Research Grants in Clinical Informatics (R01 Clinical Trial Optional)

Clinical informatics sits at the intersection of healthcare, information science, and technology, offering critical tools and approaches to improve patient care, advance clinical practice, and inform decision-making. As the healthcare landscape continues to generate vast volumes of complex data, there is a growing need for innovative informatics solutions that can turn data into actionable knowledge. The National Library of Medicine (NLM) supports research that transforms health data into meaningful knowledge to improve health outcomes and enhance decision-making. Specifically, this NOFO aligns with NLM’s commitment to accelerating discovery and advancing health through data-driven research. By supporting clinical informatics research, NLM aims to catalyze the development of scalable, interoperable, and data-driven methods that enable better diagnosis, treatment, and prevention strategies across clinical settings.

NLM’s clinical informatics research portfolio has historically spanned a broad range of topics, including artificial intelligence, clinical decision support, medical language processing, biomedical imaging, and large-scale analysis of clinical data to improve health and drive discovery. Through this work, NLM has funded innovative research that accelerates data-driven discovery, translates findings into clinical solutions, and empowers individuals to better understand and manage their health data. With this new initiative, NLM seeks bold, forward-looking projects in clinical informatics that develop novel, generalizable methods for transforming complex health data into usable knowledge and supporting decision-making. Applications submitted under this announcement should emphasize domain-independent, scalable, and reusable approaches for the discovery, analysis, organization, and management of health-related data and digital objects.

The overarching goal of this initiative is to advance the development of innovative informatics solutions that enable both healthcare providers and individuals to better understand and improve overall health. 

Research questions and topics of interest under this program are envisioned to include but are not limited to:

• Tools to assess information and knowledge needs of health care professionals and patients.
• Building & leveraging next-gen CDSS (Clinical Decision Support Systems), comprehensive patient-centric digital tools that promote precision medicine.
• Research on EHR usability, interoperability, and tools to streamline clinical documentation while reducing clinician burden and improving patient care.
• Predictive analytics for proactive care/preventative care - including models that identify at-risk patients and in real time to recommend timely interventions.
• Transformative methods in data integration - research topics that include innovation approaches to harmonizing diverse data streams and exploring advanced techniques that can be implemented in a practical manner.
• AI tools and methods with a focus on benefits to patients and health systems/workflow, patient satisfaction, costs, operational efficiency.
• Research to improve quality and outcomes of patient care, for example, for enabling clinicians to monitor patients' conditions for changes or detect undiagnosed diseases earlier.
• Automate administrative processes and reduce workforce burden and burnout.

Research Objectives

Research approaches should foster data-driven discovery to accomplish NLM mission-related goals. Additionally, the following expectations should be addressed in all applications:

• Research should exemplify scientific rigor, feasibility, technological innovation, and the potential for significant impact across biomedical and clinical domains.
• Outputs should be transformative and generalizable across diseases and biological systems; use of specific biological systems may be permissible for proof-of-concept and initial methodology development, but applicants must demonstrate broad applicability beyond that.
• Products should be durable with the potential to inform and advance further research.
• Intended use cases must be clearly stated and evaluated, with approaches expected to be wide-reaching.
• Detailed descriptions of approaches are expected, with metrics provided for the scope and scale of the study.
• Improvements over comparable existing approaches must be documented, and any limitations, trade-offs or risks resulting from the proposed innovative approach must be described and addressed.
• Applicants must describe a plan to account for accuracy of the product(s), to maintain the product(s), and to capture and communicate considerations for downstream use.
• All awardees are expected to widely disseminate the results of their research, including software products, datasets, resources and platforms.
• For applications that incorporate the aggregation of public or non-controlled-access data, applicants are expected to address methods for mitigating privacy concerns that may arise from such aggregated data. Privacy protections for human subjects are expected to be long-term and must extend beyond the funding period.

Applications Not Responsive to this NOFO

The following types of projects will be considered non-responsive to the scope of NLM’s Research Grants in Clinical Informatics program:

• Projects that do not align with current NIH or Department of Health and Human Services priorities, including projects that partially incorporate non-aligning activities.
• Projects not centrally focused on, or not clearly pertaining to, clinical informatics.
• Projects focused on social determinants of health (SDOH), or ethical, legal and social issues (ELSI).
• Projects that duplicate NLM products and databases.
• Projects that do not produce open-access datasets, methods, resources or tools.
• Projects focused on mere incremental improvements of, or on the maintenance of, existing tools, resources or platforms; significant innovation and advancement is expected from this initiative.
• Projects with most of the effort devoted to experimental research; only a small portion of the budget may be permitted for experimental validation of computational approaches.
• Projects narrowly focused on specific diseases and with limited potential to yield broadly applicable tools.

Non-responsive applications will not be reviewed. Potential applicants are strongly encouraged to discuss their proposed project with the Scientific/Research Contacts listed in Section VII for guidance about the application process and suitability of the project for support by NLM.

Investigators proposing NIH-defined clinical trials may refer to the Research Methods Resources website for information about developing statistical methods and study designs.