Improving efficiency of a rheumatology outpatient clinic through classification of newly referred patients.

ABSTRACT:

Objectives

Diagnosing a rheumatological disease in patients newly referred by their general practitioner requires assessment by a rheumatologist and often diagnostic tests. Ideally, these tests are performed prior to the patient's first consultation with the rheumatologist, aiming for quick diagnosis and fewer visits. We retrospectively studied whether a pre-first visit digital patient questionnaire can lead to fewer consultations and faster diagnosis.

Methods

We applied machine learning-based binary classification algorithms to questionnaire data of newly referred patients to classify a patient's diagnostic class (inflammatory vs. non-inflammatory). Afterwards, we quantified the rheumatology clinic's benefit when all patients classified to be non-inflammatory are planned fo

SUBMITTER: Dijkstra S 

PROVIDER: S-EPMC12007594 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature