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Information transformation: The next great innovation in health care
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AUSTIN, Texas — The next great innovation in medicine will be the optimized transformation of information, giving clinicians an active “learning health system” that continuously transmits and stores data to better care for their patients, Robert Califf, MD, said during a plenary discussion here.
“The next revolution is going to be a transformation of information,” Califf, former commissioner of the FDA under President Barack Obama, said while speaking at the American Association of Clinical Endocrinologists Scientific and Clinical Sessions. “We’re in the early phase of it right now.”
A rapid growth in new technology and innovation is coupled with an alarming trend: All-cause mortality for white adults in the United States has begun to rise for the first time in decades, Calif said, in part due to what he termed “diseases of despair,” such as alcoholism, opioid abuse and suicide.
“If you look at the [United States] relative to other countries, we don’t look so good,” Califf said. “We’re in the 30s in terms of ranking of countries for life expectances, and we pay a lot more for that mediocre result. It’s raising the question, what can we do to improve this situation in a country with so much talent and capability?”
The solution will lie in technology and information, Califf said. In the next few years, clinicians can expect whole-genome sequencing, complex, regenerative medicine, gene editing and the measurement of “metagenome” bacteria inside the human body to be accessible in practice.
“We’ve got an exciting set of opportunities, but also probably a set of problems we’re not totally prepared for,” Califf said. “We’re in an era now where we have a surplus of abundant and overwhelming data ... but we have very little information. A lot is going into the computer, but not a whole lot is going out.”
Big information companies are investing heavily to solve this problem, Califf said. Verily, a product of Google’s parent company, Alphabet, has just launched Baseline, a 4-year, community-engaged study with 10,000 participants, that aims to better predict what makes people sick, Califf said. Volunteers will be given an Android-equipped watch and sleep sensor that measure physiologic and environmental data continuously, streaming the information into the cloud.
“For an average visit, 6 terabytes of data will be generated for each person,” said Califf, who helped to develop the Baseline study. “This is something that just was not even fathomable before.”
Most importantly, Califf said, a new data system will comprehensively integrate all the information.
“What’s really the hardest about this is not just storing the information, it’s that it comes in in different forms, and it’s almost impossible to aggregate this information in a way that would allow a comprehensive analysis for the whole human being,” Califf said. “The idea behind all of this is to make research more fun, but also to eventually make clinical practice more fun, where you’re really interacting with people and the machines are doing all the work in the background.”
“The computers are here to do it,” Califf said. “It’s the culture and the concerns related to privacy of health care that are keeping us from helping people the way we should.”
The FDA has also begun to aggregate large amounts of data to learn more about patient health. The FDA Sentinel Initiative, which complements the agency’s Adverse Event Reporting System, can rapidly access large amounts of electronic health care data, including electronic health records, insurance claims data and registries from a diverse group of data partners. In 2014, the Patient Centered Outcomes Research Institute (PCORI) launched PCORnet: the National Patient-Centered Clinical Research Network. The nationwide “network of networks” collects data from a variety of health care settings and engages patients, families, providers and researchers in making more informed health care decisions, Califf said.
These programs, Calif said, take a page from big information companies.
“Did you ever wonder why when you type something into Google it finishes your sentence?” Califf said. “Because it studied other people around the world asking that same question ... I think our patients deserve the same thing. Right now, we’re guessing as practitioners what would be best, not knowing all the things about them that could be known.”
Today, many clinicians are struggling with the “2010 version of computing,” which was focused on optimizing the function of the individual, Califf said. Today, he said, computing is oriented in optimizing group activity, which will ultimately benefit the practice of medicine.
“Think about this in the simplest form — as a doctor and patient as a pair,” Califf said. “How do you optimize the intersection of the doctor and patient pair, and the family of that patient, so that everybody learns and has the information they need to make the best choices they could possibly make? This is where I hope we’re headed.” – by Regina Schaffer
Reference:
Califf R. Evidence Generation to Inform Medical Decisions. AACE Annual Scientific and Clinical Congress; May 3-7, 2017; Austin, Texas.
Disclosures: Califf is former commissioner of the FDA.