Predicting the target specialty of referral notes to estimate per-specialty wait times with machine learning.

ABSTRACT:

Background

Currently, in Canada, existing health administrative data and hospital-inputted portal systems are used to measure the wait times to receiving a procedure or therapy after a specialist visit. However, due to missing and inconsistent labelling, estimating the wait time prior to seeing a specialist physician requires costly manual coding to label primary care referral notes.

Methods

In this work, we represent the notes using word-count vectors and develop a logistic regression machine learning model to automatically label the target specialist physician from a primary care referral note. These labels are not available in the administrative system. We also study the effects of note length (measured in number of tokens) and dataset size (measured in number of notes pe

SUBMITTER: Abdalla M 

PROVIDER: S-EPMC9098074 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature