Identifying patterns in administrative tasks through structural topic modeling: A study of task definitions, prevalence, and shifts in a mental health practice's operations during the COVID-19 pandemic.
This case study illustrates the use of natural language processing for identifying administrative task categories, prevalence, and shifts necessitated by a major event (the COVID-19 [coronavirus disease 2019] pandemic) from user-generated data stored as free text in a task management system for a multisite mental health practice with 40 clinicians and 13 administrative staff members.
Author(s): Pachamanova, Dessislava, Glover, Wiljeana, Li, Zhi, Docktor, Michael, Gujral, Nitin
DOI: 10.1093/jamia/ocab185