PAR-19-072: Data Science Research: Personal Health Libraries for Consumers and Patients (R01 Clinical Trial Optional)
Slots: Only one application per institution (normally identified by having a unique DUNS number or NIH IPF number) is allowed.
Internal Deadline: October 16, 2020, noon PT
LOI: December 18, 2020
External Deadline: January 19, 2021
Award Information: Type: Grant
Estimated Number of Awards: The number of awards is contingent upon NIH appropriations and the submission of a sufficient number of meritorious applications.
Anticipated Amount: Up to $250,000 direct costs may be requested in any single year.
Submission Process: PIs must submit their application as a Limited Submission through the Office of Research Application Portal: https://research.usc.edu/usc-grants/
Materials to submit:
- Single Page Proposal Summary (0.5” margins; single-spaced; font type: Arial, Helvetica, or Georgia typeface; font size: 11 pt). Page limit includes references and illustrations. Pages that exceed the 1-page limit will be excluded from review.
- CV – (5 pages maximum)
Link to Award: https://grants.nih.gov/grants/guide/pa-files/PAR-19-072.html
Who May Serve as PI: Any individual(s) with the skills, knowledge, and resources necessary to carry out the proposed research as the Program Director(s)/Principal Investigator(s) (PD(s)/PI(s)) is invited to work with his/her organization to develop an application for support. Individuals from underrepresented racial and ethnic groups as well as individuals with disabilities are always encouraged to apply for NIH support.
The National Library of Medicine seeks applications for novel informatics and data science approaches that can help individuals gather, manage and use data and information about their personal health. A goal of this program is to advance research and application by patients and the research community through broadly sharing the results via publication, and through open source mechanisms for data or resource sharing.
To bring the benefits of big data research to consumers and patients, new biomedical informatics and data science approaches are needed, shaped to meet the needs of consumers and patients, whose health literacy, language skills, technical sophistication, education and cultural traditions affect how they find, understand and use personal health information. Novel data science approaches are needed to help individuals at every step, from harvesting to storing to using data and information in a personal health library. Areas of development suggested below are not meant to limit the scope or creativity of proposed projects.
- Constructing a personal health library: informatics approaches that help a person gather different types of health data/information/knowledge into a single, searchable resource for personal use, including intelligent mapping tools for vocabulary used to describe elements of the library.
- Managing a personal health information library: novel informatics approaches that make it easy for an average user to expand or remove entries, make notes or corrections, including intelligent tools that alert the user to new information about topics covered in a personal health information library.
- Using a personal health library: data science and informatics approaches that make it easy to find and use the information, including visual tagging, text summarization, graphics translation, knowledge mapping, suggestions for tutorials, analytic and visualization techniques that make the information understandable based on characteristics of the individual user or group.
- Digital librarian/assistant for personal health library: data science and informatics approaches that bring machine intelligence to the management and use of a personal health information library through personalized alerts and suggestions, literacy aids, translators or other approaches, taking into account characteristics of the individual user or group.
Applicants must base their proposed work on an informed profile of the intended users, and, the work should be developed through interaction with the intended users. The strongest projects will provide approaches that incorporate health data and information from more than one source, such as diagnostic images and links to full-text articles or genome sequence data linked to a family health history. An application should be centered on the problem area being addressed and the intended audience, propose a possible solution that employs novel data science or informatics, and undertake a pilot that will result in evidence of the degree of success and/or needed next steps.
Applicants may propose new tools or extensions to the capabilities of existing open source tools such as personal health record systems, by adding new features or extending capabilities of the tool. In either case, scientific innovation is key. Applicants are encouraged to take advantage of freely available public information resources available from NLM and others, such as MedlinePlus, Genetics Home Reference, PUBMED Central, online courses and tutorials.
Applicants should plan to undertake one or more pilots to test their ideas with the intended user group. If pilots focus on a single disease or health condition, applicants should provide assurance that their approach is generalizable to others. Awardees are expected to share the results of their work through publication, and through open source mechanisms for data or resource sharing.
Projects that propose the following outcomes would not be appropriate for this FOA:
- A tool that requires the user to purchase a commercial off-the-shelf product.
- An information resource that requires payment for access to information.
- A tool that supports management of only a single kind of health data or information.
- An approach that does not allow the user to expand or update the contents.
- An approach that doesn’t allow the user to update, annotate or add/delete data.
- An approach that limits the user’s ability to share information from her/his personal health library with another person or organization.
Budgetary Requirements: This FOA does not require cost sharing as defined in the NIH Grants Policy Statement.
Visit our Institutionally Limited Submission webpage for updates and other announcements.