Institute for Precision Health Pilot Study Awards

About

We are pleased to announce a call for pilot project proposals by the Institute for Precision Health (IPH) in partnership with the School of Medicine, UCI Health, and the UCI Office of Research. One-year awards in the amount of up to $75,000 will be conferred in this round.  The target start date for awards will be March 1, 2024.

The Institute for Precision Health (IPH) at UCI was initiated in 2021 to position UCI as a leading center of informatics and data science expertise to advance personalized health through discovery, implementation, and outreach. A goal of IPH is to foster synergies that occur from integrating research, clinical and phenotypic data to achieve major advances in patient-specific care.

The IPH Pilot Awards are designed specifically to support multidisciplinary research projects. The ideal project will leverage the resources of IPH and include partnerships of health scientists, translational researchers, and computational scientists across UCI. Projects should address clinical and research needs using data, machine learning, artificial intelligence, and/or statistics. Projects using Real-World Data and Evidence will be viewed favorably. Real-world data are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Examples of RWD include data derived from electronic health records, medical claims data, data from product or disease registries, and data gathered from other sources (such as digital health technologies) that can inform on health status. 

Real-world evidence is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.

Proposed precision health research projects should be multi-disciplinary and identify and fill knowledge and practice gaps in health data theory and analytics. We particularly encourage projects that employ novel approaches to health data to address health disparities and inequities. We will consider a wide range of projects from basic research (animal studies excluded) to quality improvement, and each of the projects should explain how the project outcomes may add immediate or long-term value for clinical outcomes. Both the creation of new data (e.g. omics) and use of existing data (e.g. health data) are allowed.  

Access to data can be obtained through IPH’s E2E unit or other relevant data infrastructure and platforms of IPH. Syntropy, a unified platform for curated health data recently implemented at UCI, may be utilized. Multidisciplinary teams must include faculty from at least two different academic units or UCI partner organizations (i.e., CHOC, VA) with a concrete plan to develop a research team, preliminary data, and a plan for a future extramural funding opportunity (or, if it is a quality improvement project, plans for revenue generation/cost reduction). 

infographic showing IPH components

The structure and focused themes of the Institute are represented in the figure above. More information about each resource will be provided during the mandatory workshop on Oct. 19.

  1. Statistics, ML, and AI Research Technologies (SMART). Leverage UCI’s world class leadership in Statistics and ML/AI technology development to create methodologic solutions to the unique problems posed by the integration of EHR and observational data.
  2. Applied Artificial Intelligence Research (A2IR). Research focused on the application and development of ML/AI-enabled solutions to specific clinical healthcare problems. Leverages Center for Artificial Intelligence in Diagnostic Medicine (CAIDM).
  3. Applied Advanced analytics & Artificial Intelligence (A3). Operationalize, validate, and integrate developing IPH solutions driven by analytics and AI into healthcare settings, including inpatient, ambulatory, and community settings.
  4. Precision Omics. Leverage emerging data-intensive omics technologies at the Genomics High Throughput Facility to provide for expanded omics and bioinformatics research development, as well as expanded systems administration for genomic data sharing and analysis.
  5. E2E (End-to-End). Sitting at the intersection of clinical decisions, healthcare operations, and health data research, E2E supports the enterprise by providing access to critical health data assets.   The core mission of E2E is to provide the infrastructure and architecture to provision and manage health data assets as well as partner with clinicians, researchers, operational leaders, and external partners to drive the next generation of analytics insights. This unit can utilize the Syntropy platform.
  6. UCI Collaboratory for Health & Wellness. A data and analytics platform that is designed to create an ecosystem around data common research area to support rich human interaction, foster collaboration, and provide access to dynamic data sources, artifacts, and tools required to accomplish advanced analytical tasks. This activity is powered by Syntropy.
  7. Health Equity. Brings ML/AI into communities to create solutions to narrow disparities gap in the health and wellbeing of vulnerable populations.
Criteria & Application