Health care professionals cannot examine every person calling the office with a question nor can they return every call. Therefore, medical offices seeking to improve the speed and efficiency of evaluating and triaging patients must utilize telephone personnel who are often non-clinical staff. These telephone triage personnel may be limited in their knowledge and ability to obtain the necessary details of the patient’s medical symptoms and direct medical care accordingly. Their role is not to make diagnoses by phone, but rather to collect sufficient data related to the patient’s complaints and assign them appropriately in order to get the patient to the right level of care with the right provider in the right place at the right time.

Data science has been applied to many aspects of medicine, and the use of NLP in telephone triage is a novel concept. Our objective is to analyze the verbal exchange between non-clinical triage staff and patients who are calling with symptoms limited to one organ system, namely the eye. We hypothesize that NLP may provide insight into correlating patient’s descriptive symptoms with clinical urgency, diagnoses and outcomes as determined by health care providers in the Department of Ophthalmology.

This is an UNPAID research project.

Faculty Advisor

  • Professor: Kriste Krstovski and Lisa Park
  • Department/School: DSI and CUMC
  • Location: DSI, Robert Burch Family Eye Center
  • Kriste Krstovski is an associate research scientist at DSI and an adjunct faculty at CBS. Lisa Park is an associate professor of ophthalmology at Columbia University Medical Center and an attending ophthalmologist at New York-Presbyterian hospital.

Project Timeline

  • Earliest starting date: 1/15/2021
  • End date: 6/15/2021
  • Number of hours per week of research expected during Spring 2021: ~8
  • Number of hours per week of research expected during Summer 2021: ~20

Candidate requirements

  • Skill sets: Python, NLP, and machine learning
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes