Three years ago, Jeopardy fans got to see Watson, IBM’s supercomputer, beat two human Jeopardy champions to take a $1 million prize. Watson’s skill at the game derived not just from its computing power but from its ability to process huge amounts of data rapidly. The next year, IBM and the Cleveland Clinic announced that Watson was turning to more serious pursuits and had “enrolled” in medical school. It’s been a productive partnership: Last month, they launched a new Watson program using genomic data to find the best options for cancer patients.
Watson’s venture into healthcare is part of a new movement to data-driven medicine. The federal government has recently released large amounts of data from the Centers for Medicare and Medicaid Services and the Food and Drug Administration, among other agencies. At the same time, several other trends — the use of electronic medical records, an explosion of data about the human genome, and advances in data analysis — have given us the potential for a revolution in healthcare.
We can look forward to more data-driven diagnostics, treatment plans, and predictive analytics to determine the best treatments more scientifically. Many experts now think we’re on the verge of a new era of personalized medicine, where an individual’s data — ranging from genetic makeup to exercise habits — can be used with the right algorithms to help determine a strategy for care.
Vinod Khosla, a leading tech venture capitalist and the former CEO of Sun Microsystems, sees the change as inevitable. He described his vision in a keynote at this past June’s Health Datapalooza, an annual celebration of new developments in data-driven healthcare. Khosla predicted that “data science will do more for medicine than all the biological sciences combined” over the next two decades. One driver, he believes, will be the need to reduce medical errors by using computers for more accurate case monitoring than humans can accomplish.
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These new advances are made possible by two related categories of data: big data and open data. (I’ve written elsewhere about the differences and overlap between the two.) Big data, which has been defined in a number of ways, can generally be described as large, complex datasets that test the limits of our abilities to analyze them. They might contain either public information or private records, such as massive numbers of medical records in a large medical system. Open data, in contrast, is any kind of data that’s freely available for the public to use, analyze, and republish. Some open data, such as the data released by the Centers for Medicare and Medicaid Services, is also big data. Other open data, such as lists of healthcare providers, might be less complex but equally valuable.
As the data revolution and the healthcare revolution have come together, venture capitalists have begun investing billions of dollars in digital health startups. These companies are finding new ways to use data to apply scientific research, improve care, lower costs, and help people find the best personalized treatment.
In this slideshow, we highlight nine new companies that are exploring the intersection of data and health. Several are listed in the Open Data 500, a study I direct at The GovLab at NYU on companies that use government open data as a key business resource. Click through to see how these startups are using big, open data to power apps and other tools aimed at keeping people healthier.
Aidin
Aidin is dedicated to helping hospital patients find better post-hospitalization care. CEO and founder Russ Graney saw the need for Aidin when his uncle was discharged from the hospital with nothing but a typed list of healthcare providers for guidance. The family chose one that happened to be nearby, and the uncle did not get the quality of care he needed. Now Aidin provides in-depth information to help patients and their families choose their best options.
Biodigital
Biodigital runs what might be the most intriguing-looking health website and mobile apps. It offers a voluminous library of 3D anatomical models drawn from the National Institutes of Health Visible Human project, with National Library of Medicine text to explain them. It’s like the old Visible Man and Visible Woman anatomy kits made real, or the Bodies museum exhibit made less grisly.
Clear Health Costs
Clear Health Costs, founded by health activist Jeanne Pinder, bills itself as “your source for finding health care prices.” The company uses pricing surveys on a few dozen common procedures, Medicare data from the federal government, and crowdsourced data on healthcare prices gathered from volunteers. Its motto is “Free the knowledge. Everybody should know what stuff costs in health care.”
iTriage
iTriage, started by an emergency room doctor and recently acquired by Aetna, lets you use a website or your smartphone to enter your symptoms, get quick advice on the kind of care you need, and get a list of nearby emergency facilities that can help. iTriage uses open data from the US National Provider Identifier Registry to identify physicians, hospitals, and other healthcare providers able to help in a crisis.
Purple Binder
Purple Binder fills an important public need: It matches patients with community services that can help keep them healthy. The company uses federal, state, and local data to help people locate food pantries, homeless shelters, and other services. As founder Joseph Flesh said at last June’s Health Datapalooza: “We’re working toward putting community and health on the same page” by making connections between healthcare services and social services.
Flatiron Oncology Cloud
Flatiron Health, which uses data to accelerate cancer research, is a rising star: The startup recently raised $130 million in a round of funding led by Google Ventures. Flatiron uses real-time data from patient records to create “a data platform that provides the most comprehensive view of a patient’s experience in the oncology office in real-time.” The company plans to offer a wealth of data from millions of cases so that researchers, doctors, and patients can develop new treatments and make better decisions on cancer care.
Iodine
Iodine aims to improve healthcare by personalizing it for each individual. The company puts together data on drug treatments from government sources, research, and patient input to provide a complete guide to drug effectiveness, side effects, tradeoffs, and costs.
Predilytics
Predilytics applies predictive analytics to healthcare to help health plans and providers make better care decisions. By using data to improve patient care, the company “enables our customers to target their resources in ways that improve the health of their member population and improve their performance.”
Propeller Health
Propeller Health uses sensors in asthma inhalers, mobile apps, and data analytics to aid doctors in identifying asthma patients who need more help in controlling their illness. In addition to helping physicians monitor their patients remotely, Propeller Health helps public health experts visualize asthma rates in different communities and devise preventive strategies.
Date: November 18, 2014