Notice2026-04560
Agency Forms Undergoing Paperwork Reduction Act Review
Primary source
Metadata and text below are from the Federal Register, a public-domain U.S. government work. Always verify the official published version before relying on it for any legal matter.
Published
March 9, 2026
Issuing agencies
Health and Human Services DepartmentCenters for Disease Control and Prevention
Full Text
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<title>Federal Register, Volume 91 Issue 45 (Monday, March 9, 2026)</title>
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[Federal Register Volume 91, Number 45 (Monday, March 9, 2026)]
[Notices]
[Pages 11313-11314]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2026-04560]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Disease Control and Prevention
[30Day-26-1391]
Agency Forms Undergoing Paperwork Reduction Act Review
In accordance with the Paperwork Reduction Act of 1995, the Centers
for Disease Control and Prevention (CDC) has submitted the information
collection request titled ``Enhancing Data-driven Disease Detection in
Newborns (ED3N)'' to the Office of Management and Budget (OMB) for
review and approval. CDC previously published a ``Proposed Data
Collection Submitted for Public Comment and Recommendations'' notice on
July 18, 2025 to obtain comments from the public and affected agencies.
CDC received 1,135 comments related to the previous notice. This notice
serves to allow an additional 30 days for public and affected agency
comments.
CDC will accept all comments for this proposed information
collection project. The Office of Management and Budget is particularly
interested in comments that:
(a) Evaluate whether the proposed collection of information is
necessary for the proper performance of the functions of the agency,
including whether the information will have practical utility;
(b) Evaluate the accuracy of the agencies estimate of the burden of
the proposed collection of information, including the validity of the
methodology and assumptions used;
(c) Enhance the quality, utility, and clarity of the information to
be collected;
(d) Minimize the burden of the collection of information on those
who are to respond, including, through the use of appropriate
automated, electronic, mechanical, or other technological collection
techniques or other forms of information technology, e.g., permitting
electronic submission of responses; and
(e) Assess information collection costs.
To request additional information on the proposed project or to
obtain a copy of the information collection plan and instruments, call
(404) 639-7570. Comments and recommendations for the proposed
information collection should be sent within 30 days of publication of
this notice to <a href="http://www.reginfo.gov/public/do/PRAMain">www.reginfo.gov/public/do/PRAMain</a> Find this particular
information collection by selecting ``Currently under 30-day Review--
Open for Public Comments'' or by using the search function. Direct
written comments and/or suggestions regarding the items contained in
this notice to the Attention: CDC Desk Officer, Office of Management
and Budget, 725 17th Street NW, Washington, DC 20503 or by fax to (202)
395-5806. Provide written
[[Page 11314]]
comments within 30 days of notice publication.
Proposed Project
Enhancing Data-driven Disease Detection in Newborns (ED3N) (OMB
Control No. 0920-1391, Exp. 4/30/2026)--Extension--National Center for
Environmental Health (NCEH), Centers for Disease Control and Prevention
(CDC).
Background and Brief Description
The Newborn Screening and Molecular Biology Branch (NSMBB), in the
National Center for Environmental Health (NCEH) Division of Laboratory
Science (DLS), has the only laboratory in the world devoted to ensuring
the accuracy of newborn screening (NBS) tests in every state and more
than 78 countries. NSMBB supports NBS programs by conducting research,
developing methods, and performing analyses by using complex, state-of-
the-art molecular and biochemical techniques for identifying risk
factors for diseases of public health importance. Both NSMBB and state
NBS programs are experiencing increased data analytic challenges
associated with continued expansion of the number of newborn screening
diseases, increased complexity of disease detection, and difficulties
in correlating disease markers with disease risk. Further, the addition
of late-onset diseases to NBS panels necessitates a better way to
routinely capture clinical information and outcomes so that NBS
programs can fully appreciate the spectrum of disease they are
detecting.
The NSMBB is requesting a three-year Paperwork Reduction Act (PRA)
clearance for Enhancing Data-driven Disease Detection in Newborns
(ED3N), a national NBS data platform, that will address these analytic
and post-analytic challenges and promote sharing of molecular,
biochemical, and clinical information amongst NBS partners. The
information will better equip NSMBB and newborn screening partners to
assess disease risk and will help harmonize approaches for disease
detection in newborns. Given the rarity of newborn screening diseases,
it is imperative that data be collected and analyzed at a national
level in order to glean useful insights and to analyze trends. The
NSMBB is best suited to oversee this work given its role in providing
technical assistance to NBS programs nationally.
Numerous studies along with presentations by NBS programs suggest
that gaps in programmatic resources and expertise are hampering the
ability to perform more complex data analytics resulting in low
positive predictive values for a number of conditions (which
subsequently results in higher false positive and negative rates and
downstream burden to families and the medical system). Smaller-scale
work on the use of post-analytical tools such as machine learning
algorithms have shown that incorporation of these elements into newborn
screening can improve detection rates, while reducing false positives.
These studies, however, have been limited to single sites and have not
been integrated into the daily workflow of high-throughput NBS
programs. Without this project, NBS programs will continue to be unable
to keep up with the increasing complexity and future demands of
screening, perpetuating inequities in screening across the nation.
Since approval, the CDC's ED3N project has worked with fourteen NBS
programs to develop and pilot one of the modules, providing the needed
platform to assist states in expanding their screening and
interpretation capacity. Additional programs have been engaged in
defining the other modules and in piloting data transfer mechanisms.
The estimated annualized burden hours were determined as follows.
There are 53 domestic NBS programs in the United States. A
``respondent'' refers to a single NBS program. Given that data
submission will ultimately be accomplished through automatic electronic
data transfer, each respondent's burden hours were split into two
estimates: (1) the one-time need to set-up, test, and implement the
electronic data transfer mechanism; and (2) the ongoing automatic
electronic data transfer occurring after initial set-up. Initial set-up
time burden was estimated based on analysis of similar data transfer
projects embarked upon by NBS programs as well as brief discussions
with NBS Program Laboratory Information Management System vendors. The
one-time burden to set-up the data transfer interface was estimated to
be 40 hours total, annualized to 14 hours per year per respondent.
Ongoing daily data submission burden was estimated assuming one minute
for each automatic transfer thereafter. CDC has estimated the total
annualized burden for this project to be 1,064 hours per year.
Estimated Annualized Burden Hours
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Average
Number of Number of burden per
Type of respondent Form name respondents responses per response (in
respondent hr)
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Newborn Screening Programs......... Set-up and initial 53 1 14
submission of ED3N Data
Elements.
Ongoing transfer of ED3N 53 365 1/60
Data Elements.
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Jeffrey M. Zirger,
Lead, Information Collection Review Office, Office of Public Health
Ethics and Regulations, Office of Science, Centers for Disease Control
and Prevention.
[FR Doc. 2026-04560 Filed 3-6-26; 8:45 am]
BILLING CODE 4163-18-P
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