Infer the timing of menopause from electronic health record (EHR) clinical data
Marisa Medina, Professor
UC San Francisco
Open. Apprentices needed for the fall semester. Enter your application online beginning August 21st. The deadline to apply is Monday, August 31st, 4pm.
Electronic health record (EHR)-linked biobanks, such as the All of Us Research Program, do not contain reliable information about the timing of menopause for most women. However, clinical notes can give additional clues about the timing of this important milestone in women's lives. The All of Us Research Program recently released structured health condition data extracted from EHR clinical notes of almost 100K of its participants, and we would like to harness those data, along with related diagnosis code and prescription data, to estimate the timing of menopause in postmenopausal women.
Role: 1) The undergraduate would learn about human subjects research and be trained to protect human subjects before analyzing human subjects data.
2) Under direction of the research supervisor, the undergraduate would curate and analyze data from the All of Us Research Program and other sources, generating descriptive statistics and performing quality control to arrive at a final dataset for analysis.
3) The undergraduate would learn and/or expand their knowledge of electronic health record data.
4) Under direction of the research supervisor, the undergraduate would derive menopause timing estimates for individual women from EHR clinical data and compare across data types.
Qualifications: An interest and some basic experience with statistics and coding would be a good foundation for this project.
A motivated student with a desire to analyze datasets that are relevant to human (women's) health would be ideal.
It would be desirable but not essential for the student to have prior knowledge of natural language processing and/or have proficiency in at least one programming language.
Day-to-day supervisor for this project: Beth Theusch, Staff Researcher
Hours: to be negotiated
Off-Campus Research Site: This is a data analysis project, so project can be conducted completely remotely. The Medina lab is physically located at 5700 Martin Luther King Jr Way in Oakland, but the research supervisor (Beth Theusch) works remotely.
Related website: https://profiles.ucsf.edu/elizabeth.theusch
Related website: https://medinalab.ucsf.edu/