Sam Magid ’25

University of California, San Francisco, Global Action in Nursing, San Francisco, CA

Global Action in Nursing (GAIN), founded in 2017 at the University of California, San Francisco, has one primary goal: to decrease maternal and newborn deaths across Liberia, Malawi and Sierra Leone—three countries facing high birth-related mortalities and a shortage of licensed nurses and midwives. GAIN, in collaboration with local educational institutions, provides comprehensive training programs to nurses and midwives, along with longitudinal post-training mentorship to reinforce clinicians’ education and provide necessary support.

Sam Magid with mentor Dr. Alden Blair.Alongside my mentor Dr. Alden Blair, I spent the summer looking into the effectiveness of GAIN in Malawi. The impact of a program like GAIN can be observed in several ways: qualitative analysis of nurse/midwife experiences; qualitative analysis of patient outcomes; or quantitative analysis of patient outcomes. In the past five years of GAIN’s operation, my coworkers performed various analyses of the program’s outcomes, but one aspect has proven especially difficult: data accessibility. Across Malawian birth facilities, healthcare professionals lack necessary support and vital medical resources, so in most cases nurses lack time to diligently enter birth records into computer databases. This leads to unreliable data.

Before we could perform any analysis, much of my data-analytic project required critical decision-making about how to handle our data. Our data—month-by-month sums of birth outcomes stratified across nine clinics of interest—came from a governmental database compiled by the Malawian Department of Health. Because the data underwent multiple levels of summation and manipulation between the birth facilities and our computers, I spent much of my time cleaning the dataset. I learned to program with conditional formatting in Excel, and along with the statistical programming language R, I worked to highlight outliers based on a 95% confidence interval, then determined whether each individual outlier should remain or not. I additionally took notes of each choice to ensure the reproducibility of our eventual findings. After that process, I combined this patient-outcome dataset with another dataset tracking GAIN mentorship hours. The next step in our project, which we are just now starting, is to apply high-level statistical analyses to this dataset in order to test for a correlation between GAIN mentorship hours and patient outcomes. In other words: does GAIN mentorship have a positive effect on maternal and newborn health?

Interning with GAIN provided me with a critical perspective on my career path and academic interests. Although I do not intend to pursue research professionally, working alongside so many nurses and other healthcare professionals opened my eyes to the vast field of medicine and global health. In my professional future I’d like to help others as directly as possible as well as explore the diversity of cultures and communities around the world, and I think a career in medicine would achieve both goals.

I would like to thank my mentor Dr. Alden Blair, all of my coworkers at GAIN, the ’68 Center for Career Exploration, and the Class of 1974 for this experience. I am deeply grateful for this enjoyable, enlightening opportunity.