Development and Validation of Claims-Based Algorithms for Conjunctivitis and Keratitis

Background: Ocular surface disorders have been reported among patients with various medical conditions, including atopic dermatitis (AD). Nonetheless, validated algorithms to identify conjunctivitis and keratitis in claims data are lacking.

Objective: Develop validated, claims-based algorithms for conjunctivitis and keratitis among patients with AD using medical records.

Methods: Patients with AD were identified in a claims database between March 2017 and November 2019. Among these patients, candidate algorithms were developed that included diagnosis codes for conjunctivitis or keratitis, alone and in combination with ophthalmic treatments. Among patients who met ≥ 1 candidate algorithms, a subset was randomly selected for medical record review. Additionally, records from a random sample of patients with AD were reviewed to assess sensitivity. Overall, 341 records were sought and 262 adjudicated by an expert ophthalmologist. The positive predictive value (PPV) of each algorithm was calculated and compared to a pre-specified threshold of ≥ 70%.

Results: For conjunctivitis, the final algorithm was ≥ 1 conjunctivitis diagnosis (PPV = 81%, 95% confidence interval [CI]: 73%-87%). For keratitis, the final algorithm combined the following 2 candidate algorithms: ≥ 1 keratitis diagnosis and ≥ 1 dispensing of a topical antibiotic or antibiotic-steroid combination (PPV = 91%); and ≥ 1 keratitis diagnosis and ≥ 1 dispensing of an ophthalmic corticosteroid, topical immune-modulator, or topical NSAID (PPV = 68%) for an overall PPV of 80% (95% CI: 55%-93%).

Conclusion: The first claims-based algorithms to identify conjunctivitis and keratitis among AD patients were developed and validated. They are available for use in future studies, particularly to better understand conjunctivitis and keratitis occurrence among patients with AD.