[Federal Register Volume 85, Number 222 (Tuesday, November 17, 2020)]
[Notices]
[Pages 73280-73282]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2020-25328]


-----------------------------------------------------------------------

DEPARTMENT OF HEALTH AND HUMAN SERVICES


Request for Information--Landscape Analysis To Leverage Novel 
Technologies for Chronic Disease Management for Aging Underserved 
Populations

AGENCY: Office of the Assistant Secretary for Health, Office of the 
Secretary, Department of Health and Human Services.

ACTION: Request for information.

-----------------------------------------------------------------------

SUMMARY: The Office of the Assistant Secretary for Health (OASH) in the 
Department of Health and Human Services, in partnership with other 
federal agencies, seeks to gain a more comprehensive understanding from 
health systems, community based organizations, academic institutions, 
non-federal government agencies, innovators, entrepreneurs, non-profit 
organizations, and other relevant stakeholders regarding innovative 
solutions to chronic disease management leveraging novel technologies 
(e.g., artificial intelligence (AI), biosensors, apps, remote 
monitoring, 5G) to optimize compliance with evidence-based standards of 
care in disease states that cause significant morbidity and mortality 
in aging populations in underserved areas (e.g., low income, Medicaid-
eligible, rural). OASH will review information collected in this 
request for information (RFI) to better inform federal government 
priorities and programs. We also seek to identify opportunities to 
strengthen the U.S. healthcare system, as a whole, through public-
private partnerships in data sharing, comprehensive analytics including 
AI, and other potential mechanisms. OASH welcomes public feedback 
related to how these questions should be addressed and/or potential 
solutions. The set of questions is available in the SUPPLEMENTARY 
INFORMATION section below.

DATES: To be assured consideration, comments must be received at the 
email address provided below, no later than midnight Eastern Time (ET) 
on December 22, 2020.

ADDRESSES: Individuals are encouraged to submit responses 
electronically to [email protected]. Please indicate ``RFI 
RESPONSE'' in the subject line of your email. Submissions received 
after the deadline will not be reviewed. Responses to this notice are 
not offers and cannot be accepted by the federal government to form a 
binding contract or issue a grant. Respond concisely and in plain 
language. You may use any structure or layout that

[[Page 73281]]

presents your information well. You may respond to some or all of our 
questions, and you can suggest other factors or relevant questions. You 
may also include links to online material or interactive presentations. 
Clearly mark any proprietary information, and place it in its own 
section or file. Your response will become government property, and we 
may publish some of its non-proprietary content.

FOR FURTHER INFORMATION CONTACT: Dr. Leith States, Chief Medical 
Officer, Office of the Assistant Secretary for Health, (202) 260-2873.

SUPPLEMENTARY INFORMATION: 

Background

    The Office of the Assistant Secretary for Health--in partnership 
with Division of Cardiovascular Sciences, National Heart, Lung, and 
Blood Institute, National Institutes of Health; Administration for 
Community Living; Agency for Healthcare Quality and Research; United 
States Department of Agriculture; Federal Communications Commission; 
and the White House Office of Science and Technology Policy --is 
interested in resources that enhance quality of life for aging 
populations by enabling access to emerging technologies and access to 
healthcare services. The COVID-19 response has disrupted access to 
routine and emergency healthcare services in many, if not most, 
communities. It is estimated that 41 percent of U.S. adults delayed or 
avoided medical care due to concerns over COVID-19 transmission.\1\ At 
the same time, the pandemic resulted in a strain on the country's 
public health and healthcare infrastructure. The populations affected 
most by this pandemic are those that experienced inequities in 
healthcare at baseline. These inequities are widely understood to be 
driven in part by upstream predictors identified as the social 
determinants of health (SDOH)--conditions in the environment in which 
people are born, live, learn, work, play, worship, and age that affect 
a wide range of health, functioning, and quality-of-life outcomes and 
risks.\2\
---------------------------------------------------------------------------

    \1\ Available at: https://www.cdc.gov/mmwr/volumes/69/wr/mm6936a4.htm#T1_down.
    \2\ Available at: https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health.
---------------------------------------------------------------------------

    Related to these social risk factors, the biological risk factors 
most closely associated with increased risk for COVID-19 include age 
(65 years and older) and chronic diseases (e.g., cancer, chronic kidney 
disease, Alzheimer's disease and related dementias, chronic obstructive 
pulmonary disease, heart disease and stroke, diabetes, and obesity). 
Underscoring the vulnerability of older adults, the highest rates of 
hospitalization and death from COVID-19 are in the older adult 
population. In fact, eight in ten COVID-19-related deaths reported in 
the United States have been among adults 65 and older.\3\ This 
situation is exacerbated in rural communities, for example which, 
compared to urban areas, are characterized by a higher percentage of 
older adults, higher rates of all-cause mortality, and lower density of 
healthcare infrastructure.4 5 The pandemic's further 
exacerbation of inequities in healthcare delivery introduces the 
opportunity to identify, develop, deploy and evaluate innovative 
technological approaches to chronic disease management, as well as the 
opportunity to mitigate any introduction of biases that could increase 
disparities in healthcare when applying such innovative approaches. 
Technological advances (e.g., artificial intelligence (AI) driven 
solutions) have great potential to improve health outcomes in the aging 
population, particularly for those in underserved areas (e.g., low 
income, Medicaid-eligible, rural) by empowering patients and 
facilitating integrated healthcare delivery.
---------------------------------------------------------------------------

    \3\ Available at: https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/older-adults.html.
    \4\ Available at: https://www.shepscenter.unc.edu/wp-content/uploads/dlm_uploads/2017/05/Snapshot2017.pdf.
    \5\ Available at: https://www.shepscenter.unc.edu/wp-content/uploads/dlm_uploads/2017/08/Regional-Differences-in-Urban-and-Rural-Mortality-Trends.pdf.
---------------------------------------------------------------------------

    Leveraging data and applying technologies to improve health for 
aging populations in underserved areas is of interest. These include, 
for example, advancing data availability from health systems (e.g., 
claims data, electronic health records, surveillance data, etc.), 
applying AI to inform behavior change through remote patient 
monitoring, and assessing risk to then apply appropriate preventive/
acute care--all to mitigate excess morbidity and mortality from chronic 
diseases. The federal government has taken some action to demonstrate 
this interest. For example, the Collaborative Aging (in Place) Research 
Using Technology (CART) project, a joint effort between the Veterans 
Health Administration and the National Institutes of Health, was 
launched to support future applications of AI and machine learning to 
improve health and healthcare delivery through systematic evaluation of 
technologies that enable older adults to remain independent. These 
efforts align with the National Artificial Intelligence Research and 
Development Strategic Plan, an interagency product released in 2019, 
which lays out eight strategic priority areas for federal investment in 
AI research and development. The utility of these technologies requires 
access to patient monitoring technologies and the data infrastructure 
to support analytics and transmission to integrated care teams (e.g., 
primary care, subspecialty care, nursing, pharmacy, social work, 
assisted living providers) that can effectively leverage signals that 
emerge within this system. To better inform the direction of federal 
efforts, OASH and its partners seek information about complementary 
technological activities by identifying common themes (e.g., barriers, 
opportunities, gaps), highlighting innovative solutions to chronic 
disease management, and enhancing the potential for joint public-
private activities to serve aging populations in underserved areas 
focusing on the imperative to understand and capitalize on 
opportunities to develop, operationalize, and scale innovations in 
healthcare and delivery at the individual and population levels for 
aging Americans.

Scope and Assumptions

     The purpose of this RFI is to gain a more comprehensive 
understanding of how health systems, community based organizations, 
academic institutions, non-federal government agencies, innovators, 
entrepreneurs, non-profit organizations, industry and other relevant 
stakeholders are approaching innovative efforts around chronic disease 
management (e.g., heart failure, hypertension, chronic lower 
respiratory disorders, cognitive impairment) for aging populations in 
underserved areas (e.g., rural) by leveraging technology-driven 
solutions (e.g., AI), including those designed to optimally utilize 
future 5G infrastructure.
     Responses may span the continuum of care including but not 
limited to detection, prevention (e.g., falls risk reduction), 
education, lifestyle modification and behavior change (e.g., diet, 
exercise), treatment and rehabilitation of disease.
     We are interested in novel approaches and associated 
frameworks for collecting data confirming efficacy and/or effectiveness 
of technology solutions with demonstrated improvements in one or more 
of the following measures: Patient outcomes, access, safety, quality, 
cost, and value.
     If responses refer to proposed or ongoing projects, the 
following information should be included:

[[Page 73282]]

Description, rationale, study design, data sources (to include 
harmonization/cleaning of data), funding organization(s), outcomes of 
interest, and how such an approach would avoid increasing disparities 
in care.
     Responses may include implications for scaling an 
intervention to broader population levels and other settings.
     The definition of ``AI-driven solution'', for the purposes 
of this RFI, should be interpreted broadly. We seek an understanding of 
innovative activities across the spectrum of care in underserved 
settings for older adults.
     This RFI also seeks to identify opportunities to 
strengthen the U.S. healthcare system through public-private 
partnerships. The RFI seeks to identify organizations that would be 
interested in discussing the form and function of such collaborations.

Topics

A. Barriers and Opportunities for Technology-Driven Solutions

    1. What barriers (e.g., privacy concerns, other clinician and 
patient barriers) and opportunities are most relevant for bringing 
technology-driven solutions to aging populations in underserved areas?
    2. What federal policies currently limit the capacity to deploy and 
scale technology-driven solutions for aging populations?
    3. What new federal policies could facilitate the success of 
technology-driven solutions for aging populations?
    4. What are the ways in which technology-driven solutions are 
manifested (e.g., software platforms, wearables, robotics, etc.) and 
how is the integrity of data collected ensured (e.g., fidelity, and 
accuracy of data)?
    5. How will training data sets be established and implemented to 
drive effective technology solutions that improve chronic disease 
outcomes for aging populations in rural areas?
    6. How will AI solutions be validated? What metrics will be used to 
evaluate the effectiveness of AI/machine learning algorithms?
    7. How will healthcare team and patient trust in technology 
solutions be addressed? How will legal and ethical issues be addressed 
for technology solutions designed for improving chronic disease 
outcomes?
    8. How will bias and variance be addressed in machine learning 
algorithms for this application? How will supervised versus 
unsupervised learning be used to develop inferences and patterns from 
data sources? What will be the challenges and proposed solutions for 
data cleansing and transformation?
    9. Will AI deep learning and neural networks approaches and 
solutions be appropriate and used for chronic disease improvement for 
aging populations?
    10. What are the per-person-costs of technology-driven solutions in 
the context of this RFI?

B. Key Indicators & Data Sources of Technology-Driven Chronic Disease 
Management

    1. What key indicators or data sets will be used to perform measure 
outcomes (e.g., racial, ethnic, gender, and socioeconomic disparities)?
    2. What existing methods, data sources, and analytic approaches are 
being used to assess and monitor technology-driven solutions (e.g., AI) 
in healthcare systems?
    3. What selected health conditions should be addressed as priority 
conditions to assess technology-driven capacity to influence access, 
timeliness, and quality of healthcare treatment and preventive services 
to aging populations living in rural areas?

C. Examples of Health Promotion Using Technology-Driven Solutions

    1. Describe novel technology-driven approaches (e.g., AI) that may 
prevent the onset, progression, or escalation of chronic disease states 
in patients who have decreased frequency of health system interaction 
during the COVID-19 pandemic, such as aging Americans living in rural 
areas.
    2. Outline programs leveraging novel technology-driven approaches 
that may prevent increases in morbidity and mortality due to deferred 
care for acute medical conditions (e.g., exacerbation of heart failure, 
decompensated lower respiratory tract disease).
    3. What is the established evidence or evaluation supporting 
proposed benefits, and the evaluation of potential harms of AI-driven 
solutions such as increased racial bias?

D. Public-Private Partnerships

    1. Provide ideas of the form and function of a public-private 
partnership model to leverage the adoption of technology-driven 
solutions to improve outcomes for at-risk populations such as aging 
Americans living in rural areas.
    2. What organizations, groups, and/or, associations should HHS 
engage as part of such a collaborative effort?
    HHS encourages all potentially interested parties--individuals, 
associations, governmental, non-governmental organizations, academic 
institutions, and private sector entities--to respond. To facilitate 
review of the responses, please reference the question category and 
number in your response.

    Dated: November 10, 2020.
Brett P. Giroir,
ADM, U.S. Public Health Service.
[FR Doc. 2020-25328 Filed 11-16-20; 8:45 am]
BILLING CODE 4150-28-P