Clinical Informatics and Data Science Pathway

The GME Pathways program is excited to launch the new Clinical Informatics and Data Science Pathway in January 2022!

 


The Clinical Informatics and Data Science (CI-DS) Pathway is an introduction to the fields of Clinical Informatics and Data Science. It is intended as an opportunity for learners to learn basic concepts, principals, and skills in these fields, as well as act as a resource to help them consider and pursue careers in these areas.

Learning will be done through a mix of didactics, self-paced exercises, regular group sessions, and participation in real life informatics/data science experiences.  At the end of the course, learners should come away with a basic understanding of the fields of Clinical Informatics and Data Science, and have practiced some basic data science related skills.  The course is also a great way to meet and interact with local informatics faculty, who can potentially provide additional long-term mentorship and project work.

Clinical Informatics and Data Science Objectives
  • Learn the key vocabulary, principles, and history of Clinical Informatics
  • Understand the breadth of clinical informatics
  • Explore the basic literature of the clinical informatics field
  • Learn basic data science vocabulary and principles
  • Develop basic data science skills
  • Understand possible careers in informatics
Curriculum Overview

The CI-DS pathway will have two integral components. The pathway will launch with a one week seminar, which will be followed by a longitudinal curriculum. 

The one week seminar is open to all GME trainees and fourth year medical students. We will hold the first iteration of this course during January, 2022. The course will be a mixture of lectures, workshops, and panels. There will be various sessions focused on various areas of CI-DS and the planned didactics will be as follows:

  • Two days will be focused on Clinical Informatics
  • One day will focus on Data Science 
  • One day on artificial intelligence/machine learning
  • One day on career opportunities in informatics

The longitudinal curriculum will have limited seating and learners are expected to complete 20-40 hours of coursework over the year. There will be some required activities that can be done in your free time.  In addition, the learner has to obtain a certain number of “points” in order to obtain the certificate. Points can be obtained through a variety of activities that the learner can choose from (e.g. local, regional, national informatics webinars/lectures, attending monthly check-ins, UCSF informatics meetings, taking data science courses, going to conferences, interviewing faculty members, etc).

Some highlights of the longitudinal component:

  • Obtain access to the UCSF de-identified data warehouse
  • Do standard queries in the database to learn SQL and important data science concepts
  • Obtain access to the Information Commons cloud computing platform
  • Follow instructions to run a standardized machine learning model in the Information Commons
  • Learners are required to have a question they want to explore/answer using data when they start, and should at least try to answer that question after they have done the structured SQL exercises. It is encouraged for them to complete an academic product (e.g. abstract, paper, etc), but not required. 
  • For the highly motivated, we will try to help link them with faculty mentors to take on additional work/projects per interest and fit.