Cornea
Development and Validation of a Model to Predict Anterior Segment Vision-Threatening Eye Disease Using Primary Care Clinical Notes
The purpose of this study was to develop a decision-support tool to predict anterior segment vision-threatening disease (asVTD) to aid primary care physicians (PCPs) with patient triage and referral.
Methods:
The University of Michigan electronic health record data between January 1, 2016, and May 31, 2019, were obtained from patients presenting to a PCP with anterior eye symptoms and then saw an ophthalmologist within 30 days. asVTD included diagnosis of corneal ulcer, iridocyclitis, hyphema, anterior scleritis, or scleritis with corneal involvement by an ophthalmologist. Elastic net logistic regression with 10-fold cross-validation was used for prediction modeling of asVTD. Predictors evaluated included patient demographics and PCP notes processed using clinical natural language processing software (clinspacy).
Results:
Two thousand nine hundred forty-two patients met the inclusion criteria, of which 133 patients (4.5%) had asVTD. The age was significantly lower among those with asVTD versus those without (median = 42 vs. 53 yrs, P