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HHS/OS | RIN: 0991-AC19 | Publication ID: Fall 2020 |
Title: Direct Regulatory Clean Up Initiative | |
Abstract:
This direct final rule will correct citations, remove erroneous language, or correct misspellings and other typographical errors in response to findings from an Artificial Intelligence (AI) project. HHS piloted a new method of regulatory analysis, using an AI-driven tool that analyzed HHS’s regulations using Natural Language Processing (NLP). This NLP analysis is designed to accelerate and augment expert review, allowing HHS Subject Matter Experts (SMEs) to focus on areas of opportunity for modernization. The NLP analysis revealed numerous reform opportunities, including instances where a regulation citation is now incorrect. |
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Agency: Department of Health and Human Services(HHS) | Priority: Economically Significant |
RIN Status: Previously published in the Unified Agenda | Agenda Stage of Rulemaking: Final Rule Stage |
Major: Undetermined | Unfunded Mandates: No |
EO 13771 Designation: Not subject to, not significant | |
CFR Citation: Not Yet Determined (To search for a specific CFR, visit the Code of Federal Regulations.) | |
Legal Authority: Not Yet Determined |
Legal Deadline:
None |
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Statement of Need: Executive Orders 13771 and 13563 both emphasize the importance of retrospectively reviewing existing regulations in order to achieve these objectives. In particular, section 6 of EO 13563 asks agencies to consider how best to promote retrospective analyses of rules that may be outmoded (76 FR 3822). HHS is committed to the Administration’s vision of reducing regulatory burden and modernizing the CFR and has continued to execute regulatory reform through new and innovative methods. In the past, regulatory analysis and reform has been a largely manual process, limited by each expert’s experience with a particular subset of agency regulations, and it has been labor-intensive and time-consuming to find regulatory reform opportunities through this manual review. In addition, unless a portfolio of minor changes can occur through a consolidated regulatory vehicle, it is often administratively impractical to implement many results of retrospective review; this relative infeasibility of implementation may in turn discourage the identification and correction of many small but valuable refinements to existing regulations. However, HHS has piloted a new method of regulatory analysis, using an artificial intelligence-driven tool that analyzed HHS’s regulations using natural language processing (NLP) as applied to the regulatory text in the CFR. This NLP analysis is designed to accelerate and augment subject matter expert (SME) review, by highlighting candidate provisions that could be outmoded, allowing HHS SMEs to focus on these provisions as potential areas of opportunity for modernization. The revisions outlined in this rule represent a portion of the results from this effort, and are focused on administrative, non-substantive changes that will clean up HHS’s regulations. |
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Timetable:
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Regulatory Flexibility Analysis Required: No | Government Levels Affected: None |
Small Entities Affected: No | Federalism: No |
Included in the Regulatory Plan: Yes | |
RIN Data Printed in the FR: No | |
Agency Contact: Douglas Cheung Program and Policy Analyst Department of Health and Human Services Office of the Secretary 200 Independence Avenue SW, Washington, DC 20201 Phone:202 260-6874 Email: douglas.cheung@hhs.gov |