Rev3_CDC-RFA-DD-24-0051.pdf

Centers for Disease Control and Prevention

NATIONAL CENTER ON BIRTH DEFECTS AND DEVELOPMENTAL DISABILITIES

Surveillance of Congenital Heart Defects Among Children, Adolescents, and Adults

CDC-RFA-DD-24-0051

05/14/2024

Table of Contents A. Funding Opportunity Description

B. Award Information

C. Eligibility Information

D. Application and Submission Information

E. Review and Selection Process

F. Award Administration Information

G. Agency Contacts

H. Other Information

I. Glossary

Part I. Overview Applicants must go to the synopsis page of this announcement at www.grants.gov and click on the "Subscribe" button link to ensure they receive notifications of any changes to CDC-RFA- DD-24-0051. Applicants also must provide an e-mail address to www.grants.gov to receive notifications of changes.

A. Federal Agency Name:

Centers for Disease Control and Prevention (CDC)

B. Notice of Funding Opportunity (NOFO) Title:

Surveillance of Congenital Heart Defects Among Children, Adolescents, and Adults

C. Announcement Type: New - Type 1:

This announcement is only for non-research activities supported by CDC. If research is proposed, the application will not be considered. For purposes of this NOFO, research is defined as set forth in 45 CFR 75.2 and, for further clarity, as set forth in 42 CFR 52.2 (see eCFR :: 45 CFR 75.2 -- Definitions and https://www.gpo.gov/fdsys/pkg/CFR-2007-title42-vol1/pdf/CFR- 2007-title42-vol1-sec52-2.pdf. In addition, for purposes of research involving human subjects and available exceptions for public health activities, please see 45 CFR 46.102(l) (https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46/subpart-A/section- 46.102#p-46.102(l)).

New- Type 1

D. Agency Notice of Funding Opportunity Number:

CDC-RFA-DD-24-0051

https://www.grants.gov/ https://www.grants.gov/ https://www.gpo.gov/fdsys/pkg/CFR-2007-title42-vol1/pdf/CFR-2007-title42-vol1-sec52-2.pdf https://www.gpo.gov/fdsys/pkg/CFR-2007-title42-vol1/pdf/CFR-2007-title42-vol1-sec52-2.pdf https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46/subpart-A/section-46.102#p-46.102(l) https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46/subpart-A/section-46.102#p-46.102(l)

E. Assistance Listings Number:

93.073

F. Dates:

1. Due Date for Letter of Intent (LOI):

04/12/2024 Recommended but not Required April 12, 2024

2. Due Date for Applications:

05/14/2024 11:59 p.m. U.S. Eastern Standard Time, at www.grants.gov.

3. Due Date for Informational Conference Call Topic: DD24-0051 CHD STAR 2 NOFO - Informational Call

Time: Mar 27, 2024 11:00 AM Eastern Time (US and Canada)

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G. Executive Summary:

Summary Paragraph NOFO Amendment to reflect the following changes:

1. Attached Q&A document as General

2. Attached Informational Webinar PDF Slides as General

3. Updated the Organizational Capacity of Recipients to Implement the Approach

Component A and B Section with guidance on attachment details.

NOFO # DD24-0051 solicits non-research, cooperative agreement applications to conduct population-based surveillance of congenital heart defects (CHD) to describe health outcomes including health equity, with the goal of identifying opportunities to improve the health of all people living with CHD. This project will involve a required component (A) and an optional component (B). The population included in this surveillance activity can be an entire state or a region within a state. Individuals with CHD should be identified through existing data sources including the jurisdiction birth defects surveillance system, electronic health records, administrative data (e.g., Medicaid/Medicare, hospital discharge), or other sources available to funding recipients.

a. NOFO Type:

CA (Cooperative Agreement)

b. Approximate Number of Awards https://cdc.zoomgov.com/u/adbU2aKUYw mailto:1610383146@sip.zoomgov.com

Component A: 3-7 awards

Component B: 1 award

c. Total Period of Performance Funding:

$15,500,000

d. Average One Year Award Amount:

$500,000 Component A: Up to $500,000

Component B: Up to $50,000 for Year 1 budget period, up to $300,000/year Years 2-5

e. Total Period of Performance Length:

5 year(s)

f. Estimated Award Date:

August 30, 2024

g. Cost Sharing and / or Matching Requirements:

No

Part II. Full Text

A. Funding Opportunity Description

1. Background

a. Overview Congenital heart defects (CHD) affect about 1% of all births in the United States and are a leading cause of birth defect-associated infant mortality, morbidity, and healthcare costs.

Improvements in early detection and treatment of CHD and consequently in survival have resulted in many people, including those affected by a severe CHD, living into adolescence and adulthood. An estimated two million persons in the U.S. are living with a CHD, including over one million adults; about 12% of these affected adults have a severe CHD. Most current efforts to conduct population-based surveillance of CHD have focused on monitoring newborns.

However, limited data exist on the descriptive epidemiology of CHD beyond early childhood in the U.S. Despite the public health burden, the lack of population-based surveillance precludes reliable data on people with CHD, their survival, healthcare utilization, and characteristics associated with long-term outcomes.

The federal Patient Protection and Affordable Care Act (PL 111-148, Section 10411) authorized CDC to “enhance and expand infrastructure to track the epidemiology of congenital heart disease and to organize such information into a nationally-representative, population-based surveillance system” for the purpose of facilitating “further research into the types of health services patients use and to identify possible areas for educational outreach and prevention.”

In FY12, CDC funded three recipients to pilot innovative methods of conducting population-based surveillance of adolescents and adults living with CHD, finding that surveillance is feasible, though linkage/deduplication is labor-intensive. In FY15, CDC funded five recipients to develop or expand surveillance of CHD and share individual level, de-duplicated, de-identified data with CDC. For both prior NOFOs, cases were identified through healthcare encounters with CHD diagnosis codes from various data sources. Through these projects we found that CHD diagnosis codes have limitations in identifying CHD cases accurately. Therefore, in FY19, CDC modified surveillance methods to more accurately identify CHD cases, funding seven recipients to conduct surveillance of children, adolescents, and adults with CHD ages 0-55 years over a ten-year surveillance period. These seven recipients were funded to develop new methods to increase true case identification and assess longer-term outcomes among individuals with CHD. In FY20, CDC funded one recipient to validate billing codes for congenital heart defects in healthcare claims data and determine best ways to use healthcare claims for CHD surveillance across the lifespan, using machine learning and natural language processing.

Through NOFO #DD24-0051, recipients will translate lessons learned from prior NOFOs to conduct population-based surveillance of CHD to describe health outcomes including health equity, with the goal of identifying opportunities to improve the health of all people living with CHD. Component A recipients will identify CHD cases through various data sources, including birth defects surveillance, clinical data, hospital discharge data, and healthcare claims data.

Component B will develop and refine a machine learning model that improves accuracy of CHD case identification and will apply the model to data collected through Component A, thereby improving generalizability of results obtained from large administrative datasets and enhancing public health surveillance efforts.

b. Statutory Authorities This program is authorized under Section 399V-2 of the Public Health Service Act [also cited as 42 U.S.C. 280g-13].

More specifically, CDC acting through the Secretary is authorized to study and track the epidemiology of congenital heart disease to understand health outcomes for individuals with congenital heart diseases across all ages.

c. Healthy People 2030 NCBDDD is committed to achieving the health promotion objectives of “Healthy People 2030”

This NOFO addresses the following priority areas:

• Reduce the rate of infant deaths

• Reduce the rate of deaths in children and adolescents aged 1-19 years

• Increase the proportion of children and adolescents who o Receive care in a medical home o Get support for their transition to adult health care

• Improve cardiovascular health in adults

• Improve cardiovascular health and reduce deaths from heart disease and stroke

Reduce maternal deaths https://health.gov/healthypeople

d. Other National Public Health Priorities and Strategies CDC’s mission is to promote health and quality of life by preventing and controlling disease, injury, and disability. One of the many strategies that CDC employs to accomplish this goal includes monitoring health through surveillance. Disease specific surveillance systems are critical for the accomplishment of this and other objectives that support CDC’s mission.

This program is aligned with CDC's mission of saving lives and protecting people from health threats (http://www.cdc.gov/about/organization/mission.htm). This program is also aligned with CDC's role of conducting critical science, providing health information that protects our nation against expensive and dangerous health threats, and responding when these arise.

e. Relevant Work This NOFO expands the National Center on Birth Defects and Developmental Disabilities’ programs conducting birth defects surveillance across the lifespan (http://www.cdc.gov/ncbddd/heartdefects/research.html).

In FY12 under NOFO #DD12-1207, CDC funded three recipients to pilot innovative methods of conducting population-based surveillance of adolescents and adults living with CHD identified through healthcare encounters from 2008-2010.

In FY15 under NOFO #DD15-1506, CDC funded five recipients to develop or expand their surveillance of CHD and share individual level, de-duplicated, de-identified data with CDC. For both prior NOFOs, cases were identified through healthcare encounters with CHD codes from various data sources in 2011-2013.

In FY19, under NOFO #DD19-1902, Component A, CDC funded seven recipients to conduct surveillance of children, adolescents, and adults with CHD ages 0-55 years over a ten-year surveillance period, 2010-2019. Recipients were funded to develop new methods to increase true case identification and assess longer-term outcomes among individuals with CHD.

In FY20, under NOFO #DD19-1902, Component B, CDC funded one recipient to validate billing codes for congenital heart defects in healthcare claims data and determine best ways to use healthcare claims for CHD surveillance across the lifespan, using machine learning and natural language processing.

2. CDC Project Description

a. Approach

Bold indicates period of performance outcome.

Strategies and Activities

Short-term Outcomes Intermediate Outcomes

Long-Term Outcomes

Components A & B

Program Planning

• Identify/engag e partners, establish partnership

Component A

• Improved knowledge about the characteristics of individuals identified from multiple data sources

Components A & B:

• Improved ability to develop surveillanc e programs

Component A & B:

• Improved health among individual s of all collaborations;

prioritize program goals, define source population, identify data sources

Project Management

• Develop management and staffing plan

• Obtain or demonstrate legal authority to access data

Data Reporting

• Collect/store standardized data, submit individual-level data to

CDC

Dissemination

• Share information, communicate results

• Inform stakeholders on healthcare utilization, comorbidities, and outcomes of individuals with CHD

Component A

Case Identification

• Improved understanding of:

o age-specific mortality in individuals with CHD o healthcare use, comorbidities and outcomes of individuals with CHD o health equity among individuals with CHD o racial, ethnic, and socioeconomi c patterns in healthcare use and long-term outcomes in individuals with CHD o Respiratory viruses (including

COVID-19,

influenza A, influenza B, and RSV) among individuals with CHD with and without current respiratory immunizatio ns o healthcare use during the COVID- 19 pandemic

• Improved use of surveillanc e data to understand the outcomes of individuals with CHDs

• Improved ability of policy-makers to make data-informed decisions

• Improved ability to develop effective secondary prevention strategies to reduce the public health impact of

CHD

Component B:

• Improved accuracy of surveillanc e of CHD ages with

• Improved quality of life of individual s of all ages with

CHD

• Improved continuity of care of individual s of all ages with

• Use all available data sources (birth defects registry data, clinical and administrative data) to identify eligible cases with CHD

Data collection

• Establish vital status of identified cases, link identified cases to other data sources

• Geocode address, link healthcare and census data, create standardized dataset

Data Assessment

• Describe population with CHD

• Validate 200- 300 randomly selected cases per site (if funded for

DD19-1902)

• Assess quality and accuracy of data

Dissemination

• Work with local/state partners to use among individuals with CHD o the potential impact of state and national healthcare policies on individuals with CHD

• Increased awareness among stakeholders of nationwide CHD issues

Component B:

• Improved understanding of how machine learning algorithms and models can be applied to surveillance data to identify individuals with CHD site-specific CHD data

Component B

Data Assessment

• Develop and refine a machine learning model for the surveillance data collected through Component A

• Apply this machine learning model to data collected from all recipients funded through Component A

Data Reporting

• Document the process from raw data (from Component A) to final classification for complete reproducibility

• Submit pre-processed dataset and model via standardized format, model code and documentation , and results (i.e., model’s classification for each individual person) to

CDC

Dissemination

• Share information, communicate results

i. Purpose This NOFO supports population-based surveillance of CHD to describe health outcomes and health equity, with the goal of identifying opportunities to improve the health of all individuals living with CHD.

ii. Outcomes Short-term outcomes:

Component A:

• Improved knowledge about the characteristics of individuals identified from multiple data sources

• Improved understanding of:

o age-specific mortality in individuals with CHD o healthcare use, comorbidities, and outcomes of individuals with CHD o health equity among individuals with CHD o racial, ethnic, and socioeconomic patterns in healthcare use and long-term outcomes in individuals with CHD o Respiratory viruses (including COVID-19, influenza, and RSV) and immunizations among individuals with CHD o healthcare use during the COVID-19 pandemic among individuals with CHD o the potential impact of state and national healthcare policies on individuals with

• Increased awareness among stakeholders of nationwide CHD issues

• Improved understanding of how machine learning algorithms and models can be applied to surveillance data to identify individuals with CHD

Intermediate outcomes:

Component A:

• Inform stakeholders on healthcare utilization, comorbidities, and outcomes of individuals with CHD

Component B:

• Improved accuracy of surveillance of CHD

iii. Strategies and Activities The logic model presents the strategies and component activities to be undertaken to achieve the period of performance outcomes.

Program Planning

• Identify and engage partners, establish partnership collaborations: Demonstrate effective relationships and cooperation with appropriate partners (e.g., state officials/state health departments; cross-department personnel, including informatics personnel within state health department; birth defects surveillance programs; medical centers; academic medical centers specializing in CHD; community-based organizations; patient/parent CHD support groups within catchment area/region).

• Identify and prioritize program goals: Identify goals, measurable objectives, and performance measures, responsible parties, and timeline to achieve the desired outcomes of the project.

• Define and describe the source population: Provide a clear definition of the source population (a minimum total population size of the defined geographic region should equal 1 million per year as evidenced by census data). For planning, the three-year time period of 2021-2023 (calendar years) should be used.

• Identify data sources: Name and describe each data source that will be used to identify individuals with CHD. Indicate sources that can be accessed immediately and those that will need additional approvals. Describe any new datasets that might be used, and how access to those will be obtained, and estimated length of time to obtain data. Data should be population-based, or information should be provided on how the data will provide estimates that approximate population-based estimates with respect to racial/ethnic and socioeconomic diversity. Utilization of population-based birth defects surveillance program data is strongly encouraged.

Project Management

• Develop a management and staffing plan for implementation of this program.

• Document legal authority to access data: Provide evidence of legal authority to access each of the proposed data sources and to share de-identified, de-duplicated individual-level data with CDC and other recipients of this cooperative agreement, including addressing any HIPAA and IRB requirements. Examples of past access and data transmission should be described. It is strongly recommended that applicants provide letters of support (or other documents) from each agency that houses source data authorizing access and sharing of required data. Data elements are included in the Appendix.

• Describe how information about this project will be disseminated to stakeholders (meetings, leadership briefings, newsletters, website, etc.)

• Participate on all cooperative agreement calls and on-site meetings. All sites will have at least one representative on all workgroups and will lead projects on a shared basis.

• Update CDC and other recipients regularly (at a minimum, monthly) on project status and outputs. Maintain recipient-specific documentation on data sources, collection methods, linkage, data reconciliation (e.g., how recipient determined race/ethnicity of case when information differed in multiple data sources).

Case Identification

• Use all available data sources (birth defects registry data, clinical and administrative data sources) to identify eligible cases with congenital heart defects (CHD). Applicants should demonstrate, through memorandums of understanding (MOUs) and/or letters of support, the ability to access and share the data per the NOFO parameters. Demonstrate capacity to access, link, and use data from healthcare database(s) to identify individuals with one or more healthcare encounters during 2021-2023.

Eligible cases:

o Will be ages 0-64 years at any time between 2021-2023 o Reside in the source population geographic area at any time during 2021-2023 o Have one or more of the following ICD-10-CM (or equivalent ICD-9-CM or BPA) CHD codes in a case finding data source (birth defects registry data, clinical and administrative data):

Severity ICD-10-CM codes

Severe Q23.4, Q22.4, Q22.6, Q20.4, Q22.0, Q20.0, Q20.1, Q20.2, Q21.3, Q20.3, Q20.5, Q21.2, Q25.21, Q26.2

Shunt Q21.0, Q21.1, Q21.8, Q21.9, Q25.0, Q21.4, Q26.3, Q26.4

Valve Q22.3, Q22.1, Q22.2, Q22.5, Q22.8, Q22.9, Q23.0, Q23.1, Q23.8, Q23.9, Q23.2, Q23.3, Q24.4, Q24.3, Q25.1, Q25.3, Q25.42, Q25.29, Q25.41, Q25.5, Q25.71, Q25.79

Other Q24.2, Q24.5

Other Vascular Q25.45, Q25.47, Q25.48

Data collection

• Access and link existing data sources that will be used to assess outcomes of identified cases: demonstrate capacity to access, link (to identified cases), and analyze data from clinics, health providers, vital records, birth defect registries, immunization systems, hospital discharge, payers, and other sources.

• Describe in detail all databases the applicant can currently link to and has future plans to link to, including owner of database, number and demographic characteristics of individuals in database, and representativeness of individuals in database to source population.

• Identify and describe any database/data use agreement or IRB data transmission restrictions and whether and how these restrictions may limit descriptive analyses and reporting of results.

• Describe the proposed linkage process including how the data will be de-duplicated both within and across each data set.

• Establish vital status of identified cases: Link identified cases to National Death Index (NDI) data to establish vital status; recipients may choose to link first to state death records and then link those who did not link to state death records, to NDI.

• Determine most recent address in data, geocode address, and link healthcare encounter data to census data to collect census tract-level demographic and socioeconomic status indicators agreed upon by CDC and all program recipients (e.g. % below federal poverty level; % Hispanic ethnicity; rurality).

• Create standardized diagnostic, morbidity, and healthcare resource utilization groupings as agreed upon by CDC and all program recipients.

Data Reporting

• Collect/store standardized data: Collect and store data from all data sources (case-finding, healthcare encounters, NDI, vital records, census data, etc.) in a standardized manner with common data elements o Refer to Appendix for a copy of the required data elements to be used for this project.

o Submit to CDC de-identified, de-duplicated individual level data, including standardized data elements using a common database in a secure manner in a timeline established by CDC. Component A recipients will have final dataset submitted to CDC by end of project Year 3 (September 2027). CDC has a secure network that will be used for this project and recipients will need to obtain and maintain access.

Data Assessment

• Improve knowledge of characteristics of individuals with CHD, including age-specific mortality, healthcare utilization, comorbidities, and other outcomes, and improve understanding of racial/ethnic, socioeconomic, or rural/urban patterns in healthcare use or long-term outcomes.

• Describe population of individuals with CHD including:

• Examine state and national healthcare policies that have an impact on people with CHD

• Assess quality of data sources for completeness of data (e.g., percent missing demographic data, provider type).

• If applicant was previously funded for NOFO #DD19-1902: In Year 1 of the current

NOFO (#DD24-0051), validate 200-300 randomly selected cases through abstraction of detailed medical records to complement work of Component B of this program.

• Healthcare utilization

• Distribution of CHD severity, cardiac/non-cardiac comorbidities, long-term outcomes

• Racial/ethnic, socioeconomic, or rural/urban differences in healthcare use and long-term outcomes

• Examine respiratory viruses and immunization among individuals with CHD, including changes in healthcare utilization in individuals with CHD over the course of the COVID- 19 pandemic

Dissemination

• Work collaboratively with all recipients and CDC using the multi-site data to communicate project information and results to healthcare providers, patients, families, stakeholders, the general public and other target audiences via publications, presentations, and other methods.

• Work with local/state partners to use site-specific CHD data and understanding of the epidemiology of CHD, to identify potential areas for systems-based improvements.

• Participate in collaborative projects/manuscripts using multi-site data whenever possible.

• Lead one or more collaborative manuscripts using multi-site data and submit to CDC clearance within 12 months of data finalization.

Component B

Program Planning

• Identify and engage partners as needed, establish collaborations: The collaborative team of staff and partners should include machine learning experts, data scientists, data engineers, epidemiologists, birth defects surveillance experts, and CHD subject matter experts.

• Identify and prioritize program goals: Identify goals, measurable objectives, performance measures, responsible parties, and timeline to achieve the desired outcomes of the project.

Project Management

• Develop a management and staffing plan for implementation of this program: Identified staff must include staff members or collaborating partners who have experience training machine learning models for healthcare data with administrative diagnosis codes (e.g., ICD-10-CM), and have the appropriate expertise to understand existing machine learning models, implement transfer learning of pre-trained models to new data, and adjust parameters and thresholds of the machine learning pipeline or otherwise refine pre-trained models as needed for proper application to new data.

Data Assessment

• Develop and refine a machine learning model for the surveillance data collected through Component A: The recipient should refer to materials and references provided by CDC upon funding for descriptions of existing machine learning models (pre-trained on similar data) to be used as the base for this component of the current NOFO. The recipient must evaluate the annotated dataset of the 200-300 validated cases per Component A recipient (among those previously funded for NOFO #DD19-1902), including calculating the positive predictive value, negative predictive value, and other relevant metrics. The recipient must then use the annotated data to further develop and refine the pre-trained models provided by CDC via transfer learning, such that they can be confidently applied to data on all cases identified in Component A. Recipients must apply the refined machine learning models to data collected from all recipients funded through Component A.

Data Reporting

• Document the end-to-end process from raw data (from Component A) to final classification with transparency for complete reproducibility and accurate use. Submit all datasets (including raw and preprocessed datasets), all source code to train the model, the final trained model (via a standardized format), documentation, and results (i.e., model’s classification for each individual person) to CDC in a secure manner. CDC has a secure network that will be used for this project and recipients will need to obtain and maintain access.

Dissemination

• Add the source code(s), trained model(s), and corresponding documentation on a publicly available platform (e.g., GitHub)

• Work collaboratively with all recipients and CDC using the multi-site data to communicate project information and results to healthcare providers, patients, families, stakeholders, the general public and other target audiences via publications, presentations, and other methods. The multi-site data should include the model’s classification for each individual person.

Participate in collaborative projects/manuscripts using multi-site data whenever possible.

1. Collaborations Components A & B

1. Collaborate with CDC and NOFO #DD24-0051 recipients to provide input on standardized processes, methods, standardization of data collection, and other project activities (required).

a. With other CDC programs and CDC-funded organizations:

Components A & B

1. Collaborate with CDC and NOFO #DD24-0051 recipients to provide input on standardized processes, methods, standardization of data collection, and other project activities (required).

b. With organizations not funded by CDC:

Component A

· Collaborate and coordinate across state agencies and clinical settings for data collection.

Demonstrate effective relationships and cooperation with appropriate partners with access to clinical databases, administrative databases, immunization records, birth defects surveillance data. Past collaborations with each of these partners should be described.

· Letters of support are strongly encouraged from all agencies that will contribute data to the project. For all source data that the applicant does not “own”, a letter of support from the holder of the data must be included, that addresses timeline for access to the data and an understanding that individual level, de-duplicated, de-identified data will be shared with CDC and the other NOFO #DD24-0051 recipients.

· All applicants are strongly encouraged to partner with a birth defects surveillance program and provide a letter of support describing the collaboration. If the applicant is not a state health department, then the applicant is strongly encouraged to include a letter of support from the state health department.

· Involve appropriate within-region partners, such as health care providers, community-based organizations, academic medical centers and/or outpatient centers specializing in CHD care, and other organizations to assist with project activities.

· The collaborative team should comprise personnel with expertise in birth defects surveillance, clinical care of patients with CHD, informatics, data scientists, epidemiology, project management/coordination.

· Work with CDC and other recipients to agree on standardized processes, methods, standardization of data collection, and other project activities.

· Provide evidence of legal authority to access individual-level, identifiable data from the relevant data sources for identification of sources.

· Provide evidence of legal authority to share individual-level, de-duplicated, de-identified data from the relevant data sources.

Component B

· The collaborative team should comprise personnel with machine learning, data science, and data engineering, epidemiology, expertise in birth defects surveillance, and clinical care of patients with CHD.

· Work with CDC and other recipient(s) to agree on standardized processes, methods, standardization of data collection, and other project activities.

2. Population(s) of Focus Component A: Describe the population of individuals aged 0-64 with CHD including demographics, such as race/ethnicity, or socioeconomic status, or rural/urban distribution and reside in the defined geographic area of the source population.

Component B: N/A

This NOFO, including funding and eligibility, is not limited based on, and does not discriminate on the basis of race, color, national origin, disability, age, sex (including gender identity, sexual orientation, and pregnancy) or other constitutionally protected statuses.

a. Health Disparities The goal of health equity is for everyone to have a fair and just opportunity to attain their highest level of health. Achieving this requires focused and ongoing societal efforts to address historical and contemporary injustices; overcome economic, social, and other obstacles to health and healthcare; and eliminate preventable health disparities.

Broadly defined, social determinants of health are non-medical factors that influence health outcomes. They are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life. These forces (e.g., racism, climate) and systems include economic policies and systems, development agendas, social norms, social policies, and political systems. See content below and in other sections (e.g., Approach, Collaborations, Populations of Focus) for information on how this specific NOFO affects social determinants of health.

A health disparity is a preventable difference in the burden of disease, injury, violence, or opportunities to achieve optimal health that are experienced by populations that have been socially, economically, geographically, and environmentally disadvantaged. Health disparities are inextricably linked to a complex blend of social determinants that influence which populations are most disproportionately affected by these diseases and conditions.

The goal of health equity is for everyone to have a fair and just opportunity to attain their highest level of health. Achieving this requires focused and ongoing societal efforts to address historical and contemporary injustices; overcome economic, social, and other obstacles to health and healthcare; and eliminate preventable health disparities.

Broadly defined, social determinants of health are non-medical factors that influence health outcomes. They are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life. These forces (e.g., racism, climate) and systems include economic policies and systems, development agendas, social norms, social policies, and political systems. See content below and in other sections (e.g., Approach, Collaborations, Populations of Focus) for information on how this specific NOFO affects social determinants of health.

A health disparity is a preventable difference in the burden of disease, injury, violence, or opportunities to achieve optimal health that are experienced by populations that have been socially, economically, geographically, and environmentally disadvantaged. Health disparities are inextricably linked to a complex blend of social determinants that influence which populations are most disproportionately affected by these diseases and conditions.

Surveillance data should be population-based, and not limited to individuals aged 0-64 years receiving healthcare, receiving cardiology care, or based on type of health insurance (e.g., Medicaid). The applicant’s defined geographic area and population covered should include all individuals aged 0-64 years with the CHD ICD-10-CM codes listed on page 8 (Strategies & Activities, Case Identification section). To address health disparities, data reported to CDC should include but not limit to ethnicity, race, gender, geography (e.g., rural, urban), and language spoken at home.

iv. Funding Strategy Component A: 3-7 awards for 5 year period of performance; up to $500,000 average award per budget period

Component B: Up to $50,000 for Year 1, up to $300,000/year for Years 2-5

b. Evaluation and Performance Measurement

i. CDC Evaluation and Performance Strategy

Component A:

Evaluation and progress reports:

• Prepare a written assessment of the accomplishments, challenges, and opportunities of the CHD surveillance project including a description of the problems encountered, lessons learned, potential improvements, etc.

• CDC will work with recipients to finalize measures within the first six months of the period of performance.

Strategies/Activities:

• Program Planning activities: Identify/engage partners, establish partnership collaborations; prioritize program goals, define source population, identify data sources.

Indicators for success:

• Partners are identified and letters of support from all agencies that will contribute data to the project are included in application.

• If the applicant is not a state health department, a letter of support from the state health department is included in the application.

• Updates are provided to CDC on routine partner meetings and calls.

• Program goals are identified and prioritized.

• Source population is defined, data sources are identified.

• Project Management activities: Develop management and staffing plan; obtain legal authority to access data.

• Comprehensive management and staffing plan provided in application.

• Progress on implementation of staffing plan provided to CDC.

• Evidence of legal authority, or detailed steps/timeline needed to obtain legal authority is provided in application.

• Dissemination plan is described

• Case Identification activities: Use all available data sources (birth defects registry data, clinical and administrative data) sources to identify eligible cases with congenital heart defects (CHD)

• Individuals with one or more ICD code for CHD identified in case finding data sources.

• Data Collection activities: Establish vital status of identified cases, link identified cases to other data sources; geocode address, link healthcare and census data, create standardized dataset.

• Vital status of identified cases have been established.

• Data sources have been accessed and linked; linkage success rates for vital records, immunization records, and healthcare data have been calculated.

• Addresses have been geocoded.

• Data elements have been collected in standardized manner at each site.

• Data Reporting activities: collect/store standardized data, submit de-identified, de-duplicated individual level encounter and summary level data to CDC.

• Data standardization and storage processes are documented and sent to CDC.

• De-identified, de-duplicated individual level data has been submitted to CDC within agreed upon benchmarks and timeframes.

• Feasibility of having final linked, deduplicated, de-identified dataset to CDC by the end of Year 3 is described in application.

• Data Assessment activities: Describe population with CHDs; validate 200-300 randomly selected cases per site (if funded for DD19-1902); assess quality and accuracy of data.

• Data analysis plan developed and descriptive statistics generated on population with CHD, including healthcare utilization, CHD severity, cardiac/non-cardiac comorbidities, and other long-term outcomes.

• Racial/ethnic, socioeconomic, or rural/urban differences in healthcare use and long-term outcomes have been assessed.

• Respiratory viruses and related immunizations (e.g., COVID-19, influenza, RSV) among individuals with CHD has been assessed.

• If funded for NOFO #DD19-1902, 200-300 randomly selected cases have been validated.

• Dissemination activities: Share information, communicate results.

• Communication plan is developed (including metrics on estimating audience reach, indicators of engagement: e.g., clicks, opens, comments, re-tweets, references/citations, altmetric scores), submitted to CDC, and implemented.

• CDC is notified each time project-related reports (publications, presentations, newsletters, etc.) have been disseminated.

• Information shared regularly with CDC and other recipients.

• Project information and results communicated.

• Site-specific CHD data has been shared with local/state partners.

Outputs:

• Population-based cohort of individuals aged 0-64 years with CHDs

Indicator for success: population-based cohort of individuals aged 0-64 years with CHD has been developed, submitted to CDC, met quality standards, analyzed, and findings disseminated. Dissemination of publication(s) and conference presentations/webinars (measure/report number of conference/webinar participants) that describe population-based cohort of individuals with CHD, by CHD severity and age.

• CHD cases validated

Indicator for success: If applicant was previously funded for NOFO #DD19-1902, in Year 1 of NOFO #DD24-0051, 200-300 randomly selected cases are validated through medical record abstraction

Descriptive epidemiology and mortality

Indicator for success: standardized data have been contributed to support multi-state analyses of descriptive epidemiology of individuals aged 0-64 years with CHD; report(s) on descriptive epidemiology and mortality of individuals aged 0-64 years with CHD has/have been drafted, submitted to CDC clearance within 12 months of data finalization, and disseminated. Dissemination of publication(s) and conference presentations/webinars (measure/report number of conference/webinar participants) that describe epidemiology and mortality for persons with CHD, by CHD severity and age.

Outcomes:

• Improved understanding of age-specific mortality of individuals with CHD.

Indicator for success: Describe estimated reach of disseminated publications (e.g, altmetric scores) and number of participants participating in conference and webinar presentations that describe age-specific mortality of individuals with CHD.

• Improved understanding of health equity among individuals with CHD.

Indicator for success: Describe estimated reach of disseminated publications (e.g., presentations that describe health equity among individuals with CHD. Improved understanding of racial/ethnic or socioeconomic patterns in healthcare use or long-term outcomes in study population presentations that describe racial/ethnic or socioeconomic patterns in healthcare use or long-term outcomes in study population.

• Improved understanding of respiratory viruses (including COVID-19 and influenza) and related immunizations among individuals with CHD presentations that describe respiratory viruses and related immunizations among individuals with CHD.

• Increased awareness among health service providers, patients, parents and public of nationwide CHD issues

Indicator for success: dissemination of publication(s) (describe estimated reach, e.g, altmetric scores) and their key messages through various media, and conference presentations/webinars (measure/report number of conference/webinar participants) for partners that increase awareness of nationwide CHD issues.

Evaluation and progress reports:

• Prepare a written assessment of the accomplishments, challenges, and opportunities of the CHD surveillance project including a description of the problems encountered, lessons learned, potential improvements, etc.

• CDC will work with recipients to finalize measures within the first six months of the period of performance.

Strategies/Activities:

• Program Planning activities: Identify/engage partners, establish partnership collaborations; prioritize program goals, define source population, identify data sources o Partners are identified (machine learning experts, data scientists, data engineers, epidemiologists, birth defect surveillance experts, CHD subject matter experts) and letters of support are included in application.

Indicators for success:

• Updates are provided to CDC on routine partner meetings and calls.

• Program goals are identified and prioritized.

• Project Management activities: Develop management and staffing plan o Comprehensive management and staffing plan with appropriate machine learning expertise provided in application.

• Progress on implementation of staffing plan provided to CDC.

• Data Assessment activities: develop and refine an existing machine learning model (pre-trained on similar data) for the surveillance data collected through Component A; apply this refined machine learning model to data collected from all recipients funded through Component A o Pre-trained machine learning model modified by transfer learning using the annotated dataset of the 200-300 validated cases per Component A recipient (among those previously funded for NOFO #DD19-1902), and evaluated, including calculating the positive predictive value, negative predictive value, and other relevant metrics.

Indicators for success:

• Machine learning model developed and applied to data collected from all recipients through Component A.

• Data reporting activities: document the end-to-end process from raw data (from Component A) to final classification for complete reproducibility; submit all datasets (including raw and preprocessed), all source code to train the model, the final trained model (via standardized format), documentation, and results (i.e., model’s classification for each individual person) to CDC

• End-to-end process from raw data (from Component A) to final classification documented

• Datasets, source code to train the model, the final trained model (in standardized format), documentation, and results submitted to CDC

• Dissemination activities: Share information, communicate results

• Communication plan is developed, submitted to CDC, and implemented.

• Information shared regularly with CDC and other recipients.

• Project information and results communicated

• Source codes, models, and corresponding documentation are publicly available

• Site-specific CHD data has been shared with local/state partners

Outputs

• Machine learning model trained and applied to data collected through Component A

Indicator for success: models trained, tested, applied to Component A data; datasets, source code to train the model, the final trained model (in standardized format), documentation, and results submitted to CDC and released on a publicly available platform (e.g. GitHub).

• Labeled dataset for population-based cohort of individuals aged 0-64 years with

Indicator for success: Multi-site dataset of all individuals with administrative CHD codes in the population-based cohort from Component A includes model’s classification for each individual; this labeled dataset has been submitted to CDC, met quality standards, analyzed, and findings disseminated.

Outcomes

• Improved understanding of how machine learning algorithms and models can be applied to surveillance data to identify individuals with CHD

Indicator for success: dissemination of publication(s) (describe estimated reach, e.g., altmetric scores) and conference presentations/webinars (measure/report number of conference/webinar participants) describing how machine learning model was developed and applied to administrative data for surveillance of individuals with CHD and relevant metrics of the data before and after application.

ii. Applicant Evaluation and Performance Measurement Plan Applicants must provide an evaluation and performance measurement plan that demonstrates how the recipient will fulfill the requirements described in the CDC Evaluation and Performance Measurement and Project Description sections of this NOFO. At a minimum, the plan must describe:

• How applicant will collect the performance measures, respond to the evaluation questions, and use evaluation findings for continuous program quality improvement, including, as applicable to the award, how findings will contribute to reducing or eliminating health disparities and inequities.

• How key program partners will participate in the evaluation and performance measurement planning processes.

• Available data sources, feasibility of collecting appropriate evaluation and performance data, and other relevant data information (e.g., performance measures proposed by the applicant).

• How evaluation findings will be disseminated to communities and populations of interest in a manner that is suitable to their needs.

• Plans for updating the Data Management Plan (DMP) as new pertinent information becomes available. If applicable, throughout the lifecycle of the project. Updates to DMP should be provided in annual progress reports. The DMP should provide a description of the data that will be produced using these NOFO funds; access to data;

data standards ensuring released data have documentation describing methods of collection, what the data represent, and data limitations; and archival and long-term data preservation plans. For more information about CDC’s policy on the DMP, see https://www.cdc.gov/grants/additional-requirements/ar-25.html.

Where the applicant chooses to, or is expected to, take on specific evaluation studies, the applicant should be directed to:

• Describe the type of evaluations (i.e., process, outcome, or both).

• Describe key evaluation questions to be addressed by these evaluations.

• Describe other information (e.g., measures, data sources).

Recipients will be required to submit a more detailed Evaluation and Performance Measurement plan, including a DMP, if applicable, within the first 6 months of award, as described in the Reporting Section of this NOFO.

Data Management Plan (DMP)

Applicants should submit a DMP in their application as part of their Evaluation and Performance Management Plan. A DMP is required for each collection of public health data proposed.

Applicants who contend that the public health data they collect or create are not appropriate for https://www.cdc.gov/grants/additional-requirements/ar-25.html release must justify that contention in the DMP submitted with their application for CDC funds.

The DMP may be outlined in a narrative format or as a checklist, but, at a minimum, should include:

· Description of the data to be produced in the proposed project

· How access will be provided to the data (including provision for protection of privacy, confidentiality, security, intellectual property, or other right)

· Use of data standards that ensure all released data have appropriate documentation that describes the method of collection, what the data represent, and potential limitations for use

· Plans for archival and long-term preservation of the data or explaining why long-term preservation and access cannot be justified

Examples of DMPs include: the USGS site: https://www.usgs.gov/products/data-and-tools/data-management/data-management-plans.

d. Work Plan Applicants are required to provide a detailed work plan for Year 1 of the project and a high-level work plan for subsequent years. No specific work plan format is required as long as the work plan crosswalks to the strategies and activities, outcomes, and performance measures presented in the logic model and narrative sections of this NOFO. A sample work plan format is presented below.

Period of Performance Outcome:

[from Outcomes section and/or logic model]

Outcome Measure:

[from Evaluation and Performance

Measurement section]

Strategies and

Ac…