AIM-AHEAD Hub Specific Projects

Call for Proposals

Key Dates

Solicitation Release Date: May 1, 2024

Application Due Date: June 16, 2024

Programmatic Review Date: July 26, 2024

Earliest Start Date: September 16, 2024

Informational Webinar

View the informational webinar recording and presentation that address the program as a whole and the application process.

 

Click here to view the webinar recording.

Click here to view the webinar presentation.



Issued by

Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program

 

Overview and Purpose

 

The overall goal of the AIM-AHEAD Hub-Specific Projects is to advance the conduct of community-based participatory research (CBPR) using AI/ML to address and reduce health disparities. This funding opportunity will support small-scale research projects co-led by community-based organizational leaders and researchers from academic institutions. Collaborative teams are encouraged to submit applications using novel approaches to address diseases and conditions that disproportionately affect populations that experience health disparities. Approaches that utilize the interests, concerns, and values of communities have led to improvements in population-level outcomes.

 

The seven AIM-AHEAD regional hubs solicit hub-specific project applications that: 1) support research teams that equitably include community stakeholders to address critical health challenges using AI/ML methods; 2) facilitate direct interaction between key stakeholder teams, AIM-AHEAD hubs, and AIM-AHEAD technical cores; 3) utilize CBPR approaches to advance AI/ML-related capacity building opportunities for vulnerable communities; and 4) enhance community stakeholder understanding of and familiarity with AI/ML analytic methods. Funding for these small-scale projects is expected to establish and facilitate sustainable efforts that will enhance community leadership in AI/ML research, accelerate the dissemination of study findings back to communities, and generate preliminary data to enhance the competitiveness of future larger-scale community-engaged NIH grant applications for AI/ML research applications.

 

Background

The overall AIM-AHEAD Consortium seeks to support multidisciplinary research projects that use artificial intelligence/machine learning (AI/ML) to develop novel algorithms and approaches to address health disparities and inequities in populations that experience health disparities. Research of particular interest use new or real-world synthetic data or existing datasets that include but are not limited to electronic health records (EHR), images, and social determinants of health (SODH) variables to develop and enhance AI/ML algorithms and applications that have the potential to reduce health disparities while improving healthcare and outcomes.

 

Hub-Specific Projects are designed for new stakeholders in AIM-AHEAD regional hubs to conduct small-scale, community-engaged research studies.

 

The overarching goal of AIM-AHEAD is to build trusted partnerships to increase and enhance the engagement of researchers and communities underrepresented in the development of AI/ML models, and to expand the capabilities of this emerging technology to address health disparities and advance health equity. Underrepresented and underserved communities are often disproportionately burdened by infectious and chronic diseases and related complications. Engaging community stakeholders is essential to include their expertise, sources of data, and own lived perspectives which can result in innovative research questions, the interpretation of findings, and novel analytic strategies. The benefits of engaging underrepresented individuals, institutions, and communities can be significant; however, historical inequities have often limited the infrastructural and data science training capacity of these groups and organizations to engage in research applying AI/ML approaches to study topics relevant to these communities.

 

The AIM-AHEAD Coordinating Center (A-CC) is comprised of four cores: 1) Leadership/Administrative Core; 2) Data Science Training Core; 3) Data and Research Core; and 4) the Infrastructure Core. Each core provides distinct resources that are essential to expand and support education, training, and implementation of AI/ML models and research that addresses health disparities and advances health equity. Brief descriptions of the cores are provided below.

 

Leadership/Administrative Core: Leads the overall A-CC, recruits and coordinates consortium members, project management, partnerships, stakeholder engagement, and outreach to enhance the diversity of researchers in AI/ML related research, with an emphasis on health disparities research, and establishes and maintains trusted relationships with groups experiencing health disparities to enhance the diversity of data used in AI/ML research. The Leadership/Administrative Core is comprised of seven regional hubs (i.e., Central, Northeast, North and Midwest, South Central, Southeast (2), and West) that are designed to engage partners and stakeholders across the United States (U.S.). This core operates as a Pass-Through Entity (PTE) for AIM-AHEAD.

 

Data Science Training Core: Develops, implements, and assesses data science training curricula to enhance capacity among diverse populations, including underrepresented or underserved groups impacted by health disparities.

 

Data and Research Core: Determines and addresses research priorities and needs in linking and preparing multiple sources and types of research data to form an inclusive basis for AI/ML use cases that will illuminate strategies and approaches to ameliorate health disparities. This may include facilitating the extraction and transformation of data from EHR for research use and consideration of social determinants of health as crucial contributors to health outcomes.

 

Infrastructure Core: Conducts the assessment of data, computing, and software infrastructure models, tools, resources, data science policies, ethical AI, and AI/ML computing models that will facilitate AI/ML and health disparities research; and establishes pilot data and analytic environments to accelerate overall A-CC aims.

 

 

Eligibility

Eligible Organizations

 

Eligible organizations may include:

 

  • Higher Education Institutions
  • Public/State Controlled Institutions of Higher Education
  • Private Institutions of Higher Education

 

The following types of Higher Education Institutions are always encouraged to apply for NIH support as Public or Private Institutions of Higher Education:

  • Hispanic-serving Institutions
  • Historically Black College and Universities (HBCUs)
  • Tribally Controlled Colleges and Universities (TCCUs)
  • Alaska Native and Native Hawaiian Serving Institutions
  • Asian American Native American Pacific Islander Serving Institutions (AANAPISIs)
  • Community-based Organizations 
  • Nonprofits with 501(c)(3) IRS Status
  • Nonprofits without 501(c)(3) IRS Status
  • Tribal health and/or human service organizations or Tribally derived institutions (Urban Indian Health Organizations, Tribal Epidemiology Centers)
  • For-Profit Organizations
  • Small businesses
  • For-project organizations (other than small businesses)

 

The primary applicant organization must be a domestic institution located in the United States and its territories. Higher education institutions must meet the following criteria:

  • Has received an average of less than $50 million total costs per year of NIH support, and less than $25 million per year of R01 total costs of NIH support for the past three fiscal years; and
  • Has a documented historical and current mission to educate students from any of the populations that have been identified as underrepresented in biomedical, behavioral and social science research as defined by the National Science Foundation (see http://www.nsf.gov/statistics/wmpd/), including African Americans or Blacks, Hispanic or Latino Americans, American Indians, Alaska Natives, Native Hawaiians, U.S. Pacific Islanders, and persons with disabilities, or has a documented record of:
    • Recruiting, training and/or educating, and graduating underrepresented students as defined by NSF (see above), which has resulted in increasing the institution's contribution to the national pool of graduates from underrepresented backgrounds who pursue biomedical research careers
    • Working with community stakeholders (e.g.,Community-based organizations, Nonprofits (with or without 501(c)(3) IRS status, Faith-based organizations, Healthcare Providers, Health Systems, Small businesses, Large businesses, start-ups.) that have historically not participated in biomedical, behavioral, and social sciences research in the areas of AIM/ML
  • Community organizations, nonprofits and non-academic institutions are strongly encouraged to apply and need not demonstrate a mission to educate students but should have a documented interest in working with health disparity populations.

 

Required Registrations for Applicant organizations

Applicant organizations must complete and maintain the following registrations as described in the SF 424 (R&R) Application Guide to be eligible to apply for or receive an award. Registrations are required to received federal grant awards. Registration can take 6 weeks or more, so applicants should begin the registration process as soon as possible.

 

System for Award Management (SAM) Applicants must complete and maintain an active registration, which requires renewal at least annually. The renewal process may require as much time as the initial registration. SAM registration includes the assignment of a Commercial and Government Entity (CAGE). “Federally recognized tribes and their derivatives are exempt from this requirement.”

  • Unique Entity Identifier (UEI) - A UEI is issued as part of the SAM.gov registration process. The same UEI must be used for all registrations, as well as on the grant application.
  • eRA Commons- Once the unique organization identifier is established, organizations can register with eRA Commons in tandem with completing their Grants.gov registration; all registrations must be in place by time of submission. eRA Commons requires organizations to identify at least one Signing Official (SO) and at least one Program Director/Principal Investigator (PD/PI) account in order to submit an application.
  • Grants.gov Applicants must have an active SAM registration in order to complete the Grants.gov registration.

 

Foreign Institutions

Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply.

Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.

Foreign components, as defined in the NIH Grants Policy Statementare not allowed

 

Eligible Applicants

Individuals who are affiliated with an eligible institution (described above) can apply for Hub-Specific Project funding. Applicants who have previously received AIM-AHEAD funding are eligible, however, the research question(s) must be distinct from the previous award.  

 

Multiple applications from the same institution are permitted, as long as the studies are scientifically distinct.

 

Budget Estimates, Number of Awards, and Duration of the Program

Each Hub-Specific Project award cannot exceed $150,000 in total cost. Each hub can support a maximum of 2 awards. The research and/or capacity building supported by funded applications must be completed within one year from the start date (TBD).

 

Potential risks/challenges and mitigation measures

Hub-Specific Project investigators are expected to submit timely invoices and monthly reports, and complete monthly project management and evaluation documents. Potential mitigation strategies involve the development of standardized reporting tools, the use of easily accessible systems for information exchange, applicant organizations sufficiently staffed to facilitate compliance, and appreciation of the heterogeneity of organizational infrastructures. 

 

Expected Outcomes and Impact of the Program

Hub-Specific Projects are expected to expand the AIM-AHEAD consortium, lead to consortium development grant applications, and enhance the professional networks of AIM-AHEAD stakeholders, particularly those from groups and organizations underrepresented in AI/ML research. Findings from funded Hub-Specific Projects are expected to generate strong proof-of-concept data that can be disseminated in scholarly journals and other communication channels and serve as the empirical foundation for subsequent NIH grant applications.

 

 

Application Submission Guidelines, Process, Components, and Review Criteria

 

Submission Guidelines

The AIM-AHEAD Consortium utilizes the online portal InfoReady for the submission of proposal applications. Please use this link to access, complete, and upload the above completed application components no later than  June 16th at 11:59pm EDT: https://aim-ahead.infoready4.com/CompetitionSpace/#freeformCompetitionDetail/1937900. The application should be directed to the hub that represents the applicant’s geographic location. We recommend contacting the relevant Hub Principal Investigator before submitting your application. Late applications will be returned unreviewed.

 

Application Process:

  • Step 1: Click here to login or to register as a “mentor” on AIM-AHEAD Connect (our Community Building Platform)
  • Step 2: After you login to AIM-AHEAD Connect, click here to submit an application for review using the InfoReady platform*.

 

 * To submit your application in InfoReady, please use Chrome, Firefox, or Edge. If you're using Safari, make sure to clear your cache before logging in.

Please note both steps must be completed for consideration.

All applications must be received by June 16, 2024 — 11:59 PM Eastern Time.

Direct your application to the Hub listed below that represents your geographic location:

 

 

Hub Name

States Represented

Central Hub

American Samoa, Hawaii, Guam

North and Midwest Hub

Alaska, Colorado, Idaho, Iowa, Kansas, Minnesota, Montana, Nebraska, North Dakota, Oregon, South Dakota, Utah, Washington, Wisconsin

Northeast Hub

Delaware, Maine, Maryland, Massachusetts, Pennsylvania, New Jersey, New Hampshire, New Jersey, New York, Vermont, Washington DC

South-Central Hub

Louisiana, Mississippi, Oklahoma, Texas

Southeast Hub

Arkansas, Illinois, Indiana, Kentucky, Michigan, Missouri, North Carolina, Ohio, Tennessee, Virginia, West Virginia

Southeast Hub

Alabama, Georgia, Florida, Puerto Rico, South Carolina, Virgin Islands

West Hub

Arizona, California, Nevada, New Mexico, Northern Mariana Islands

 

 

Application Components

1. Applicant Information (Principal Investigator(s)/Program Director)(s)

a. Provide names, institution/organizations, department, position titles, research areas, and email addresses

b. Gender, race/ethnicity, socioeconomic background , veteran, disability status

 

2. Biosketch in NIH (https://grants.nih.gov/grants/forms/biosketch.htm) or other format, a curriculum vitae or a professional resume (Maximum 5 pages). Biosketches are required for key personnel from universities.

 

3. Proposal Summary (limit 300 words) Provide a succinct description of the proposed work including the project's long-term objectives, and a summary of the research design and methods for the project

 

4. The proposed research focus or scope must propose community-engaged research approaches. Proposed studies that do not actively demonstrate the inclusion of community partners in all aspects of the project will be considered non-responsive to this funding opportunity.

a. The Research Description should consist of the following sections:

i. Title: Provide Project Title

ii. Specific Aims (1 page)

            • Provide a clear, concise summary of the aims of the proposed work and its relationship to your long-term goals. State the hypothesis to be tested. Briefly state the anticipated outcomes and benefits that will accrue upon successful completion of the project.

iii. Significance (1 page)

            • Must address the premise for the research grant
            • State the importance of the problem, the critical issue to be addressed, and the significance and relevance for community-engaged research
            • Explain how the proposed project will advance scientific knowledge or technical capability
            • Describe how the proposed project will contribute to the development of a subsequent extramural grant application

iv. Approach and Timeline (3 pages)

            • Include the feasibility of accomplishing the proposed research and/or capacity-building activities. The study must be completed within one year.
            • Describe a community-engaged and/or collaborative research study design and strategies for inclusive participation of all partners and partner organizations (if applicable).
            • Specify the specific data source (e.g. primary data collection or a data base).
            • Outline the processes for establishing a data use agreement and obtaining IRB approval within the first 90 days of the award

v. Investigative Team (1 page maximum)

            • Provide a description of the investigative team and their experience related to the proposed study

vi. Partnership Plan (1 page maximum)

            • See the Sample Partnering Agreement Template from the NIH Office of the Ombudsman in the Center for Collaborative Resolution for elements to address in this section https://ombudsman.nih.gov/partnerAgree)

vii. References Cited (40 references maximum)

            • List only references cited in the project description or supplementary documents of the proposal.

viii. The Budget and Budget Justification (2 pages)

            • Use the NIH Detailed Budget for Initial Budget Period for page one.
            • Justification should be included under the separate fields for itemizing costs (consultants, equipment, supplies, travel, etc.) for page 2. The total budget cannot exceed $150,000 and must include direct and indirect costs. Applicants should budget for travel costs to attend the Hub Annual meeting and the AIM-AHEAD Consortium August 6th-9th Annual Meeting.

ix. Responsible Conduct of Research, Human Subjects, and Animal Training

NIH funding requires that investigators and all key personnel MUST comply with the Responsible Conduct of Research requirement. Additionally, projects that involve human subjects or data from living humans are required to submit the study protocol for review from an Institutional Review Board (IRB) and provide documentation of the determination from the IRB.

There is flexibility in assigning page limits among the components, but the proposal should not exceed 9 pages excluding the reference list.  Use 11-point Arial font, single-spaced lines, and margins of at least 0.5 inches.

 

Review Criteria

 

Applications submitted to the AIM-AHEAD Coordinating Center will be reviewed for scientific and technical merit through a peer-review process. Peer reviewers will use the following criteria to evaluate and score the applications. Based on the scores, AIM-AHEAD Multiple Principal Investigators (MPIs) will make recommendations to NIH for grant awards.

 

  • Is the proposal led by a community-based organization that demonstrates a willingness to engage in the proposed research and/or capacity building activities?
  • Do the AI research projects reflect community input?
  • Are the study methods and findings shared back with the community?
  • What is the likelihood of accomplishing the specific aims within the period of the award?
  • To what extent does the proposal align with the overall goals of the AIM-AHEAD Consortium?
  • Does the application propose to develop novel algorithms or methods for addressing a health disparity, or generate novel insights into factors that contribute to a health disparity?
  • Does the proposal provide a strong rationale and solid track record for community engagement?
  • To what extent does the proposal describe solid research methods, evidence-informed approaches to build and sustain community partnerships and participation?
  • To what extent is the proposed approach likely or appropriate to achieve the goals of the project? What is the likelihood of a successful outcome?
  • To what extent does the proposal appropriately consider ethical, legal, social, and privacy considerations?
  • Is this project likely to generate sufficient preliminary data that can lead to a larger NIH grant application?

 

An internal pre-review of applications for completeness and adherence to proposal guidelines will be conducted. Incomplete and non-adherent applications will be returned unreviewed. All eligible applications will be reviewed following a modified NIH peer review process. The standard NIH scoring range (1-9) will be used to assess the strengths and weakness of the criteria:

 

  • Overall Impact
  • Significance
  • Innovation
  • Approach

 

Additional Review Criteria. Evaluations of the investigative teams and the institutional environment will be assessed, but not scored.

 

Reviewers will identify a subset of proposals to be considered for funding. The NIH AIM-AHEAD program staff will review the final pool of applications recommended for funding and provide the final approval. PIs. Of proposals recommended will be notified by email. Brief feedback from the reviewers will be provided to all applicants via email.

 

Grantee Expectations

 

The Applied Ethical AI (AEAI) Sub-core was established to provide support in identifying and resolving ethical issues in the AIM-AHEAD program. It is expected that all Hub-Specific Projects will work with the AEAI on the development of an initial ethics review and plan for their project and will commit to participating in two AEAI-supported ethics forums during their sponsorship. These forums are designed to highlight and address ethical challenges in the development and implementation of AI/ML and range from open office hours to moderated discussions on hot topics in ethics and AI/ML.

 

Hub-Specific Project grantees will also be expected to comply with AIM-AHEAD program expectations guidelines which include:

 

  1. Participation in monthly awardee meetings (via Zoom)
  2. Timely submission of monthly progress reports, invoices, and surveys
  3. Participation in annual hub and AIM-AHEAD Consortium meetings
  4. Presentation of project results in AIM-AHEAD meetings
  5. Agreement for AIM-AHEAD to disseminate study findings through online websites, social media, and other communication channels
  6. Provision of a summary of research status about milestones listed in the proposal, challenges faced and plans to overcome those challenges, usage of funds, and next steps
  7. Submission of a provide a final report of research findings, usage of funds, and a list of publications, grant applications, articles, and conference talks emerging from the research should be submitted within. 30 day of project end date.

 

Available Data Sources

 

Applicants may apply to use existing AIM-AHEAD resources including the OCHIN Community Health Equity Database on AIM-AHEAD Service Workbench or MedStar Health EHR through the AIM-AHEAD Data Bridge (AADB).

Dataset options (more information available on below datasets/cohorts):

 

Dataset

Brief Description

Data Allowed

Size

Analysis platform tools

A customized subset from OCHIN Community Health Equity Database

Primary care EHR and SDOH data from a 33-state network of community-based health centers. 

HIPAA Limited Data Set, patient-level data with dates and geographic information if needed for research 

A customized subset will be created from over 6 million records for the research question of approved projects 

AIM-AHEAD Service Workbench

Five curated MedStar Health EHR datasets from AIM-AHEAD Data Bridge OR Option for custom curated dataset from MedStar Health EHR

Five curated dataset options of EHR data from underserved communities

De-identified dataset; Multiple curated dataset options

(see detailed data description on the AADB website) information below for dataset descriptions)

MedStar Health EHR has a population of 5+ million records; curated datasets vary in size - See AADB website for more information MedStar Health EHR5 curated datasets from a population of 5+4 million records.

AIM-AHEAD Data Bridge

Selected 88 Open datasets on AWS 

A variety of datasets available including clinical and genomic data

Public data, and controlled access data (depends on dataset)

Selected 88 Open datasets on AWS 

AIM-AHEAD Service Workbench

 

OCHIN Community Health Equity Database

 

OCHIN, a nonprofit health care innovation center with a core mission to advance health equity, operates the most comprehensive database on primary healthcare and outcomes of traditionally underserved patients. The OCHIN Epic EHR data warehouse aggregates electronic health record (EHR) and social determinants of health (SDOH) data representing >6 million patients from 170 health systems and 1,600 clinic sites across 33 states (4.6 million patients are ‘active,’ with a visit in the last 3 years).

 

Approved AIM-AHEAD projects can obtain access to up to 10 years of longitudinal OCHIN Epic ambulatory EHR data, which is research-ready on the PCORnet Common Data Model (CDM). Contributing health systems are outpatient community-based health centers, which deliver comprehensive, culturally responsive, high-quality primary care health care services for communities most impacted by health disparities. This includes individuals and families experiencing poverty, houselessness, migrant agricultural workers and veterans. Community-based health centers often provide on-site services such as dental, pharmacy, mental health, substance abuse treatment, and social work regardless of patients’ ability to pay.

 

The OCHIN Community Health Equity Database will be accessed on the AIM-AHEAD Service Workbench.

 

See Data Dictionary of the OCHIN Community Health Equity Database on AIM-AHEAD Service Workbench.

 

MedStar Health AADB Data

 

MedStar Health Research Institute hosts a robust database of Electronic Health Records wich can be made available to approved applications. The MedStart Health System includes an extensive network of clinical facilities in the mid-Atlantic region, including 10 hospitals (33% rural hospitals) and includes over 300 points-of-care connected by MedStar’s HER system, built on the Cerner Millennium platform. The system includes 5 million unique patients with approximately 31% African American patients. Project-specific datasets can be curated and made available for pilot use. Additionally, the AADB has curated six AI/ML ready datasets which are fully de-identfied and ready for access upon regulatory clearance.

Six AADB available curated datasets:

  • Cardiometabolic correlates and maternal health
  • COVID-19 pandemic: Cardiometabolic, cancer, and behavioral health
  • Opioid use and misuse
  • Schizophrenia data
  • Voice-Assisted Personal Assistance in Heart Failure
  • Breast and Lung Cancer Images

To learn more about these data, visit the AADB website.

 

Requirements Prior to Obtaining Access to AIM-AHEAD Curated Data (AADB):

  • Mandatory Human Subjects Research Trainings such as CITI “Human Research (Protection of Human Subjects)” and “Responsible Conduct of Research”
  • Initial data consult with the MedStar Health AADP personnel to refine data request 30 days of award
  • Submission for IRB approval/determination within 60 days of award.
  • Signed data use agreement and IRB approval/determination within 90 days of award. Applicants unable to meet this requirement must notify Hub MPIs for recommendation on project feasibility.

 

ScHaRe

 

As described on the NIMHD website, the Science Collaborative for Health disparities and Artificial intelligence bias REduction (ScHARe) is a cloud-based platform for population science including social determinants of health (SDOH), and data sets designed to accelerate research in health disparities, health and healthcare delivery outcomes, and artificial intelligence (AI) bias mitigation strategies.

ScHARe aims to fill three critical gaps:

  • Increase participation of women and underrepresented populations with health disparities in data science through data science skills training, cross-discipline mentoring, and multi-career level collaborating on research.
  • Leverage population science, SDOH, and behavioral Big Data and cloud computing tools to foster a paradigm shift in health disparity, and health and healthcare delivery outcomes research.
  • Advance AI bias mitigation and ethical inquiry by developing innovative strategies and securing diverse perspectives.

 

https://www.nimhd.nih.gov/resources/schare/

 

Glossary

 

Community-based Participatory Research (CBPR) - CBPR is a collaborative research approach that equitably engages community members, researchers, and other stakeholders in the research process and recognizes the unique strengths that each contributes bring (Kellogg Foundation).

 

Social Determinants of Health – Social determinants of health (SODH) are the conditions in the environments where 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. (Healthy People 2030).

 

Synthetic Data - Synthetic datasets are generated through computer programs, instead of being composed through the documentation of real-world events. The primary purpose of a synthetic dataset is to be versatile and robust enough to be useful for the training of machine learning models. (https://www.unite.ai/what-is-synthetic-data/).

 

Questions

Questions regarding the Hub-Specific Pilot Program, please create a help desk ticket and select the regional hub in the dropdown based on your location (refer to regional hubs and states table above): Create Help Desk Ticket

 

 

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