“I think I could better predict someone’s risk of a heart attack based upon their Visa bill than their genome,” said Harry Greenspun, MD, director of the Center for Health Solutions at Deloitte, according to the report.
According to Dr. Greenspun, who heads up a team that mines data for health insurers, numerous habits could be predictors of an individual’s health. Even simple measures like a person’s ethnicity can help insurers anticipate health issues.
After gleaning such data, insurers can take one of two approaches. Some choose to be aggressive in their intervention measures, such as sending a patient a scale if he or she has congestive heart failure. Others choose not to interfere.
The data mining technique has been taken up by a variety of insurers, including Aeta, which used GNS Healthcare to predict which of their patients were at risk of metabolic syndrome.
Regardless of how helpful it may be, the phenomenon has also faced pushback. Many privacy advocates are concerned that insurers are using private patient information without informed consent.
Others believe data mining has little value — especially when the data is variable. “If you’ve got unreliable data, you’re going to make unreliable decisions,” said Doug Fridsma, MD, PhD, president of the American Medical Informatics Association, according to the report. This was the case when, after being prescribed asthma medication for a case of the flu, a six-year-old girl in Hawaii received a letter from her insurer encouraging her to quit smoking.
More articles on payer issues:
Sen. Blumenthal urges UnitedHealth Group CEO to reassess leaving ACA exchanges
PPOs fade from ACA exchanges: 6 things to know
HealthSpan to dissolve medical group, close 11 facilities
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