University of Southern California

Research

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:                          Contact the Office of Research if interested.

LOI:                                                        December 17, 2019         

External Deadline:                          January 17, 2020, 5pm PT

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://app.wizehive.com/webform/USCgrants

Materials to submit:

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.

Purpose:

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.

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 MedlinePlusGenetics Home ReferencePUBMED 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:

Potential applicants are urged to discuss their proposed project with the Research Contact listed in Section VII Agency Contacts, for advice about the suitability of their idea for this funding initiative.Visit our Institutionally Limited Submission webpage for updates and other announcements.