Business

Anita Carson

Professor, Operations & Technology Management

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Volunteer Basis, Independent Funding Available, Potential for UROP Funding

Overview

RA Position – Healthcare empirical/qualitative oriented

Have you ever seen a generative AI-powered tool (e.g., ChatGPT) produce an obvious or surprising error? As AI-powered tools rapidly expand across industries, especially in healthcare. Understanding why these errors occur and their impact on real-world work is becoming increasingly important.
We are seeking a highly motivated and detail-oriented undergraduate student to join an interdisciplinary research project at the intersection of healthcare operations and artificial intelligence. Through this project, students will gain firsthand exposure to one of the fastest-growing areas in healthcare technology and business analytics. The role is especially valuable for students interested in business, healthcare, medical technology, artificial intelligence, or future graduate studies.

About the project:
Our research investigates how physicians adopt AI-powered documentation tools and how these tools impact workflow efficiency, documentation quality, and patient safety. The project includes analyzing a real dataset on physician–patient consultation transcripts. A key component of the work is helping to build a rigorous framework for understanding errors generated by AI-powered medical documentation systems.

Learning & Professional Development Opportunities:
● Work closely with a supportive research team at the Questrom School of Business
● Build practical skills in qualitative coding, empirical research, and healthcare operations management
● Develop a deeper understanding of a rapidly evolving topic—how AI shapes and impacts people’s daily workflow, especially in clinical settings
● Gain meaningful research experience that strengthens pathways to careers in consulting, data science, healthcare analytics, medical technology, and academia

Preferred Qualifications:
Students from Business, Public Health, Psychology, Medical Technology, or related fields are encouraged to apply. The ideal candidate will have:
● Strong attention to detail and organizational skills
● Ability to conduct qualitative coding using software such as NVivo (training provided)
● Strong curiosity, critical thinking, and willingness to learn new research methods
● Ability to work independently and reliably meet deadlines
● Strong writing and communication skills

Time Commitment:
● 5 hours per week, flexible scheduling
● At least one semester commitment, with the option to continue into the summer or the next academic year
● Potentially paid position (rate aligned with BU undergraduate research assistant pay)

How to Apply:
Please send the following to Ruozhu Wang (ruozhuw@bu.edu) with the subject line “Undergraduate Research Assistant Application – [Your Name]”:
1. A brief cover letter about your interest in the project
2. Your résumé