhD, CPE, associate professor in the Department of Environmental and Occupational Health and director of the Ergonomics Center at the Texas A&M School of Public Health. “Knowing the trends will greatly improve both care and prevention.” In fact, according to a 2013 report, 73 percent of physicians think that health information technology will—at least in the long term—improve health care quality.
Technology may aid in taking a simple patient history. A wearable device can already show things like how many steps a patient is taking each day and their average heart rate, and at some point, they may also be able to measure disease markers or indicators like blood pressure, cholesterol or blood sugar.
Benden states that having information from these devices allows providers and patients to have a data-driven conversation, not one based on a one-time sample. “Having objective data can also help with the natural tendency of patients telling their provider what they think they want to hear.”
For example, if a wearable device could accurately measure heart rate and blood pressure at every moment of the day, providers could keep this data as part of the person’s electronic health record. If someone’s blood pressure started to rise over time, the provider could consider prescribing a medication to bring it down to the healthy range and be confident that the rise was an actual trend, not a one-time high outlier.
Make better decisions
Technology can help physicians make better decisions in other ways as well. Hongbin Wang, PhD, professor at the Texas A&M College of Medicine and co-director of the Texas A&M Biomedical Informatics Center, is working on a computer model of neurons to predict a decision—a medical diagnosis, for example—and illuminate any biases that might be present.
Wang’s work, and other applications of big data, may help with diagnosis by drawing together not only one person’s test results over time but also results from thousands or millions of other people. Data from many patients’ treatment outcomes may also help clinicians recommend the best treatment for each individual: the ultimate goal of precision medicine.
Prevention more potential
More than helping with better diagnozing and more personalised treatment, technology can help preventing people from becoming sick. Here lies the most exciting potential. If exercise is one of the most effective methods of staving off diseases from cancer to heart disease to Alzheimer’s, the main challenge is motivating people to become active.
Although the popular fitness trackers were supposed to help, there’s as of yet little evidence that they make people more active over time. “We’re struggling to show that wearables are changing behaviors…what’s missing?” Benden asked. “I think we’re missing human connection.”
That human connection could be as simple as the healthcare provider receiving a notification about a shift in their patient’s trends, allowing the physician or nurse to follow up with a phone call to check in. Of course, as technology itself becomes more human-like, it may be able to motivate people on its own – for example with a virtual coach that learns about its user through machine learning.
“When we learn to use these devices in a way that responds to someone as a person and caters to their individual needs, it will be very powerful,” Benden said. “The technology will know you and be able to help you make healthy choices in whatever way works best for you personally.”
Someday technology may even allow patients to deal with less-complicated issues on their own—or possibly respond by itself, limiting the need for professional intervention. This is already the case e.g. with connected medicine dispensers that improve adherence to medicine.
“Someday, the devices will be smart enough to know what’s happening to you and intervene when necessary,” Benden said, like a pacemaker that can help a heartbeat regularly while monitoring rhythms, and then if needed defibrillate automatically. “A lot of those corrections will be automatic, and people can continue about their days without ever knowing that a device just saved their lives.”