Dec 31 2009

Money Matters

Does Labor have the answer to the multibillion-dollar problem of federal misspending?

Photo: Drake Sorey
At Labor, CFO Samuel Mok says he's testing a
financial early warning system that will help the
department catch mispayments before they happen.

Whether you call it found money or a $45 billion money pit, what agencies mispay each year is no longer a secret, something hidden away in financial spreadsheets.

The problem of inaccuracies in benefits—predominantly overpayments—paid to citizens enrolled in a variety of federal programs first gained wide attention three years ago when Congress passed the Improper Payments Information Act, which mandated that agencies set plans for reining in errant spending.

This year, to prod agencies to meet the mandates, the White House added the category to the President's Management Agenda scorecards and began rating agencies' progress in reducing mispayments. Even so, improper payments continued to grow last year, to $45.1 billion—up $10 billion governmentwide from 2003.

Now the Labor Department may be pointing the way for how agencies can combine data analysis technology with interagency and state collaboration to reverse the overpayments trend. And, the Office of Management and Budget has taken notice.

"Agencies are examining current best practices for eliminating improper payments," a senior OMB official says. "The solutions that DOL is currently employing and planning are a key part of this process. Notably, many agencies are seeking to implement the types of data matches that DOL has started implementing."

But others worry that cross-jurisdictional data sharing might open the door to privacy issues.

"An ongoing balance needs to be achieved between making sure the government doesn't waste taxpayer money with overpayments and that it uses all the information available to keep from doing that," says Frederick Thompson, vice president for management and technology at the Council for Excellence in Government in Washington. "On the other hand, agencies must ensure that people have trust in the government and that it's going to use all the information that people disclose accurately and fairly."

For now, Labor is walking that line and pushing forward with its efforts to reduce mispayments.

Modest Progress

The latest PMA scorecards show how thorny the problem can be. No agency has reached green, or success, in the payments category, and fewer than half have attained yellow, meaning they've made some progress. Eight have remained in the red, or unsatisfactory, ranks.

Currently ranked yellow, Labor is focusing on mispayments in the department's unemployment insurance program, which accounted for $4 billion in problem payments last year.

By matching data from the Health and Human Services Department's National Database of New Hires with its own payment records, Labor expects to identify double dippers—people who continue to collect unemployment insurance after they return to work.

This interagency data sharing needed a push from the law enacted last summer that gave states access to the new hires database for employment monitoring. Labor also joined forces with the Social Security Administration to let states exchange data for verifying workers' identities and spotting fraud or mistakes tied to Social Security numbers.


Total Effect

Labor expects these collaborations will reduce unemployment insurance overpayments by $74 million this year, $259 million by 2007 and $371 million over the next decade.

But achieving widespread data sharing hasn't been easy. Because the unemployment insurance programs have many stakeholders, "reaching consensus across all states for technical and operational parameters is a challenge," Labor CFO Samuel Mok says.

Determining ways to measure the effectiveness of the HHS and SSA database access programs can also be difficult, he adds. "The HHS pilot program and the SSA data exchange are both new and are still being evaluated."

For the future, Mok is working on what he calls a financial early warning system—a desktop PC dashboard with indicators that flag existing or impending problems. So far, the system is only a prototype.

"The performance indicators cascade, allowing access to information in varying levels," he explains. "The user has the option to drill down into the data and access detailed information should additional information be required."

The data-matching initiatives run in conjunction with reductions that follow Labor's hiring of a contractor to process and pay Federal Employees Compensation Act medical claims. The contractor uses proprietary software to screen for hospital billing errors.

The department also plans to launch an automated tracking system to uncover claims paid to people whose improved medical condition makes them ineligible for benefits.

To stop overpayments before claims are paid, Labor uses commercial software that analyzes historical data to detect patterns in billing that may indicate fraud. The software also checks for duplicate payments, checks payments relative to a database of clinical rules and monitors physicians' reports for questionable billing inconsistencies, Mok says.

"The increased automation of [the FECA] process has made possible several controls, including the automation of fee calculations where applicable to reduce the possibility of improper payments," he says. "Inpatient bills with no Medicare numbers are suspended or denied, and system edits deny potential duplicate payments."

Although the government's efforts at reducing errant payments are chalking up successes, agencies need to monitor closely the routine exchange of personal information, including Social Security numbers, says Alan Webber, a senior government analyst for Forrester Research of McLean, Va.

"This really exposes information to privacy and security issues," Webber says. "It comes down to what the information was originally gathered for. Even with the passage of the Improper Payments Acts of 2002, we still haven't gotten away from the fact that personal information is gathered for specific purposes and the data may not necessarily be used for another purpose."

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