Big Data Could Mean Big Problems for Healthcare
Source: David Lazarus
The future of the U.S. healthcare system will be influenced to a large extent by a company that makes weapons of war.
Defense giant Northrop Grumman has signed a nearly $92-million contract with the Centers for Medicare and Medicaid Services to build the second phase of a computer system that's currently focused on reducing fraud but down the road will play a greater role in anticipating beneficiaries' medical disorders.
It's the most prominent example of how public and private insurers are spending millions of dollars on "big data" -- using advanced technology to predict people's future healthcare needs based on their interactions with doctors, hospitals and pharmacies, as well as information gleaned from other sources, such as social media.
Such systems, known as predictive analytics, aim to make healthcare more efficient and effective by opening the door to addressing medical issues before they become serious problems.
For example, you've complained to your doctor that you're having trouble losing weight. You're taking a cholesterol medication. You've posted on Facebook that you're feeling stressed because you've separated from your spouse or on LinkedIn that you're looking for a new job.
A big data algorithm would connect the dots and alert your doctor that you're running a risk of a heart attack. It would recommend immediate medical intervention.
"There are tremendous advantages to big data in healthcare," said Gerard Magill, a professor of healthcare ethics at Duquesne University in Pittsburgh. "It's about creating a comprehensive approach to using medical information."
The trade-off: Say goodbye to individual privacy.
"Big data requires that information; it's nonnegotiable," Magill said. "Individual privacy is gone for the common good."
Medicare's contract with Northrop Grumman is one of the largest efforts underway to create a healthcare crystal ball capable of looking into patients' futures.
"The use of data in healthcare is absolutely critical," said Dr. Shantanu Agrawal, director of Medicare's Center for Program Integrity, which is tasked with lowering costs. "Having it be predictive of various issues is extremely important."
Medicare has been criticized in the past for using a "pay and chase" approach to fraud -- that is, paying all 4.5 million claims that are submitted daily and then attempting to determine which ones may have been bogus and trying to reclaim the funds.
Rep. Peter Roskam (R-Ill.), chairman of the House Ways and Means Oversight Subcommittee, said at a hearing on healthcare fraud last month that the agency needs to move faster in implementing "better data analysis and predictive analytics."
Medicare says the first phase of its Northrop-designed fraud-detection system produced more than $1 billion in savings over the last two years.
Amy Caro, vice president of Northrop's healthcare-technology division, told me it's clear that sophisticated algorithms are the best way to spot and crack down on fraudulent medical claims. They're capable of sifting through millions of submissions and recognizing signs and patterns that indicate a claim may not be on the up and up.
The next step, she said, will be using big data capabilities to get ahead of Medicare and Medicaid beneficiaries' healthcare needs.
"You have all types of data out there and available," Caro said. "You're able to drill down and look for signs of certain diseases or conditions."
I shared my own experience as an example. Because Type 1 diabetes runs in my family, over the years I've routinely asked physicians to test to make sure I wasn't at risk of coming down with the disease. Even though I was prone to low blood sugar, doctors informed me again and again that I was fine.
A decade ago, I was diagnosed with the chronic condition.
"That's a perfect example," said Dr. Sam Shekar, chief medical officer for Northrop's Technology Services division. "The kind of system we're designing would have seen that you may be in a pre-diabetes stage. It allows you to get ahead of diseases before they're diagnosed."
In my case, the episodes of low blood sugar were the red flag, he said. Coupled with my family history -- which a national DNA database would know -- my doctor could have been more proactive in keeping diabetes at bay.
The thing about big data, though, is that it's more effective the bigger it gets. Agrawal at Medicare said the program is eager to share information and algorithms with private insurers. Most private insurers, meanwhile, are busy developing their own predictive analytical systems.
Anthem, one of the country's largest private insurers, is typical of the industry. Like Medicare, the company wants to find high-tech ways to reduce fraud and improve the well-being of those it covers.
Ariel Bayewitz, Anthem's vice president of provider analytics, said the goal is to crunch data from multiple sources, including claims for doctor, hospital and drugstore visits, and to be able to alert an individual's physician that there may be an issue that needs attention.
"We have a unique lens because of the access we have to claims data," he said.
Are people deemed to be at higher risk of a disease or condition in danger of insurance rate hikes? At this point, the answer is no.
Obamacare protects people in the individual insurance market. People in large employer-sponsored plans who submit expensive claims can have an impact on overall rates, but such price increases are spread throughout the entire coverage group.
Yet most experts I spoke with said big data for healthcare is largely uncharted territory, and it's still unclear how the advent of vast troves of available medical information will affect public and private insurers.
Similarly, existing privacy laws for medical data may be insufficient to address the scope of information sharing on the horizon.
"There are definitely protections that we need to put in place that haven't been put in place," acknowledged Bayewitz.
Northrop's Caro said that "there will have to be a national conversation" about big data's use of medical info and overhauling the existing regulatory structure to reflect a need for additional safeguards.
"We're not there yet," she said.
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