Agency Forms Undergoing Paperwork Reduction Act Review, 63956-63957 [2023-20066]

Agencies

• Centers for Disease Control and Prevention
• DEPARTMENT OF HEALTH AND HUMAN SERVICES

[Federal Register Volume 88, Number 179 (Monday, September 18, 2023)]
[Notices]
[Pages 63956-63957]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-20066]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

[30Day-23-23FJ]


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 ``Evaluating Deep Learning Algorithm 
Assessment of Digital Photographs for Dental Public Health 
Surveillance'' 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 June 5, 
2023 to obtain comments from the public and affected agencies. CDC 
received two comments. 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 www.reginfo.gov/public/do/PRAMain. 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

    Evaluating Deep Learning Algorithm Assessment of Digital 
Photographs for Dental Public Health Surveillance--New--National Center 
for Chronic Disease Prevention and Health Promotion (NCCDPHP), Centers 
for Disease Control and Prevention (CDC).

Background and Brief Description

    By age 19, 57% of U.S. adolescents have experienced tooth decay and 
17% have at least one decayed tooth needing treatment. Prevalence of 
untreated tooth decay among non-Hispanic Black and Mexican American 
adolescents is about 30% higher than among non-Hispanic White 
adolescents, and among low-income, almost twice the prevalence of 
higher-income adolescents. Untreated tooth decay will not resolve and 
can cause pain, infection, and difficulties in learning. Poor oral 
health in youth is associated with both lower school attendance and 
grades. More than 34 million school hours are lost annually due to 
unplanned dental visits for acute care needs. Reducing the percentage 
of youths who have experienced tooth decay and the percentage with 
untreated tooth decay are national health goals (Healthy People 2030).
    There are two highly effective interventions to prevent tooth 
decay. Dental sealants prevent about 80% of cavities over two years in 
the permanent molars where about 90% of tooth decay occurs. Fluoride 
can prevent decay in permanent teeth by 15% to 43% per year depending 
on mode of delivery. Although the American Dental Association 
recommends dentists provide topical fluoride and dental sealants to 
youth at risk for caries, uptake of these services is low with about 
20% of low-income youth receiving them during an annual dental visit. 
Access to these preventive services as measured by dental sealant 
prevalence and receipt of preventive dental services among low-income 
children are national health goals.
    The Centers for Disease Control and Prevention (CDC) has collected 
national data on caries, sealant, and fluorosis prevalence in the 
National Health and Nutrition Examination Survey (NHANES) for over 30 
years and has supported State oral health programs to collect data on 
caries and sealant prevalence through cooperative agreements since 
2001. Twenty States are currently funded from September 2018 to August 
2023 by Actions to Improve Oral Health Outcomes, CDC-RFA-DP18-1810. 
Collecting these data can be resource intensive as they are obtained 
through visual/tactile examinations conducted by dental professionals. 
These data, however, have enabled Federal and State agencies to: (1) 
prioritize groups at elevated risk for enhanced prevention efforts; (2) 
monitor trends in children's oral health status and disparities; (3) 
inform planning, implementation and evaluation of effective oral health 
interventions, programs, and policies; (4) measure progress toward 
Healthy People objectives; and (5) educate the public and policy makers 
regarding cross-cutting public health programs. Having local estimates 
of these measures would enable decision-makers to better prioritize 
communities for programs that increase access to preventive dental 
services.
    CDC is examining the feasibility and validity of using digital 
photos taken by non-dental professionals, which in turn would be 
analyzed by deep learning algorithms to assess youth's oral health 
status in lieu of human examination. This deep learning assessment tool 
ultimately could be used by public health officials for dental public 
health surveillance at the local, State, and national level. It is 
anticipated that obtaining information on dental conditions via deep 
learning assessment of digital images as opposed to human assessment 
will: (1) be more cost effective as it would not require dental 
personnel; and (2) improve the accuracy of assessment due to minimal 
bias and less confounding factors associated with the examiner (e.g., 
subjective index and thresholding). This tool also would offer 
mobility, simplicity, and affordability for rapid and scalable 
adaptation in community-based settings.
    In order to train and test the deep learning algorithms to identify 
caries, sealants, and fluorosis, data on these conditions as assessed 
by standardized examiners and corresponding photos are required. The 
CDC requests a one-year OMB approval for the one-time

[[Page 63957]]

collection of oral health data from 1,000 middle- and high-school 
students in Colorado communities with naturally occurring fluoride in 
the tap water at or exceeding one part per million. CDC is funding the 
Colorado State Health Department to implement the collection by 
recruiting eligible schools and dental examiners, gaining consent, 
arranging logistics, and collecting de-identified examination data and 
photos taken by the dental examiners. CDC is funding a national expert 
in dental public health data collection to train the examiners. 
Finally, CDC is funding researchers at Purdue University to develop 
photo-taking protocols and deep learning algorithms to identify dental 
conditions. Data collected for each student will include: (1) human 
assessment of fluorosis severity in the six upper anterior teeth, and 
caries/sealant assessment of the occlusal surfaces of the eight 
permanent molars; and (2) nine smartphone digital photos of the upper 
anterior teeth and 24 intraoral camera digital photos of the occlusal 
surfaces of the eight permanent molars. Digital photos of the teeth and 
the completed paper screening form will be uploaded to a HIPAA 
compliant cloud storage box that can only be accessed by examiners and 
designated CDC researchers with administrative rights. CDC is 
authorized to collect this information under the Public Health Service 
Act, title 42, section 247b-14, Oral health promotion and disease 
prevention; and the Public Health Service Act, title 42, section 301.
    CDC proposes using data collected from 750 students to train the 
deep learning algorithms to assess caries, sealants, and fluorosis and 
data from 250 students to evaluate the accuracy of the algorithms in 
terms of agreement with standardized examiner assessment. Manuscripts 
on: (1) the methodologies used to ensure sufficient photo quality when 
taken under field conditions; and (2) the performance of the deep 
learning algorithms will be submitted to peer-reviewed journals. The 
deep learning tool, if sufficiently accurate, will be piloted in one 
data collection cycle of NHANES that is administered by the National 
Centers for Health Statistics (NCHS). Ultimately, the tool would be 
shared with the State and local oral health programs and other 
pertinent partners.
    CDC requests OMB clearance for data collection for one year. The 
total estimated annualized burden hours are 827. There are no costs to 
student respondents other than their time.

                                        Estimated Annualized Burden Hours
----------------------------------------------------------------------------------------------------------------
                                                                                                      Average
                                                                     Number of       Number of      burden per
          Type of respondent                    Form name           respondents    responses per   response  (in
                                                                                    respondent          hr)
----------------------------------------------------------------------------------------------------------------
Child.................................  Screening/photo/form....           1,000               1           16/60
Parent or caretaker...................  Consent.................           1,000               1            1/60
Screener..............................  Screening/photo form                   6               1           90/60
                                         includes training,
                                         travel, screening and
                                         photos, and ongoing
                                         technical assistance.
----------------------------------------------------------------------------------------------------------------


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. 2023-20066 Filed 9-15-23; 8:45 am]
BILLING CODE 4163-18-P