​Biomedical Informatics and Data Science

Graduate Student Coordinator:  K​atie Bay​

Faculty Director:  Philip Payne, Ph.D., FACMI

 ​GRE is not required for this program

​BIDS.png​The Biomedical Informatics and Data Science (BIDS) PhD program will provide opportunities for graduate students with diverse backgrounds to gain expertise in the field of biomedical informatics and data science, to train as future biomedical researchers and industry leaders in biomedical informatics and data science core competencies, and to engage in scholarly activities under the guidance of experienced informatics faculty. Beyond an educational program, the mission of BIDS is to support biomedical informatics and data science practice through applied research in real-world settings. The objectives of BIDS are to: 

  • Expand students’ knowledge in data science theories and applications in biomedical informatics;
  • Provide training and hands-on research and industry experience in biomedical informatics and data science;
  • Assist students in enhancing and applying their skills in translational science, real-world problem solving, and dissemination of knowledge;
  • Encourage students to pursue careers in academia and/or industry through exposure to professional role models or mentors; and
  • Develop and improve students’ skills in interdisciplinary teamwork and communication. 

The BIDS program spans the fields of Data Science and Biomedical Informatics- which we define as follows (Payne PR, Bernstam EV, Starren JB. Biomedical informatics meets data science: current state and future directions for interaction. Jamia Open. 2018 Oct;1(2):136-41.):

  • Biomedical Data Science is the study of the generalizable extraction of knowledge from biomedical data; and
  • Biomedical Informatics is the science of information applied to or studied in the context of biomedicine. 
BIDS Fig1.png 

Figure 1: Overview of an integrated biomedical data, information, and knowledge lifecycle, showing the contributions of theories and methods associated with Big Data, Biomedical Data Science, and Biomedical Informatics (BMI). For each phase of the model, exemplary contributions to such theory and practice as have been generated by the BMI community over the last several decades are shown.

Throughout their training, learners will interact with patients, providers, and the healthcare data ecosystem in addition to working at the bench. The BIDS program will promote interdisciplinary collaboration in solving problems in clinical practice, individual and population health, data science, and biomedical research, through the optimal use of information. The training opportunities will include the five areas as defined by the American Medical Informatics Association (AMIA), the largest professional scientific community in the field of biomedical informatics: 1) Applied Clinical Informatics; 2) Consumer Health Informatics; 3) Clinical Research Informatics; 4) Translational Bioinformatics; and 5) Population Health Informatics:

Applied Clinical Informatics (ACI) focuses on supporting and elevating clinical informatics practice through research translation, which is essential to fill the gaps between practice and research. ACI involves the application of innovative measurement and informatics approaches to inform and improve clinical practice.

Consumer Health Informatics (CHI) involves views from consumers or patients and focuses on information structures and processes to empower individual’s management of their own health. CHI investigates consumers' needs and integrates consumers' preferences into health information systems.

Clinical Research Informatics (CRI) involves the use of informatics in the discovery and management of new knowledge relating to health and disease. Specifically, CRI manages information related to clinical trials as well as secondary use of clinical data.

Translational Bioinformatics (TBI) is the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data into proactive, predictive, preventative, and participatory health.

Population Health Informatics (PopHI) integrates aspects of public health, clinical informatics, and health care delivery with the target of improving health care system effectiveness and the well-being of communities and populations.

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