Validity of Administrative Claims and Electronic Health Registry Data From a Single Practice for Eye Health Surveillance.

IMPORTANCE

Diagnostic information from administrative claims and electronic health record (EHR) data may serve as an important resource for surveillance of vision and eye health, but the accuracy and validity of these sources are unknown.

OBJECTIVE

To estimate the accuracy of diagnosis codes in administrative claims and EHRs compared to retrospective medical record review. DESIGN, SETTING,

AND PARTICIPANTS

This cross-sectional study compared the presence and prevalence of eye disorders based on diagnostic codes in EHR and claims records vs clinical medical record review at University of Washington-affiliated ophthalmology or optometry clinics from May 2018 to April 2020. Patients 16 years and older with an eye examination in the previous 2 years were included, oversampled for diagnosed major eye diseases and visual acuity loss.

EXPOSURES

Patients were assigned to vision and eye health condition categories based on diagnosis codes present in their billing claims history and EHR using the diagnostic case definitions of the US Centers for Disease Control and Prevention Vision and Eye Health Surveillance System (VEHSS) as well as clinical assessment based on retrospective medical record review.

MAIN OUTCOME AND MEASURES

Accuracy was measured as area under the receiver operating characteristic curve (AUC) of claims and EHR-based diagnostic coding vs retrospective review of clinical assessments and treatment plans.

RESULTS

Among 669 participants (mean [range] age, 66.1 [16-99] years; 357 [53.4%] female), identification of diseases in billing claims and EHR data using VEHSS case definitions was accurate for diabetic retinopathy (claims AUC, 0.94; 95% CI, 0.91-0.98; EHR AUC, 0.97; 95% CI, 0.95-0.99), glaucoma (claims AUC, 0.90; 95% CI, 0.88-0.93; EHR AUC, 0.93; 95% CI, 0.90-0.95), age-related macular degeneration (claims AUC, 0.87; 95% CI, 0.83-0.92; EHR AUC, 0.96; 95% CI, 0.94-0.98), and cataracts (claims AUC, 0.82; 95% CI, 0.79-0.86; EHR AUC, 0.91; 95% CI, 0.89-0.93). However, several condition categories showed low validity with AUCs below 0.7, including diagnosed disorders of refraction and accommodation (claims AUC, 0.54; 95% CI, 0.49-0.60; EHR AUC, 0.61; 95% CI, 0.56-0.67), diagnosed blindness and low vision (claims AUC, 0.56; 95% CI, 0.53-0.58; EHR AUC, 0.57; 95% CI, 0.54-0.59), and orbital and external diseases (claims AUC, 0.63; 95% CI, 0.57-0.69; EHR AUC, 0.65; 95% CI, 0.59-0.70).

CONCLUSION AND RELEVANCE

In this cross-sectional study of current and recent ophthalmology patients with high rates of eye disorders and vision loss, identification of major vision-threatening eye disorders based on diagnosis codes in claims and EHR records was accurate. However, vision loss, refractive error, and other broadly defined or lower-risk disorder categories were less accurately identified by diagnosis codes in claims and EHR data.