Stanford’s mHealth App Gets a Precision Medicine UpgradeJan 8, 2017
One of the first apps to be introduced on Apple’s ResearchKit platform two years ago, the Stanford University School of Medicine’s MyHeart Counts app has logged more than 54,000 participants in a research project that focuses on heart health. Now comes MyHeart Counts 2.0, which combines mHealth with precision medicine to give the user a personalized care management plan.
mHealth advocates see this as the next phase in app development, which moves to combine biometric monitoring with analytics tools and artificial intelligence to move from collecting to coaching. This, in turn, could spur more interest from healthcare providers who want to use wearables to drive care coordination and behavior change.
“We know when it comes to changing key health habits, such as physical activity and daily sitting time, one size definitely does not fit all,” Abby King, PhD, a professor of medicine and health research and policy at Stanford, said in a news release prepared by the university. “Yet until the advent of mobile apps and other e-health programs, we’ve had few options for customizing messages and feedback to individuals in real time.”
Apple’s ResearchKit platform, unveiled in 2015, was seen as a means of pushing mHealth beyond passive data collection. Targeted at the healthcare industry, rather than consumers, the framework enables clinical researchers to gather data through Apple devices from users around the world, then apply that data to population health programs.
Aside from MyHeart Counts, other research projects unveiled alongside ResearchKit targeted asthma, breast cancer, diabetes and Parkinson’s disease. Dozens more have been introduced since then, focusing on subjects like concussions, post-partum depression, sleep issues, peripheral artery disease, hepatitis c, health concerns among the LGBT population, moods, even lifestyle and health conditions that might affect a child’s temperature.
Through MyHeart Counts 2.0, users share their data on day-to-day activity levels, cardiovascular health, blood pressure and cholesterol levels. Stanford – working with app development company LifeMap Solutions and Oxford University – takes that data and pushes it back to the user in the form of a personal health plan called the Stanford Coaching Module. The plan includes a week of baseline measurements, then four one-week-long behavior change interventions that are based on comparing the user’s health data to population health metrics.
“[This] lets us begin to customize feedback to users, and also discover which types of information might be most useful or motivating for different groups,” King said, who designed the coaching module.
“The most unique thing about the new version is its ability to randomize patients and intervene,” added Euan Ashley, DPhil, MRCP, an associate professor of cardiovascular medicine and of genetics at Stanford and the principal investigator for the MyHeart Counts study. Those interventions, he added, “will give researchers a handle on whether a particular intervention for an individual is prompting a change in behavior for the better.”
Though still in the data-gathering stage, researchers at Boston Children’s Hospital are hoping for the same results from their ResearchKit study.
Through the Feverprints app, researchers from BGH’s Innovation & Digital Health Accelerator and Autoinflammatory Diseases Clinic are gathering data from iPhone users on body temperature, lifestyle and health. Their goal is to create a definition of a normal or febrile temperature and a framework of unique temperature patterns – or feverprints – that would help in diagnosing infections and other health issues.
“Many factors come together to set an individual’s ‘normal’ temperature, such as age, size, time of day and maybe even ancestry,” Jared Hawkins, MMSc, PhD, the IDHA’s director of informatics and a member of the hospital’s Computational Health Informatics Program, said in a press release issued last April. “We want to help create a better understanding of the normal temperature variations throughout the day, to learn to use fever as a tool to improve medical diagnosis and to evaluate the effect of fever medications on symptoms and disease course. By using ResearchKit to bring this study to iPhone, we’re able to gather more data about body temperature patterns than ever before possible.”