Justification and Anticipated Results. A. Cost Benefit Analysis As required by § 552a(u)(4) of the Privacy Act, a cost benefit analysis (CBA) is included as Attachment 1, covering this and seven other “Marketplace” matching programs which CMS conducts with other Federal agencies. The CBA demonstrates that monetary costs to operate the eight Marketplace matching programs exceed $30.5 million, but does not quantify direct governmental cost saving benefits sufficient to offset the costs since the Marketplace matching programs are not intended to avoid or recover improper payments. The CBA, therefore, does not demonstrate that the matching program is likely to be cost- effective.
B. Other Supporting Justifications Although the cost benefit analysis does not demonstrate that this matching program is likely to be cost effective, the program is justified for other reasons, as explained in this section. The DIB therefore is requested to make a determination, in writing, that the cost benefit analysis is not required, in accordance with 5 U.S.C. § 552a(u)(4)(B), and to approve the agreement based on other factors.
a. Certain Marketplace matching programs are required and are not discretionary. However, some Marketplace matching programs are based on VHA’s permissive routine use disclosure authority, not a statutory obligation.
b. The Marketplace matching programs’ eligibility determinations and MEC checks result in improved accuracy of consumer eligibility, which CMS anticipates will continue to produce expedited Eligibility Determinations while minimizing administrative burdens and achieve operational efficiencies.
c. The matching programs provide a significant net benefit to the public by accurately determining eligibility for the APTC.
d. An efficient eligibility and enrollment process contributes to greater numbers of consumers enrolling in Marketplace qualified health plans, resulting in a reduction of the uninsured population, therefore improving overall health care delivery.
e. Continuing to use the current matching program structure, which is less costly than any alternative structure, is expected to increase the public’s trust in the participating agencies as stewards of taxpayer dollars.
C. Specific Estimate of Any Savings There is no cost savings to conducting the Marketplace matching programs, as opposed to not conducting them. By requiring a single, streamlined application process, the ACA effectively required use of computer matching to make eligibility determinations. Therefore, the optim...
Justification and Anticipated Results. The Privacy Act requires that each matching agreement specify the justification for the program and the anticipated results, including a specific estimate of any savings. 5 U.S.C. § 552a(o)(1)(B).
Justification and Anticipated Results. A. Cost Benefit Analysis
Justification and Anticipated Results. A. Cost Benefit Analysis A detailed cost benefit analysis for the PARIS matching programs (this matching program providing VA compensation and pension payment data, the federal data matching program using data from the Department of Defense, and the interstate data matching program) is included as Attachment D: Cost Benefit Analysis for PARIS Computer Matching Programs to this agreement. The analysis demonstrates that the PARIS matching programs are likely to be cost effective.
B. Other Supporting Justifications States must verify client circumstances when determining an applicant’s eligibility for public assistance benefits. The parties to this agreement have determined that a computer matching program is the most efficient, expeditious, and cost-effective means of verifying client declarations of income circumstances. The principal alternative to using a computer matching program for identifying such individuals would be to conduct a manual match; however, this would clearly impose a considerable administrative burden, constitute a greater intrusion of individual’s privacy, and result in additional delay in the eventual recovery of any outstanding debts. By contrast, when using computer matching, the information on successful matches (hits) can be provided within thirty (30) days of receipt of an electronic file of SPAA beneficiaries.
C. Specific Estimate of Any Savings The programs impacted are under the auspices of the Department of Health and Human Services (i.e., CMS’s Medicaid program and ACF’s TANF program) and the Department of Agriculture (i.e. SNAP program administered by FNS), which are administered by the States (i.e., by SPAAs and their sister agencies). Each SPAA collects information on the costs and benefits related to its state’s use of VA’s information. All savings resulting from PARIS matching program data are in state program dollars, because no costs are paid by SPAAs to either ACF or DMDC to participate. Additionally, GAO, in its 2001 report Public Assistance: PARIS Project Can Help States Reduce Improper Benefit Payments, projected that if States included PARIS data from the TANF, Medicaid, and SNAP programs in their matching activities, the benefit to cost ratio would be approximately 11:1 (GAO 01-935, pp. 14, 15). Recent data received by ACF from states continues to suggest that the PARIS is a cost- effective program. See Attachment D: Cost Benefit Analysis for PARIS Computer Matching Programs, including section “Recent PARIS Succe...
Justification and Anticipated Results. A. Cost Benefit Analysis As required by 5 U.S.C. § 552a(u)(4), a Cost Benefit Analysis (CBA) was prepared for this matching program by CMS and VHA, which is included as Attachment A. The CBA reflects that total costs to conduct the matching program are estimated to be $6,330,024 and total monetary benefits of the matching program are estimated to be $45,000,000 for the first 12-month period of the Agreement. The CBA, therefore, demonstrates that the matching program is likely to be cost effective.
Justification and Anticipated Results. A. Cost-Benefit Analysis As directed by the Privacy Act at 5 U.S.C. § 552a(u)(4)(A), the FCC has conducted a cost-benefit analysis of this matching program. This analysis, which is attached to this Agreement as Attachment 1, demonstrates that the Federal Programs are cost effective, and includes a specific estimate of the savings.
Justification and Anticipated Results. The disclosure of NDNH information for the research conducted by OPRE is justified for several reasons. Employment and earnings outcomes are critical measures of the success of TANF programs’ efforts to promote self-sufficiency. The NDNH is a centralized database of new hire, quarterly wage, and unemployment insurance information, providing an effective and efficient means for OPRE to obtain employment and earnings data, and to track that information over an extended period. Baseline and follow-up new hire, quarterly wage, and unemployment insurance information allows the analysis of income and benefits receipt, job stability, job changes, and re- hire. The use of NDNH records is preferable to the use of state records as a source of information for research purposes because the NDNH contains individual employer, wage, and unemployment insurance records across states, uses a uniform format for records, includes employment information pertaining to federal employees, and is systematically and consistently collected and submitted to the NDNH by employers and state workforce agencies. NDNH records can be collected for a large number of individuals relatively cost-effectively and data request processes are well-defined. Lastly, security and access provisions for NDNH research purposes are clearly defined. OPRE anticipates that the NDNH information from new hire, quarterly wage and unemployment insurance information is the best way to evaluate the employment and unemployment status of TANF recipients and the effect of the economy on TANF recipient employment long-term. Use of the NDNH, will allow OPRE to complete statistical analyses that include geographic and demographic information and case-level information that will inform the agencies on employment trajectories and experiences of low wage workers and their families, including the impact of Covid-19.
Justification and Anticipated Results
