Key Dates

Related Announcements

NOT-HL-22-061 - Notice to Clarify Expiration Date for NOT-HL-20-815 "Notice of Special Interest (NOSI): Use of Predictive Analytics to Accelerate Late-Stage Implementation Research to Address Heart, Lung, Blood, and Sleep Disorders"

PAR-19-274 - Dissemination and Implementation Research in Health (R01 Clinical Trial Optional)

PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)

NOT-OD-16-025 - Clarifying NIH Priorities for Health Economics Research

NOT-OD-19-122 - Fast Healthcare Interoperability Resources (FHIR ) Standard

Issued by

National Heart, Lung, and Blood Institute (NHLBI)

Purpose

Purpose

NHLBI is issuing this Notice of Special Interest (NOSI) to leverage existing data resources using Predictive Analytics Implementation Research (PAIR) that utilizes complex and innovative methodologies and modeling techniques to rely on integration of existing data to inform the designs (and often test) implementation strategies for heart, lung, blood, and sleep (HLBS) conditions. NHLBI also encourages applications which focus on the development of advance modeling techniques and data reporting, which would be publicly available and could be used to inform subsequent implementation strategies to address HLBS conditions.

Scope

PAIR modeling will be supported to identify the critical details, parameters, or factors for more efficient evidence-based practices (EBP) and guidelines to improve HLBS health and disease outcomes. Repetitive findings across multiple data resources can reveal robust insights from existing information which can be applied to the context-specific design of implementation strategies of EBP as compared to traditional clinical site-specific data which often use de novo data collection for that given site. Intermittent use of predictive analytical methods can refine an on-going EBP implementation strategy to achieve sustainable, adaptive implementation strategies. Using data across communities, PAIR provides unique solutions for preventive strategies and health policy for HLBS.

Data integrated from multiple types of communities (e.g., school, primary care, and clinic) can use complex forecast models and predictive analytics to propose implementation strategies for scale-up. NHLBI encourages applicants to define each community clearly and describe how findings would inform similar communities for this NOSI. The NLM Common Data Definition for the term community is a set of people with some shared elements. That shared element varies widely, from geography to situations to interests to lives and values. For example, a community may be defined by geospatial location, by the type of health practice, by people with a specific set of characteristics, e.g., common diagnoses, genetic traits, risk profiles, etc. There may be multiple types of communities within a particular study depending on the complexity of the predictive analytical methodology and outcomes desired, and the source data used for data integration, analyses, and forecasting.

Collaborations among multiple disciplines are encouraged for this NOSI, including implementation scientists, health system analysts, methodologists, and data repository administrators. The community-based stakeholders and other end-users (e.g., clinicians, public health analysts, patients, parents, clinicians, public health analysts, patients, patient representatives) are welcome along the research continuum, from initial study conception to dissemination and implementation.

We encourage the development and dissemination of the implementation strategy plan, which includes re-usable infrastructure such as national standards for data extraction and interoperability, e.g., NOT-OD-19-122, (i.e., use of Fast Healthcare Interoperability Resources (FHIR), principles of findability, accessibility, interoperability, and reusability (FAIR) data, Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), so that the approach may be replicated longitudinally and allow others to adapt the implementation strategies. Applicants are encouraged to become familiar with the most-recent NIH Strategic Plan for Data Science (November 2020, https://datascience.nih.gov/sites/default/files/NIH_Strategic_Plan_for_Data_Science_Final_508.pdf)).

Applicants considering health economic analyses are encouraged to review NOT-OD-16-025 for the NIH policy related to funding health economics research. PAIR applications defined as clinical trials, according to NOT-OD-15-015, should be submitted in response to PAR-19-274, or its successor. NHLBI is also interested in studies that focus on developing predictive analytical modeling methodologies and PAIR-generated data not defined as a clinical trial. Applicants considering PAIR that are not defined as NIH clinical trials should be submitted in response to PA-20-185 NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).

Prospective applicants are encouraged to contact the most appropriate NLHBI scientific research contact(s) listed below to ensure that the proposed aims are consistent with NHLBI's mission. Scientific research contacts may advise on the criteria for defining an NIH clinical trial and selecting the appropriate Funding Opportunity Announcement (FOA) for this NOSI.

Research projects that could be addressed in response to this NOSI include, but are not limited to, the following:

• Interventions that use PAIR-informed implementation strategies from community-based resources for larger-scale uptake of evidence-based practices and guidelines for efficiency in time, cost, and quality.
• Research studies that use a wide variety of social, behavioral, environmental, demographic, and summary health data that provide comprehensive profiles of health, disease risk factors, burden, and community resources to develop and test models for improving community health outcomes using clinical and public health strategies.

• Research studies using mobile health and personal wearable health technologies coupled with geospatial information for continuous or intermittent monitoring to passively quantify human behaviors, physiologic responses, and environmental exposures to promote health or prevent and treat HLBS disorders.
• Research studies using integrated data from well-defined populations to develop and test community-based decision support tools to enhance prediction models for HLBS health promotion and prevention outcomes.

• Model complex, multilevel data from public health policy, community stakeholders, and other healthcare decision-makers to assess and design rapid solutions to prevent health service disruptions and to optimize care access.
• Research studies that integrate population genomics data (e.g., TOPMed data) with socioenvironmental data to design precision implementation research for HLBS conditions with proven interventions (e.g., cholesterol reduction, blood pressure reduction, etc.).

• PAIR that integrates omics and condition-specific data with Electronic Health Records (EHR) to predict outcomes and to gather insights on the progression of co-occurring HLBS disorders, such as asthma and obstructive sleep apnea (OSA), hypertension, etc.

• Integration of environmental, behavioral, and social risk information with biomedical risk to create a global risk score for heart, lung, blood, and sleep to support health policies and health system priorities for improvement.
• Research studies that use machine learning techniques, natural language processing techniques, simulation modeling, or predictive modeling to develop and test algorithms for enhancing diagnostic or prognostic yield at the individual- or community-level in complex HLBS conditions.

Note: NHLBI will only accept PAIR clinical trial applications as defined by NIH (NOT-OD-15-015) in response to PAR-19-274 Dissemination and Implementation Research in Health. NHLBI will only accept PAIR applications that are not clinical trials defined by NIH, which are submitted in response to PA-20-185 NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).

Non-clinical trial PAIR applications may focus on methodological development and proof of concept methodologies, including the use of secondary data analyses that do not meet NIH's definition of a clinical trial.

Application and Submission Information

This notice applies to due dates on or after February 5, 2021 and subsequent receipt dates through January 7, 2024.

Submit applications for this NOSI using one of the following funding opportunity announcements (FOAs) or any reissues of these announcement through the expiration date of this notice.

• PAR-19-274 - Dissemination and Implementation Research in Health (R01 Clinical Trial Optional)
• PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed

All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:

• For funding consideration, applicants must include "NOT-HL-20-815" (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.

Applications nonresponsive to terms of this NOSI will not be considered for the NOSI initiative.

Inquiries

Scientific/Research Contact(s)

For Clinical Trial PAIR Applications (that target PAR-19-274 Dissemination and Implementation Research in Health (R01 Clinical Trial Optional))

Keith Mintzer, PhD
Center for Translation Research and Implementation Science
National Heart, Lung and Blood Institute (NHLBI)
Telephone: 301-827-7949
Email:[email protected]

Marishka K. Brown, PhD
Division of Lung Diseases
National Heart, Lung and Blood Institute (NHLBI)
Phone: 301-435-0199
Email: [email protected]

George Papanicolaou, PhD
Division of Cardiovascular Sciences
National Heart, Lung and Blood Institute (NHLBI)
Telephone: 301-435-0453
Email:[email protected]

For Non-Clinical Trial PAIR applications (that target PA-20-185 NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed))

Lucy Hsu, MS
Division of Cardiovascular Sciences
National Heart, Lung and Blood Institute (NHLBI)
Telephone: 301-402-3276
Email:[email protected]

Peer Review Contact(s)

Examine your eRA Commons account for review assignment and contact information (information appears two weeks after the submission due date).

Financial/Grants Management Contact(s)

Anthony Agresti
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0186
Email: [email protected]