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Big health data made headlines recently with the news that vaccines have prevented 100 million cases of contagious disease since their introduction. The supporting data came from Project Tycho at the University of Pittsburgh, which digitized and standardized more than a century of weekly local health reports from cities across the U.S. The new project, named for 16th-century Danish astronomer Tycho Brahe, gives the public and researchers access to historical records on more than 56 diseases, including the eight featured in the disease prevention report.
Health officials welcomed the news as a reminder that vaccines are crucial to healthy communities, especially at a time when diseases like measles are making a comeback because some parents are opting out of immunizations for their kids. And it's not the only health news emerging from databases. The CDC analyzed data going back to 2005 to report last week that flu shots prevented some 6.6 million cases of the disease in the U.S. last year.
Project Tycho and other big health data sets hold promise that goes beyond reminding people that shots can prevent illnesses. The McKinsey Global Institute's October report on the economic potential of open data focused on seven sectors, one of which was health care. While McKinsey looked at health impacts in general, I was interested in how their insights about open data could apply to vaccines and vaccine-preventable illnesses.
Three ways to put big data to work
The McKinsey report estimates that smart use of open data can generate health care-related value of up to $450 billion annually in the U.S. This figure includes more than vaccines, of course, like encouraging lifestyle improvements, defining the best treatment protocols, and rooting out billing fraud. Among the possible improvements are ways to use shared data to get more people vaccinated, better protect at-risk populations, and monitor the impact (and side effects) of vaccines.
McKinsey describes a "right living" health category that would benefit from the use of apps to monitor lifestyle habits and chronic conditions. Why not have an app alert you when you need your tetanus booster or reach the recommended age for your first shingles vaccine? Apps supported by up-to-date data could also help travelers keep current on the shots they need before international trips, especially if they're headed to an infectious-disease hotspot. People with chronic health conditions like asthma that put them at high risk for flu complications could be notified as soon as the annual vaccine is available in their area. Children's Hospital of Philadelphia already offers an iOS app for parents who want reliable scientific information about childhood immunizations.
Big data can also streamline "right innovation," McKinsey says. This means using data to decide which clinical trials to fast-track, which research to shelve, and which initiatives to promote to the public. For instance, I'd love to know if this year's new quadrivalent flu shots from Sanofi Pasteur (NYSE: SNY ) , GlaxoSmithKline (NYSE: GSK ) , and AstraZeneca (NYSE: AZN ) subsidiary MedImmune—which protect against four strains of flu instead of the usual three—will have an impact on flu rates that justifies their higher cost. Will egg-allergic patients who can't get standard flu shots embrace the new hypoallergenic FluBlok shot from Protein Sciences, and how much will their infection rate fall as a result? Big data can check the results against the expectations.
Open data reporting could also help allay fears of parents who delay or refuse vaccines for their children because they fear adverse reactions. Real-time data monitoring could quickly identify problems with new vaccines, such as drug interactions or side effects like the rare but serious intestinal problems in babies that led to the 1999 withdrawal from the market of Wyeth's rotavirus vaccine. Careful and up-to-date data tracking could also prevent a repeat of the sloppy research that discredited researcher Andrew Wakefield used in the now-retracted Lancet report that started the measles vaccine panic by proposing a causative link between the shot and autism. (The CDC's Vaccine Adverse Event Reporting System database is already open to the public.)
Crowd-sourced care analysis
"Right care" is how McKinsey describes the analysis of big data sets to find the best treatments for particular diseases and conditions. By analyzing public health data on outbreaks of flu, meningitis, and other vaccine-preventable diseases, researchers can also help people in affected areas take steps to protect themselves.
Google (Nasdaq: GOOG) already tracks the flu across the U.S. to show where outbreaks are happening and where getting vaccinated is most urgent. This sort of tracking could be implemented worldwide using existing health data to analyze outbreaks of diseases such as polio, measles, and malaria. (GlaxoSmithKline will seek regulatory approval for its new malaria vaccine next year.)
Especially in regard to polio, real-time tracking is important for containing outbreaks. India made news and ruffled some feathers last week when it announced that Pakistani visitors must show proof of polio vaccination to enter the country. The Taliban's anti-vaccine campaign in Pakistan and Afghanistan has made those countries (along with Nigeria) the world's remaining reservoirs of polio—and doctors say the recent polio outbreak in Syria can be traced back to Pakistan.
Big hurdles to harnessing the power of big data
The McKinsey report points out that getting real value from big data will require real work. Data has to be standardized for analysis, patient privacy safeguards have to be put into place, interagency communication has to be streamlined, and someone has to pay for all of that.
Besides the logistical issues, there's the logic issue. Patients, doctors, and policymakers have to be willing to base their treatment decisions on what the data reveal rather than tradition, habit, and in the case of vaccine refusers, fear. But the potential payoff of big data is a healthier, richer world.
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