Evaluating predictive modeling's potential to improve teleretinal screening participation in urban safety net clinics.
BACKGROUND
Screening guidelines for diabetic patients recommend yearly eye examinations to detect diabetic retinopathy and other forms of diabetic eye disease. However, annual screening rates for retinopathy in US urban safety net settings remain low.


METHODS
Using data gathered from a study of teleretinal screening in six urban safety net clinics, we assessed whether predictive modeling could be of value in identifying patients at risk of developing retinopathy. We developed and examined the accuracy of two predictive modeling approaches for diabetic retinopathy in a sample of 513 diabetic individuals, using routinely available clinical variables from retrospective medical record reviews. Bayesian networks and radial basis function (neural) networks were learned using ten-fold cross-validation.


RESULTS
The predictive models were modestly predictive with the best model having an AUC of 0.71.


CONCLUSIONS
Using routinely available clinical variables to predict patients at risk of developing retinopathy and to target them for annual eye screenings may be of some usefulness to safety net clinics.
Center for Biomedical Informatics.
Omolola
O
Ogunyemi
Senait
S
Teklehaimanot
Lauren
L
Patty
Erin
E
Moran
Sheba
S
George
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001499:Bayes Theorem; D003930:Diabetic Retinopathy / Q000175:diagnosis* / Q000453:epidemiology*; D005260:Female; D006801:Humans; D015141:Los Angeles / Q000453:epidemiology; D008297:Male; D008403:Mass Screening / Q000706:statistics & numerical data*; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015995:Prevalence; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D064876:Safety-net Providers / Q000706:statistics & numerical data*; D012680:Sensitivity and Specificity; D017216:Telemedicine / Q000706:statistics & numerical data*; D014505:Urban Population / Q000706:statistics & numerical data; D055815:Young Adult