12946 Federal Register / Vol. 86, No. 42 / Friday, March 5, 2021 / Notices 

EXHIBIT 2—ESTIMATED ANNUALIZED COST BURDEN

Form name Number of 

respondents 

Total burden 

hours 

Average 

hourly wage 

rate * 

Total cost 

burden 

Qualitative semi-structured interviews with AIM Team Leads ........................ 8 8 $49.83 $398.64 

Qualitative semi-structured interviews with frontline staff ............................... 32 16 49.83 797.28 

Focus group discussions with AIM Team Leads and frontline staff ............... 40 40 49.83 1,993.20 

Total .......................................................................................................... 80 64 ........................ $3,189.12 

* National Compensation Survey: Occupational wages in the United States May 2017 ‘‘U.S. Department of Labor, Bureau of Labor Statistics.’’ 

Weighted mean hourly wage for obstetrician-gynecologists ($113.10; occupation code 29–1064; 30%); nurse-midwives ($49.83; occupation code 

29–1161; 30%); registered nurses ($35.36; occupation code 29–1161; 20%); and nurse practitioners ($51.86; occupation code 29–1171; 20%). 

Request for Comments 

In accordance with the Paperwork 

Reduction Act, 44 U.S.C. 3501–3520, 

comments on AHRQ’s information 

collection are requested with regard to 

any of the following: (a) Whether the 

proposed collection of information is 

necessary for the proper performance of 

AHRQ’s health care research and health 

care information dissemination 

functions, including whether the 

information will have practical utility; 

(b) the accuracy of AHRQ’s estimate of 

burden (including hours and costs) of 

the proposed collection(s) of 

information; (c) ways to enhance the 

quality, utility and clarity of the 

information to be collected; and (d) 

ways to minimize the burden of the 

collection of information upon the 

respondents, including the use of 

automated collection techniques or 

other forms of information technology. 

Comments submitted in response to 

this notice will be summarized and 

included in the Agency’s subsequent 

request for OMB approval of the 

proposed information collection. All 

comments will become a matter of 

public record. 

Dated: March 1, 2021. 

Marquita Cullom, 

Associate Director. 

[FR Doc. 2021–04502 Filed 3–4–21; 8:45 am] 

BILLING CODE 4160–90–P 

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES 

Agency for Healthcare Research and 

Quality 

Supplemental Evidence and Data 

Request on Management of Infantile 

Epilepsy 

AGENCY: Agency for Healthcare Research 

and Quality (AHRQ), HHS. 

ACTION: Request for Supplemental 

Evidence and Data Submissions. 

SUMMARY: The Agency for Healthcare 

Research and Quality (AHRQ) is seeking 

scientific information submissions from 

the public. Scientific information is 

being solicited to inform our review on 

Management of Infantile Epilepsy, 

which is currently being conducted by 

the AHRQ’s Evidence-based Practice 

Centers (EPC) Program. Access to 

published and unpublished pertinent 

scientific information will improve the 

quality of this review. 

DATES: Submission Deadline on or 

before April 5, 2021. 

ADDRESSES: 

Email submissions: epc@

ahrq.hhs.gov. 

Print submissions: 

Mailing Address: Center for Evidence 

and Practice Improvement, Agency for 

Healthcare Research and Quality, 

ATTN: EPC SEADs Coordinator, 5600 

Fishers Lane, Mail Stop 06E53A, 

Rockville, MD 20857. 

Shipping Address (FedEx, UPS, etc.): 

Center for Evidence and Practice 

Improvement, Agency for Healthcare 

Research and Quality, ATTN: EPC 

SEADs Coordinator, 5600 Fishers Lane, 

Mail Stop 06E77D, Rockville, MD 

20857. 

FOR FURTHER INFORMATION CONTACT: 

Jenae Benns, Telephone: 301–427–1496 

or Email: epc@ahrq.hhs.gov. 

SUPPLEMENTARY INFORMATION: The 

Agency for Healthcare Research and 

Quality has commissioned the 

Evidence-based Practice Centers (EPC) 

Program to complete a review of the 

evidence for Management of Infantile 

Epilepsy. AHRQ is conducting this 

systematic review pursuant to Section 

902 of the Public Health Service Act, 42 

U.S.C. 299a. 

The EPC Program is dedicated to 

identifying as many studies as possible 

that are relevant to the questions for 

each of its reviews. In order to do so, we 

are supplementing the usual manual 

and electronic database searches of the 

literature by requesting information 

from the public (e.g., details of studies 

conducted). We are looking for studies 

that report on Management of Infantile 

Epilepsy, including those that describe 

adverse events. The entire research 

protocol is available online at: https://

effectivehealthcare.ahrq.gov/products/ 

management-infantile-epilepsy/ 

research-protocol. 

This is to notify the public that the 

EPC Program would find the following 

information on Management of Infantile 

Epilepsy helpful: 

D A list of completed studies that 

your organization has sponsored for this 

indication. In the list, please indicate 

whether results are available on 

ClinicalTrials.gov along with the 

ClinicalTrials.gov trial number. 

D For completed studies that do not 

have results on ClinicalTrials.gov, a 

summary, including the following 

elements: Study number, study period, 

design, methodology, indication and 

diagnosis, proper use instructions, 

inclusion and exclusion criteria, 

primary and secondary outcomes, 

baseline characteristics, number of 

patients screened/eligible/enrolled/lost 

to follow-up/withdrawn/analyzed, 

effectiveness/efficacy, and safety results. 

D A list of ongoing studies that your 

organization has sponsored for this 

indication. In the list, please provide the 

ClinicalTrials.gov trial number or, if the 

trial is not registered, the protocol for 

the study including a study number, the 

study period, design, methodology, 

indication and diagnosis, proper use 

instructions, inclusion and exclusion 

criteria, and primary and secondary 

outcomes. 

D Description of whether the above 

studies constitute ALL Phase II and 

above clinical trials sponsored by your 

organization for this indication and an 

index outlining the relevant information 

in each submitted file. 

Your contribution is very beneficial to 

the Program. Materials submitted must 

be publicly available or able to be made 

public. Materials that are considered 

confidential; marketing materials; study 

types not included in the review; or 

information on indications not included 

in the review cannot be used by the EPC 

Program. This is a voluntary request for 

information, and all costs for complying 


jbell on DSKJLSW7X2PROD with NOTICES
Federal Register / Vol. 86, No. 42 / Friday, March 5, 2021 / Notices 12947 

with this request must be borne by the 

submitter. 

The draft of this review will be posted 

on AHRQ’s EPC Program website and 

available for public comment for a 

period of 4 weeks. If you would like to 

be notified when the draft is posted, 

please sign up for the email list at: 

https://

www.effectivehealthcare.ahrq.gov/ 

email-updates. 

The systematic review will answer the 

following questions. This information is 

provided as background. AHRQ is not 

requesting that the public provide 

answers to these questions. 

Key and Contextual Questions 

Key Question 1. What is the 

effectiveness and comparative 

effectiveness of pharmacologic 

treatments for infantile epilepsy (infants 

age 1 month to <3 years)? 

Key Question 2. What is the 

effectiveness and comparative 

effectiveness of non-pharmacologic 

treatments for infantile epilepsy (e.g., 

dietary therapies, surgery, and brain 

stimulation therapies), including 

comparisons to other nonpharmacologic and/or pharmacologic 

therapies? 

Key Question 3. What are the harms 

or comparative harms of treatments for 

infantile epilepsy? 

Contextual Question 1. What are the 

parental preferences for treatment 

options for infantile epilepsy? 

Contextual Question 2. What are the 

harms or comparative harms of not 

treating infantile epilepsy? 

PICOTS 

[Population, intervention, comparator, outcome, timing, setting] 

Inclusion Exclusion 

Population ............................ • Infants (1 month to <3 years) diagnosed with epilepsy ...........................................

• Subpopulations based on baseline seizure severity/frequency, history of previous 

treatment, length of gestation.

• West syndrome/infantile 

spasms. 

• Non-epileptic seizures. 

• Provoked seizures, including febrile seizures. 

• Metabolic epilepsies. 

• Status epilepticus. 

• Acute symptomatic seizures. 

Intervention .......................... • KQ 1, 3: Pharmacologic interventions ......................................................................

• KQ 2, 3: Non-pharmacologic intervention: dietary therapies, surgery, brain stimulation, and gene therapy.

• Diagnostic research. 

• Provider/organization 

level interventions such 

as awareness campaigns. 

• Metabolic therapies. 

• Vitamin therapies. 

• Social and community 

services. 

Comparator .......................... • KQ1: Other pharmacologic interventions or usual care.

• KQ2: Other pharmacologic or non-pharmacologic interventions or usual care.

• KQ3: Inclusive of comparators for KQ1&2.

Outcomes ............................. • All-cause mortality.

• SUDEP.

• Hospitalization.

• Seizure freedom.

• Seizure frequency.

• Seizure severity (including seizure duration, seizure burden, and status 

epilepticus).

• Engel classification.

• Progression to other seizure types or syndromes (e.g., infantile spasms, LennoxGastaut Syndrome).

• Time to seizure remission.

• Neurodevelopment.

• Quality of life (including eating).

• Sleep outcomes (e.g., total time spent asleep at night).

• Behavioral function.

• Cognitive function.

• Functional performance (including school).

• Social function.

• Caregiver anxiety.

• Caregiver quality of life.

• General health status.

• Cost of treatment.

• Adverse events (infection, new neurological deficits, surgical complications, irritability, somnolence, dizziness, drug toxicity, etc.).

Timing .................................. Effectiveness: 12 week minimum follow-up. 

Harms: No minimum follow-up. 

Setting .................................. Setting not limited.


jbell on DSKJLSW7X2PROD with NOTICES
12948 Federal Register / Vol. 86, No. 42 / Friday, March 5, 2021 / Notices 

Dated: March 1, 2021. 

Marquita Cullom, 

Associate Director. 

[FR Doc. 2021–04538 Filed 3–4–21; 8:45 am] 

BILLING CODE 4160–90–P 

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES 

Agency for Healthcare Research and 

Quality 

Request for Information on the Use of 

Clinical Algorithms That Have the 

Potential To Introduce Racial/Ethnic 

Bias Into Healthcare Delivery 

AGENCY: Agency for Healthcare Research 

and Quality (AHRQ), HHS. 

ACTION: Notice of Request for 

Information. 

SUMMARY: The Agency for Healthcare 

Research and Quality (AHRQ) is seeking 

information from the public on clinical 

algorithms that are used or 

recommended in medical practice and 

any evidence on clinical algorithms that 

may introduce bias into clinical 

decision- making and/or influence 

access to care, quality of care, or health 

outcomes for racial and ethnic 

minorities and those who are 

socioeconomically disadvantaged. 

DATES: Comments must be submitted on 

or before May 4, 2021. The EPC Program 

will not respond individually to 

responders but will consider all 

comments submitted by the deadline. 

ADDRESSES: Submissions should follow 

the Submission Instructions below. We 

prefer that comments be submitted 

electronically on the submission 

website. Email submissions may also be 

sent to: epc@ahrq.gov 

FOR FURTHER INFORMATION CONTACT: 

Anjali Jain, Email: Anjali.Jain@

ahrq.hhs.gov. 

SUPPLEMENTARY INFORMATION: The 

Agency for Healthcare Research and 

Quality (AHRQ) is seeking information 

from the public on clinical algorithms 

that are used or recommended in 

medical practice and any evidence on 

clinical algorithms that may introduce 

bias into clinical decision-making and/ 

or influence access to care, quality of 

care, or health outcomes for racial and 

ethnic minorities and those who are 

socioeconomically disadvantaged. 

Information received in response to 

this request will be used to inform an 

AHRQ Evidence-Based Practice Center 

Program (EPC) evidence review and may 

inform other activities commissioned by 

or in collaboration with AHRQ. 

Established in 1997, the mission of the 

EPC Program (https://

effectivehealthcare.ahrq.gov/about/epc) 

is to create evidence reviews that 

improve healthcare by supporting 

evidence-based decision-making by 

patients, providers, and policymakers. 

Evidence reviews summarize and 

synthesize existing literature and 

evidence using rigorous methods. 

AHRQ is conducting this review 

pursuant to sections 902 and 901(c) of 

the Public Health Service Act, 42 U.S.C. 

299a and 42 U.S.C. 299(c). 

AHRQ intends to commission an 

evidence review that will critically 

appraise the evidence on commonly 

used algorithms, including whether 

race/ethnicity is included as an explicit 

variable, and how algorithms have been 

developed and validated. The review 

would examine how race/ethnicity and 

related variables included in clinical 

algorithms impact healthcare use, 

patient outcomes and healthcare 

disparities. In addition, the review will 

identify and assess other variables with 

the potential to introduce bias such as 

prior utilization. The review will 

identify and review approaches to 

clinical algorithm development that 

avoid the introduction of racial and 

ethnic bias into clinical decision making 

and resulting outcomes. 

For the purposes of this evidence 

review, clinical algorithms are defined 

as a set of steps that clinicians use to 

guide decision-making in preventive 

services (such as screening), in 

diagnosis, clinical management, or 

otherwise assessing or improving a 

patient’s health. Algorithms are 

informed by data and research evidence 

and may include patient-specific factors 

or characteristics which may be 

sociodemographic factors such as race/ 

ethnicity, physiologic factors such as, 

for example, blood sugar level, or others 

such as patterns of healthcare 

utilization. 

When used appropriately, algorithms 

can improve disease management and 

patient health by creating efficiencies in 

place of individuals having to weigh 

multiple and complex factors when 

making a clinical judgement. As a 

result, the use of clinical algorithms has 

become widespread in healthcare and 

includes a heterogeneous set of tools 

including clinical pathways/guidelines, 

the establishment of norms and 

standards that may vary according to 

patient-specific factors, clinical decision 

support embedded in electronic health 

records (EHRs) or within medical 

devices, pattern recognition software 

used for diagnosis, and apps and 

calculators that predict patient risk and 

prognosis. Some clinical algorithms 

include information about a patient’s 

race or ethnicity among its inputs and 

thus lead clinicians to decision-making 

that varies by race/ethnicity, including 

decisions about how best to diagnose 

and manage individual patients. 

The purpose of this evidence review 

is to understand which algorithms are 

currently used in different clinical 

settings; the type and extent of their 

validation; their potential for bias with 

impact on access, quality, and outcomes 

of care; awareness among clinicians of 

these issues; and strategies for 

developing and testing clinical 

algorithms to assure that they are free of 

bias in order to inform the scope of a 

future evidence review. We are 

interested in understanding which 

algorithms are currently in use in 

clinical practice including those related 

to the use of clinical preventive 

services. How many include race/ 

ethnicity and other factors that could 

lead to bias within the algorithm? We 

are interested in all algorithms 

including clinical pathways/guidelines, 

norms and standards (including 

laboratory values) that vary according to 

patient-specific factors such as race/ 

ethnicity and related variables, clinical 

decision support embedded in EHRs, 

pattern recognition software, and apps 

and calculators for patient risk and 

prognosis. We are interested both in 

algorithms developed through 

traditional methods and through new 

and ongoing methods including 

machine learning and artificial 

intelligence. AHRQ seeks information 

• From healthcare providers who use 

clinical algorithms to screen, diagnose, 

triage, treat or otherwise care for 

patients 

• From laboratorians or technicians 

who use algorithms to interpret lab or 

radiology data 

• From researchers and clinical 

decision support developers who 

develop algorithms used in healthcare 

for patients 

• From clinical professional societies 

or other groups who develop clinical 

algorithms for healthcare 

• From payers who use clinical 

algorithms to guide payment decisions 

for care for patients 

• From healthcare delivery 

organizations who use clinical 

algorithms to determine healthcare 

practices and policies for patients 

• From device developers who 

incorporate algorithms into device 

software to interpret data and set 

standards 

• From patients whose healthcare and 

healthcare decisions may be informed 

by clinical algorithms 


jbell on DSKJLSW7X2PROD with NOTICES