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FCW : April 30, 2015
trying to distill it down to universal truths.” 18 April 30, 2015 FCW.COM Big data organization’s CDO or CDS is to help their organization acquire, process and lever- age data in a timely fashion to create efficiencies, iterate on and develop new products, and navigate the competitive landscape.” Patil pointed to NIH’s Pre- cision Medicine Initiative as a federal priority. That effort, as NIH describes it, is “an emerg- ing approach for disease treat- ment and prevention that takes into account individual vari- ability in genes, environment and lifestyle.” And he said NIH and other agencies “will work to deliver not just raw data- sets, but also value-added ‘data products’ that integrate and usefully present information from multiple sources.” Under the initiative, investigators plan on ana- lyzing the genes, electronic health records and lifestyles of at least 1 million Americans. One of the agencies leading the way in terms of business intelligence is the Centers for Medicare and Medicaid Services. The agency’s Office of Enterprise Data and Analytics, launched last November, could serve as a case study for other federal agencies because it has such a clearly defined structure and detailed mission statement. Niall Brennan, who helped establish the unit, is its director and chief data officer. And just like a commercial entity, the office contains an Information Products Group, a formal acknowledgment of the role an agency can play in packaging information that helps support decision-making both inside and outside the government. That’s an especially important role at CMS: The agency is becoming one of the analytical engines behind health care reform. In addition to gathering and analyzing information on payments and medical conditions related to Medicare, Medicaid and the Children’s Health Insurance Program, CMS is also responsible for analyzing other data related to programs that seek to reduce the costs and increase the efficiency of health care delivery. The agency’s spending reflects that focus. In fiscal 2014, CMS spent $32.6 million on contracts for analytics, dash- boards and reporting — second only to NASA in total spend- ing in that area, according to government market analytics company Govini. And although it is not immune to complaints about the usability of its data, the Office of Enterprise Data and Analytics has managed to keep the public focused on how the health care industry operates and what that means for pub- lic pocketbooks. For example, its release of data on hospital charges nationwide gener- ated front-page headlines and academic analyses about the potential social impact of wide- spread discrepancies in charg- es for similar procedures. Its release of the payment records for the 880,000 doctors and other health care providers paid by Medicare in 2014 had a similar impact. CMS’ Fraud Prevention Sys- tem is another widely lauded example of a successful big-data project. The system, which launched in 2011, analyzes the 4.5 million claims that flow in daily from the 1.5 million Medicare providers. It uses predictive algorithms that rely on a variety of factors — such as payment patterns, contact information, tips and detailed, eight-year-long historical records — to help CMS detect suspicious patterns in billing activity. The system also helps law enforcement officials speed up their inves- tigations and prosecutions. As with NIH’s Alzheimer’s portal, CMS has emphasized the importance of assembling a multidisciplinary team whose members work together to analyze information and achieve the project’s goal. In this case, a team that included policy experts, clinicians, field investigators and data analysts developed and tested 74 models used to flag potential cases of fraud, waste or abuse. In a report to Congress in June 2014, CMS officials wrote that “bringing together teams with a variety of skill sets is a best practice in model development — ensuring that the [Fraud Prevention System] models yield solid, actionable leads.” CMS awarded the contract for developing the system to Northrop Grumman and the modeling contract to IBM. Fifteen full-time staff members oversee the system and run the analytics part of the program. A CMS spokesperson told FCW it is crucial to involve the end users of the analytics system from the beginning of the development process and on an ongoing basis so that In my opinion, this is a big-data project in that it is taking a large amount of information and trying to distill it down to universal truths.” — LARA MANGRAVITE, SAGE BIONETWORKS, ON THE NIH ALZHEIMER’S PORTAL 0430fcw_016-021.indd 18 4/8/15 2:35 PM
April 15, 2015
May 15, 2015