The AAN's Axon Registry: Mastering how we are measured

Examining the National Representativeness of the Axon Registry: A Neurology-Specific Patient Registry

BACKGROUND AND OBJECTIVES

The objective of this study was to determine the external validity of the Axon Registry by comparing the 2019 calendar year data with 2 nationally representative, publicly available data sources, specifically the National Ambulatory Medical Care Survey (NAMCS) and the Medical Expenditure Panel Survey (MEPS). The Axon Registry is the American Academy of Neurology's neurology-focused qualified clinical data registry that reports and analyzes electronic health record data from participating US neurology providers. Its key function is to support quality improvement within ambulatory neurology practices while also promoting high-quality evidence-based care in clinical neurology. We compared demographics of patients who had an outpatient or office visit with a neurologist along with prevalence of selected neurologic conditions and neurologic procedures across the 3 data sets.

METHODS

We performed a cross-sectional, retrospective comparison of 3 data sets: NAMCS (2012-2016), MEPS (2013-2017, 2019), and Axon Registry (2019). We obtained patient demographics (age, birth sex, race, ethnicity), patient neurologic conditions (headache, epilepsy, cerebrovascular disease, multiple sclerosis, parkinsonism, dementia, spinal pain, and polyneuropathy), provider location, and neurologic procedures (neurology visits, MR/CT neuroimaging studies and EEG/EMG neurophysiologic studies). Parameter estimates from the pooled 5-year samples of the 2 public data sets, calculated at the visit level, were compared descriptively with those of the Axon Registry. We calculated Cohen h and performed Wald tests (α = 0.05) to conduct person-level statistical comparisons between MEPS 2019 and Axon Registry 2019 data.

RESULTS

The Axon Registry recorded 1.3 M annual neurology visits (NAMCS, 11 M; MEPS, 22 M) and 645 K people with neurologic conditions (MEPS, 10 M). Compared with the pooled national surveys, the Axon Registry has similar patient demographics, neurologic condition prevalence, neuroimaging and neurophysiologic utilization, and provider location. In direct comparison with MEPS 2019, the Axon Registry 2019 had fewer children (2% vs 7%), more elderly persons (21% vs 16%), fewer non-Black and non-White race persons (5% vs 8%), less number of patients with epilepsy (10% vs 13%), more patients with dementia (8% vs 6%), more patients with cerebrovascular disease (11% vs 8%), and a greater predominance of neurology providers in the Midwest (25% vs 20%). The only difference with a non-negligible effect size was the proportion of people younger than 15 years (Cohen h = 0.25).

DISCUSSION

The Axon Registry demonstrates high concordance with 2 nationally representative surveys. Recruiting more and diverse neurology providers will further improve the volume, representativeness, and value of the Axon Registry.

Big Data Research in Neuro-Ophthalmology: Promises and Pitfalls

BACKGROUND

Big data clinical research involves application of large data sets to the study of disease. It is of interest to neuro-ophthalmologists but also may be a challenge because of the relative rarity of many of the diseases treated.

EVIDENCE ACQUISITION

Evidence for this review was gathered from the authors' experiences performing analysis of large data sets and review of the literature.

RESULTS

Big data sets are heterogeneous, and include prospective surveys, medical administrative and claims data and registries compiled from medical records. High-quality studies must pay careful attention to aspects of data set selection, including potential bias, and data management issues, such as missing data, variable definition, and statistical modeling to generate appropriate conclusions. There are many studies of neuro-ophthalmic diseases that use big data approaches.

CONCLUSIONS

Big data clinical research studies complement other research methodologies to advance our understanding of human disease. A rigorous and careful approach to data set selection, data management, data analysis, and data interpretation characterizes high-quality studies.

Utilizing the Axon Registry® for quality improvement

In 2015, the American Academy of Neurology began development of a clinical quality data registry now known as the Axon Registry®. The data collected by the Axon Registry and reported back to participants include performance on a number of quality measures relevant to neurology practice. While the Axon Registry may serve any number of needs for neurology practices, the essential function of the registry is to inform neurologists regarding the quality of their care and provide them with a tool to establish not only performance baselines but progress toward improved quality of care. This article includes 2 case studies of how the Axon Registry has been implemented in neurology practices to date. In the future, implementation of patient-reported outcome data and additional outcome measures will be necessary to expand the reach and effectiveness of the Axon Registry as a quality improvement tool.