Validity of International Classification of Diseases Codes for Identifying Neuro-Ophthalmic Disease in Large Data Sets: A Systematic Review

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.

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

BACKGROUND

The accuracy of International Classification of Diseases (ICD) codes for identifying cases of acute optic neuritis (aON) is not known. A prior study reported 61% accuracy for ICD code plus MRI consistent with aON within 2 months. This study determined accuracy for ICD code plus MRI within 2 months regardless of results.

METHODS

Retrospective chart review was conducted using a medical record research repository of a tertiary care institution from 1998 to 2019. Subjects with ICD-9/10 codes for ON and an MRI brain and/or orbits within 2 months of earliest (initial) ICD code were included. MRI was classified as positive or negative for aON based on report noting gadolinium-contrast enhancement. Clinical diagnosis at the time of initial code was classified as aON, prior ON, considered ON, alternative diagnosis, or unknown based on review of physician authored clinical notes within 7 days of the initial code. Accuracy of ICD code for aON, acute or prior ON, and acute, prior, or considered ON were calculated for all subjects and stratified based on MRI result.

RESULTS

Two hundred fifty-one subjects had MRI results within 2 months of their initial ON ICD code (49 positive MRI [previously reported]; 202 negative MRI). Among those with negative MRI, 32 (16%) had aON, 40 (20%) had prior ON, 19 (9%) considered ON as a diagnosis, 92 (46%) had other confirmed diagnoses, and 19 (9%) had unknown diagnosis at time of code. Considering all subjects, accuracy for ICD code was 25% for acute ON, 41% for acute or prior ON, and 48% for acute, prior, or considered ON. Positive MRI, increased number of ON ICD codes, a code given by an ophthalmologist or neurologist within 2 months, and the presence of a neurology encounter within 2 months were associated with an increased accuracy for clinical aON diagnosis.

CONCLUSIONS

In the setting of an MRI within 2 months, ICD codes for ON have low accuracy for acute ON and only slightly better accuracy for acute or prior ON. Accuracy is higher for cases with a positive MRI than those with a negative MRI, suggesting positive MRI in conjunction with ICD codes may help more accurately identify cases. Reliance on ICD and Current Procedural Terminology codes alone to identify aON cases may introduce substantial misclassification bias in claims-based research.

Predictors of Glucocorticoid Use for Acute Optic Neuritis in the United States, 2005-2019

PURPOSE

Acute optic neuritis (ON) is variably treated with glucocorticoids. We aimed to describe factors associated with glucocorticoid use.

METHODS

In this retrospective, longitudinal cohort study of insured patients in the United States (2005-2019), adults 18-50 years old with one inpatient or ≥2 outpatient diagnoses of ON within 90 days were included. Glucocorticoid use was classified as none, any dose, and high-dose (>100 mg prednisone equivalent ≥1 days). The primary outcome was glucocorticoid receipt within 90 days of the first ON diagnosis. Multivariable logistic regression models assessed the relationship between glucocorticoid use and sociodemographics, comorbidities, clinician specialty, visit number, and year.

RESULTS

Of 3026 people with ON, 65.8% were women (n = 1991), median age (interquartile range) was 38 years (31,44), and 68.6% were white (n = 2075). Glucocorticoids were received by 46% (n = 1385); 54.6% (n = 760/1385) of whom received high-dose. The odds of receiving glucocorticoids were higher among patients with multiple sclerosis (OR 1.61 [95%CI 1.28-2.04]; P < .001), MRI (OR 1.75 [95%CI 1.09-2.80]; P = .02), 3 (OR 1.80 [95%CI 1.46-2.22]; P < .001) or more (OR 4.08 [95%CI 3.37-4.95]; P < .001) outpatient ON visits, and in certain regions. Compared to ophthalmologists, patients diagnosed by neurologists (OR 1.36 [95%CI: 1.10-1.69], p = .005), emergency medicine (OR 3.97 [95%CI: 2.66-5.94]; P < .001) or inpatient clinicians (OR 2.94 [95%CI: 2.22-3.90]; P < .001) had higher odds of receiving glucocorticoids. Use increased 1.1% annually (P < .001).

CONCLUSIONS

Demyelinating disease, care intensity, setting, region, and clinician type were associated with glucocorticoid use for ON. To optimize care, future studies should explore reasons for ON care variation, and patient/clinician preferences.

Accuracy of the International Classification of Diseases, 9th Revision for Identifying Infantile Eye Disease

PURPOSE

To determine the predictive value of International Classification of Diseases, 9th Revision (ICD-9) codes for identifying infantile eye diagnoses.

METHODS

Population-based retrospective cohort study of all residents of Olmsted County, Minnesota diagnosed at ≤1 year of age with an ocular disorder. The medical records of all infants diagnosed with any ocular disorder from January 1, 2005, through December 31, 2014, were identified. To assess ICD-9 code accuracy, the medical records of all diagnoses with ≥20 cases were individually reviewed and compared to their corresponding ICD-9 codes. Main outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-9 codes.

RESULTS

In a cohort of 5,109 infants with ≥1 eye-related ICD-9 code, 10 ocular diagnoses met study criteria. The most frequent diagnoses were conjunctivitis (N = 1,695) and congenital nasolacrimal duct obstruction (N = 1,250), while the least common was physiologic anisocoria (N = 23). The PPVs ranged from 8.3% to 88.0%, NPVs from 96.3% to 100%, sensitivity from 3.0% to 98.7%, and specificity from 72.6% to 99.9%. ICD-9 codes were most accurate at identifying physiologic anisocoria (PPV: 88.0%) and least accurate at identifying preseptal cellulitis (PPV: 8.3%). In eye specialists versus non-eye specialists, there was a significant difference in PPV of ICD-9 codes for conjunctivitis (26.8% vs. 63.9%, p < .001), pseudostrabismus (85.9% vs. 25.0%, p < .001), and physiologic anisocoria (95.5% vs. 33.3%, p = .002).

CONCLUSION

The predictive value of ICD-9 codes for capturing infantile ocular diagnoses varied widely in this cohort. These findings emphasize the limitations of database research methodologies that solely utilize claims data to identify pediatric eye diseases.Abbreviations/Acronyms PPV: positive predictive value; NPV: negative predictive value; CNLDO: congenital nasolacrimal duct obstruction.

Factors Associated With Increased Emergency Department Utilization in Patients With Acute Optic Neuritis

BACKGROUND

Symptoms of acute vision loss and eye pain may lead patients with optic neuritis to seek care in the emergency department (ED). Given the availability of lower cost alternatives for providing medical care for optic neuritis, this study aimed to identify factors associated with higher ED utilization.

METHODS

Subjects with acute optic neuritis were identified through a chart review of adults with International Classification of Diseases-9 (ICD-9) or ICD-10 codes for optic neuritis with corresponding gadolinium contrast enhancement of the optic nerve on MRI in the medical record research repository of a tertiary care institution. Subjects were grouped based on the number of ED visits (0-1 and 2-3) within 2 months of either ICD code or MRI. Demographics, characteristics of disease presentation, type and location of medical care, testing (chest imaging, lumbar puncture, optical coherence tomography, spine MRI, visual field, and laboratory tests), treatment, provider specialty of follow-up visits, and duration of care were extracted from the medical record.

RESULTS

Of 30 acute optic neuritis subjects (age 41 ± 16 years, range 18-76, 53% [16/30] female), 19 had 0-1 ED visit and 11 had 2-3 ED visits. Most subjects were Caucasian, non-Hispanic (47%), followed by Asian (23%), Hispanic/Latino (17%), Black (10%), and others (3%). Subjects had an initial clinical encounter primarily in the outpatient setting (63%) as compared with the ED (37%). The median time from symptom onset to initial clinical encounter was 4 days with a range of 0-13. Subjects were mostly insured through a private insurance (60%), followed by Medicare/Medicaid (23%) and uninsured (17%). Fewer ED visits were associated with an initial clinical encounter in an outpatient setting (P = 0.02, chi-square), but not residential distance from the hospital or insurance type. Subjects with a higher number of ED visits were more likely to be of Hispanic/Latino ethnicity (P = 0.047, Fisher exact). There was no significant difference in the ophthalmic, radiologic, or laboratory testing performed in both groups. Both groups presented in a similar time frame with similar symptoms and clinical signs. Treatment was similar in both groups.

CONCLUSIONS

Subjects with their first clinical encounter for optic neuritis in the ED had more visits to the ED overall when compared with those first seen in an outpatient setting and thus strategies aimed at facilitating outpatient care may help reduce unnecessary ED visits, although some, such as insurance status, may be difficult to modify. Further study in a larger sample is needed to refine these observations.