iStandardize: Recommendations for Healthcare Form Standardiz

iStandardize is an AI-powered machine learning solution that is designed to streamline the standardization of clinical order sets (i.e., forms) by using machine learning and natural language processing techniques. Currently, hospital networks use multiple versions of forms and order sets, many of them are similar in nature. The lack of standardization poses a challenge in integrating the data for sharing, adds additional documentation burden, and disrupts the workflow for clinicians. The solution applies Natural Language Processing and Machine Learning to identify similar order sets and their elements (attributes and responses), reduce the manual work required to compare the order sets, and expedite the decision making process for standardization.

Faculty Supervisor:

Michael Brudno

Student:

Joseph Roussy

Partner:

Deloitte Consulting

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto