Recommendations and Actions
Each State Employment Security Agency (except the Virgin Islands) is required to conduct a benefits quality control (BQC) program. Several state agencies have reported problems with this program indicating that it uses scarce staff resources to identify the same types of payment errors--quarter after quarter, year after year--and that it measures only one aspect of the quality of the unemployment insurance program, i.e., benefit payment accuracy. These agencies also believe it fails to improve the quality of the program. The states maintain that little attention is paid to correcting errors identified through the BQC program.
Under the BQC program, states are required to perform an in-depth audit on a sample of at least 400 paid claims annually. The Department of Labor (DOL) determines the actual sample based on a state's size and needs for precision. The audit involves interviewing the individual claimants and verifying base period wages, job search contacts during the week in question and all other aspects of their eligibility. Done almost entirely in person through June 1993, each audit averaged about 13 hours. A new auditing methodology, introduced in July 1993, combines telephone, mail, and facsimile communication with in-person contact. These procedures were designed to reduce the audit to approximately 10.5 hours. As data are verified, they are entered into a computer provided through BQC for analysis by the state, and then transmitted to DOL.
These audits are used to estimate each state's proper payment and payment error rates and to identify the party responsible and the reason for improper payments. The largest dollar errors identified are due to claimants' working while claiming benefits, their failure to meet work search requirements, and their being separated from their jobs for reasons that should disqualify them from receiving benefits. Because of their unique unemployment insurance laws, states have the primary responsibility for analyzing BQC data and using it to improve program operations.
Each June, states must report to the public the findings for the preceding calendar year, which DOL then releases in a compendium in July. Data release is intended to get interest groups involved in unemployment insurance improvement at the state level. Some states contend that DOL does make some use of the reports, but DOL has poorly explained how the information gathered applies to effective management.
A review of several state employment security offices provided differing opinions on the value of BQC data. Some office directors report that the data are necessary because of the potential for overpayments in a program distributing more than $33 billion in funds annually.
Many states take the position that something must be done because the data are not being used in a manner that justifies the cost. Recommendations from some states range from reducing the number of cases reviewed to abolishing the program altogether. Others call for a combination of actions, including an explanation of how the data are improving the quality of the program.
DOL is aware of state dissatisfaction with the BQC program. The department agrees that, despite efforts to promote analysis and improvement actions through small funding grants, information sharing, training, and provisions for collecting more state-specific information, the anticipated level of BQC-inspired state analysis and corrective actions has not been forthcoming. As originally planned, some BQC resources are now being shifted from BQC activities. About one-tenth of the resources potentially available for BQC will be used to examine the quality of unemployment insurance tax operations through the newly developed Revenue Quality Control (RQC) program. However, DOL contends that BQC is indispensable, because it measures total payment accuracy in a way that is considered to be statistically valid. This measure is essential for state management and federal oversight. The Office of Management and Budget (OMB) considers the unemployment insurance accuracy rate to be an essential measure of the Unemployment Insurance program's accomplishments, which is required by the Chief Financial Officers Act.
The DOL should reexamine the present mix of systems for improving the performance of the unemployment insurance program, and devise a unified strategy that improves its effectiveness.
This reexamination will include a substantial focus on the BQC program and how its resources can best be divided between measurement, analysis, and direct support for program improvement. In addition, DOL should consider the extent to which the BQC performance measurement will continue to keep its existing focus on paid claims in unemployment insurance core programs, or will include measurement of decisions to grant or deny claims or activities designed to strengthen the quality of the unemployment insurance program.
The $34 million currently spent on the unemployment insurance quality control program now goes mostly to measure the accuracy of paid claims ($2 million funds RQC, and roughly $1 million is diverted to state-designed studies to craft program improvements). Some of the resources could be employed more directly in drawing implications from the performance measures for program improvement, or used to improve benefit payment processes or to measure other areas to complement existing measures, e.g., denied claims.
The net result is intended to be a shift in focus from error measurement to constructive use of the results to improve benefit payment quality and more effectively achieve the unemployment insurance program's goals.
States were allocated approximately $34 million to operate BQC programs in fiscal year 1993, which is about 1.7 percent of the $2 billion states receive to administer the unemployment insurance program. These funds can be used more efficiently if DOL, in consultation with the state agencies operating the program, can identify the combination of activities that will lead to program improvements. The net result is expected to be a shift of resources from performance measurement activities to data analysis and process improvement. The magnitude of the shift cannot be projected in advance of the policy review. Thus, the fiscal implications cannot be estimated.
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