Accuracy of International Classification of Diseases Codes for Identifying Acute Optic Neuritis

Validity of Administrative Coding for Nonarteritic Ischemic Optic Neuropathy

BACKGROUND

Administrative claims have been used to study the incidence and outcomes of nonarteritic ischemic optic neuropathy (NAION), but the validity of International Classification of Diseases (ICD)-10 codes for identifying NAION has not been examined.

METHODS

We identified patients at 3 academic centers who received ≥1 ICD-10 code for NAION in 2018. We abstracted the final diagnosis from clinical documentation and recorded the number of visits with an NAION diagnosis code. We calculated positive predictive value (PPV) for the overall sample and stratified by subspecialty and the number of diagnosis codes. For patients with ophthalmology or neuro-ophthalmology visit data, we recorded presenting symptoms, examination findings, and laboratory data and calculated PPV relative to case definitions of NAION that incorporated sudden onset of symptoms, optic disc edema, afferent pupillary defect, and other characteristics.

RESULTS

Among 161 patients, PPV for ≥1 ICD-10 code was 74.5% (95% CI: 67.2%-80.7%). PPV was similar when restricted to patients who had visited an ophthalmologist (75.8%, 95% CI: 68.4%-82.0%) but increased to 86.8% when restricted to those who had visited neuro-ophthalmologists (95% CI: 79.2%-91.9%). Of 113 patients with >1 ICD-10 code and complete examination data, 37 (32.7%) had documented sudden onset, optic disc swelling, and an afferent pupillary defect (95% CI: 24.7%-42.0%). Of the 76 patients who did not meet these criteria, 54 (71.0%) still received a final clinical diagnosis of NAION; for most (41/54, 75.9%), this discrepancy was due to lack of documented optic disc edema.

CONCLUSIONS

The validity of ICD-10 codes for NAION in administrative claims data is high, particularly when combined with provider specialty.

From real world data to real world evidence to improve outcomes in neuro-ophthalmology

Real-world data (RWD) can be defined as all data generated during routine clinical care. This includes electronic health records, disease-specific registries, imaging databanks, and data linkage to administrative databases. In the field of neuro-ophthalmology, the intersection of RWD and clinical practice offers unprecedented opportunities to understand and treat rare diseases. However, translating RWD into real-world evidence (RWE) poses several challenges, including data quality, legal and ethical considerations, and sustainability of data sources. This review explores existing RWD sources in neuro-ophthalmology, such as patient registries and electronic health records, and discusses the challenges of data collection and standardisation. We focus on research questions that need to be answered in neuro-ophthalmology and provide an update on RWE generated from various RWD sources. We review and propose solutions to some of the key barriers that can limit translation of a collection of data into impactful clinical evidence. Careful data selection, management, analysis, and interpretation are critical to generate meaningful conclusions.

Risk of Nonarteritic Anterior Ischemic Optic Neuropathy in Patients Prescribed Semaglutide

Importance

Anecdotal experience raised the possibility that semaglutide, a glucagon-like peptide 1 receptor agonist (GLP-1 RA) with rapidly increasing use, is associated with nonarteritic anterior ischemic optic neuropathy (NAION).

Objective

To investigate whether there is an association between semaglutide and risk of NAION.

Design, Setting, and Participants

In a retrospective matched cohort study using data from a centralized data registry of patients evaluated by neuro-ophthalmologists at 1 academic institution from December 1, 2017, through November 30, 2023, a search for International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code H47.01 (ischemic optic neuropathy) and text search yielded 16 827 patients with no history of NAION. Propensity matching was used to assess whether prescribed semaglutide was associated with NAION in patients with type 2 diabetes (T2D) or overweight/obesity, in each case accounting for covarying factors (sex, age, systemic hypertension, T2D, obstructive sleep apnea, obesity, hyperlipidemia, and coronary artery disease) and contraindications for use of semaglutide. The cumulative incidence of NAION was determined with the Kaplan-Meier method and a Cox proportional hazards regression model adjusted for potential confounding comorbidities. Data were analyzed from December 1, 2017, through November 30, 2023.

Exposures

Prescriptions for semaglutide vs non-GLP-1 RA medications to manage either T2D or weight.

Main Outcomes and Measures

Cumulative incidence and hazard ratio of NAION.

Results

Among 16 827 patients, 710 had T2D (194 prescribed semaglutide; 516 prescribed non-GLP-1 RA antidiabetic medications; median [IQR] age, 59 [49-68] years; 369 [52%] female) and 979 were overweight or obese (361 prescribed semaglutide; 618 prescribed non-GLP-1 RA weight-loss medications; median [IQR] age, 47 [32-59] years; 708 [72%] female). In the population with T2D, 17 NAION events occurred in patients prescribed semaglutide vs 6 in the non-GLP-1 RA antidiabetes cohort. The cumulative incidence of NAION for the semaglutide and non-GLP-1 RA cohorts over 36 months was 8.9% (95% CI, 4.5%-13.1%) and 1.8% (95% CI, 0%-3.5%), respectively. A Cox proportional hazards regression model showed higher risk of NAION for patients receiving semaglutide (hazard ratio [HR], 4.28; 95% CI, 1.62-11.29); P < .001). In the population of patients who were overweight or obese, 20 NAION events occurred in the prescribed semaglutide cohort vs 3 in the non-GLP-1 RA cohort. The cumulative incidence of NAION for the semaglutide vs non-GLP-1 RA cohorts over 36 months was 6.7% (95% CI, 3.6%-9.7%) and 0.8% (95% CI, 0%-1.8%), respectively. A Cox proportional hazards regression model showed a higher risk of NAION for patients prescribed semaglutide (HR, 7.64; 95% CI, 2.21-26.36; P < .001).

Conclusions and Relevance

This study's findings suggest an association between semaglutide and NAION. As this was an observational study, future study is required to assess causality.

Predictive Value of the International Classification of Diseases, 9th Revision Codes for Identifying Ocular Oncology Diagnoses

Introduction

The aim of this study was to determine the predictive value of International Classification of Diseases, 9th Revision (ICD-9) billing codes for identifying ocular oncology diagnoses.

Methods

Population-based retrospective cohort study of all Olmsted County, Minnesota residents with any ocular neoplasm-related ICD-9 code from January 1, 2006 to October 1, 2015. All medical records were reviewed for confirmation of ocular neoplasm. Diagnoses with ≥5 cases confirmed via a medical record review were compared to corresponding ICD-9 codes. Main outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-9 codes.

Results

Among 3,932 subjects with ≥1 ocular neoplasm-related ICD-9 code, 21 diagnoses met study criteria. The most frequent intraocular, extraocular/orbital, and ocular surface diagnoses were choroidal nevus (n = 824), epidermal inclusion cyst (n = 263), and conjunctival nevus (n = 74), respectively. PPVs ranged from 1.2% to 73.8%, NPVs from 96.9% to 100%, sensitivity from 0% to 100%, and specificity from 85.7% to 100%. Among malignant neoplasms, PPV ranged from 0% to 73.8%: ocular surface squamous neoplasia (PPV: 0%), choroidal melanoma (PPV: 25.0%), eyelid squamous cell carcinoma (PPV: 46.7%), and eyelid basal cell carcinoma (PPV: 73.8%). Among benign neoplasms, PPV ranged from 1.2% (dermoid cyst) to 61.6% (choroidal nevus).

Conclusion

There was a wide variation in a predictive value of ocular neoplasm-related ICD-9 billing codes, which suggests that ocular oncology-related claims data alone may overestimate the true number of ocular oncology diagnoses.