Clostridioides difficile infection (CDI) is highly associated with antibiotic exposure, but it is uncertain which classes of antibiotics confer the greatest risk for CDI. This project will use the MarketScan database, a large commercial insurance billing database containing 40 million patient records, outpatient antibiotic prescription data, and ICD-based disease information, to test for associations between specific antibiotic classes and risk for CDI.

This project is eligible for a matching fund stipend from the Data Science Institute. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Daniel Freedberg
  • Center/Lab: Freedberg (me)
  • Location: P&S 3-401
  • I am a gastroenterologist and a clinical-translational researcher focused on the role of the gut microbiome in enteric and systemic infections. Relevant for this project, I am interested in the pharmacoepidemiology of enteric infections such as Clostridioides difficile infection (CDI). Past pharmacoepidemiology projects related to CDI have included studies of proton pump inhibitors (anti-acid medications), antibiotics, and immunosuppressants.

Project Timeline

  • Earliest starting date: 9/6/21
  • End date: 9/9/22
  • Number of hours per week of research expected during Fall 2021: ~5
  • Number of hours per week of research expected during Summer 2021: ~5

Candidate requirements

  • Skill sets: statistical knowledge and/or training, prior experience in healthcare outcomes research, some minimum coding skills; the student will access the data through an online portal using an ID code that we will provide
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes
  • Additional comments: they will need access to a computer