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Businesses Mine Data To Predict What Happens Next
Real-time information is no longer fast enough for some companies. The trend is applying predictive analysis to everything from patient care to airline safety.
May 26, 2006
4 Min Read
It Gets Personal
As electronic health records become more prevalent, those databases will provide a rich source of information for predictive analysis. Blue Cross Blue Shield of Tennessee has used a neural net-based predictive model from MEDai for the past 18 months to analyze claims data to predict which health care resources individual members will need months and even years into the future.
"If we're seeing a pattern that predicts heart failure, kidney failure, or diabetes, we want to know that as soon as possible," says Soyal Momin, manager of research and development and consulting at the insurer. While Momin says the technology can't predict disease, it can portend the severity of an illness.
Children's Memorial Research Center in Chicago hopes to come one step closer to actually predicting the recurrence of tumors. It uses SPSS's Clementine data mining software to classify pediatric brain tumors. Then, using predictive analytics, genomic research, and tools that search electronic medical texts for relevant information, doctors can determine the best therapy and predict the probability that a tumor will recur. "I think this idea is going to go hand in hand with personalized medicine," says Dr. Eric Bremer, director of the center's brain tumor research program.
In the airline industry, the FAA just started a program to correlate pilot health and aircraft accidents. The agency is applying S-Plus and Insightful Miner predictive analysis software from Insightful to cross-analyze information about plane crashes and pilot incapacitation incidents with data on pilot health and certification. (Private and commercial pilots are required to have regular medical exams, and the results are maintained in an FAA database that holds 15 million records.)
Researchers plan to examine pilot cardiovascular and neurological conditions for possible links to accidents, as well as scrutinize whether pilot age is a factor in flight safety. "Can we spot an issue before it becomes a safety problem, like older pilots taking up flying later in life?" asks Stephen Veronneau, bioinformatics research team leader for the FAA's Civil Aerospace Medical Institute. The program, which uses medical data that doesn't identify individual pilots, also will look for markers in pilots' blood, such as sugars and even genomic data, that indicate a pilot is more susceptible to fatigue. "But that's way out there," Veronneau concedes.
Valen's Vlasimsky says his company's technology can similarly be used to examine telematics data collected from trucks to identify drivers who may be at risk for getting into accidents because of their driving habits or susceptibility to fatigue.
All this data analysis raises ethical questions. Will predictive analytics lead to mass profiling, denying people jobs because of their genes or denying them insurance coverage because of their predicted health conditions? "You could certainly imagine some kind of Orwellian system with all kinds of data," the FAA's Veronneau says.
The police in Richmond are considering adding more data to their system, such as intelligence from informants about drug dealers and gangs, and even the crime records of individuals, to determine their propensity to commit more crimes. While privacy advocates are sure to squeal, Chief Monroe thinks he's on solid ground using hard data rather than discredited practices like racial profiling.
At Blue Cross Blue Shield of Tennessee, Brooks is aware of the potential misuse of predictive technology and says the insurer would never deny coverage to subscribers based on a predicted health condition. We'll see.
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