Personalized health care and artificial intelligence could improve your life—at the cost of your privacy

.videocontent{position:relative;padding-bottom:56.25%}.tvplayer > div {position:absolute;top:0;left:0;width:100%;height:100%} Health Andres Rubiano first got the news that his blood pressure was too high in the 1990s, when he was in his late 30s. It didn’t come as a complete surprise—his father had had chronic hypertension at an early age too. His doctor prescribed medication and encouraged him to get more exercise and cut down on the amount of salt in his diet.

There are, however, clear risks. The key to digital medicine is, after all, the gathering and sharing of copious data about nearly every aspect of a patient’s life. Are hospitals, researchers, Big Pharma, insurers and tech companies worthy stewards of such sensitive data? “If a system can detect signs of cognitive decline in patients’ voices, they don’t want it being used against them in job situations or health insurance,” says Christine Lemke, co-founder of Evidation, a health data company.

A digital health industry has spent billions on developing new tools and projects in recent years. To improve patient care, they are trying to create an ecosystem of apps and devices that link hospitals and doctors offices to data from portable devices like the Fitbit and an insulin injector for diabetics. FS Productions/Getty

A man checks his heart rate on a Fitbit Charge HR wearable activity tracker and monitor. Data from Fitbit trackers alone has inspired 675 studies in health-related journals. Lisa Werner/Getty De Brouwer channeled his data obsession into a startup called Doc.ai, which makes a medical app that automates the process of assembling its users’ exposome and behaviorome. You start by taking a selfie, which the app’s AI uses to estimate your age, height, weight and gender . Next, you enter your current and previous ZIP codes, which the software uses to query databases of air pollution.

To head off these crises, doctors at Ochsner wired their patients’ inhalers to alert them to patterns of usage that signal growing respiratory distress. Those patients get a text or call at home suggesting a change in medication or prompt a checkup. Patients also get text alerts when air particle readings are dangerously high in their communities, urging them to ease up on outdoor activity. “We can wirelessly manage the symptoms of thousands of patients closely,” says Milani.

Mordecai took data from 14 million patient visits to clinics run by Kaiser Permanente and two other health care systems that collaborated on the project. The data included whether or not each patient ultimately attempted suicide. Then he fed the data into “machine-learning” software, a form of AI that can identify complex patterns in reams of data that humans cannot see. The AI found 150 factors that, in various combinations, tend to signal that a patient is at an elevated risk.

Source: Healthcare Press (healthcarepress.net)

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