Notice2022-25992
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
November 29, 2022
Issuing agencies
Health and Human Services DepartmentCenters for Disease Control and Prevention
Full Text
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<title>Federal Register, Volume 87 Issue 228 (Tuesday, November 29, 2022)</title>
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[Federal Register Volume 87, Number 228 (Tuesday, November 29, 2022)]
[Notices]
[Pages 73311-73313]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2022-25992]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Disease Control and Prevention
[30-Day-23-22BC]
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
[[Page 73312]]
review and approval. CDC previously published a ``Proposed Data
Collection Submitted for Public Comment and Recommendations'' notice on
December 6, 2021 to obtain comments from the public and affected
agencies. CDC received one comment 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 comments within 30 days of notice
publication.
Proposed Project
Enhancing Data-driven Disease Detection in Newborns (ED3N)--New--
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 new 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.
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. For purposes of annualizing this component of burden
over the three-year period of this request, the 53 respondents are
represented as 18 respondents in the table below (53/3 = 17.67, rounded
to 18). Ongoing daily data submission burden was estimated assuming
automatic transfer thereafter, 365 days per year. The estimated burden
per response is one minute.
CDC requests OMB approval for an estimated 1,042 annualized burden
hours. There are no costs to respondents other than their time to
participate.
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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 of ED3N Data 18 1 40
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 Scientific
Integrity, Office of Science, Centers for Disease Control and
Prevention.
[FR Doc. 2022-25992 Filed 11-28-22; 8:45 am]
BILLING CODE 4163-18-P
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