Improved Accuracy/Completeness of EHR Race/Ethnicity Data: A Requisite Step to Address Disparities in Care.

Accurate and complete racial/ethnic data in the electronic health record are a requisite step to addressing disparities in neurologic care, and at local, regional, and national levels. The current data pertaining to the patients' race and ethnicity contained in the electronic health record are inadequate. This article outlines recommendations at the individual practice and electronic health record vendor level to improve documentation of race and ethnicity.

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.

Measuring Ambulatory Racial and Ethnic Neurologic Disparities With the Axon Registry.

Background and Objectives: The primary objective is to examine potential racial and ethnic (R/E) disparities in ambulatory neurology quality measures within the American Academy of Neurology Axon Registry. R/E disparities in neurologic US morbidity and mortality have been clearly documented. Despite these findings, there have been no nationwide examinations of how ambulatory neurologic care affects these negative health outcomes. Methods: This was a retrospective nonrandomized cohort study of patients in the AAN Axon Registry. The Axon Registry is a neurology-specific outpatient quality registry that collects, reports, and analyzes real-world deidentified electronic health record (EHR) data. Patients were included in the study if they contributed toward one of the selected quality measures for multiple sclerosis, epilepsy, Parkinson disease, or headache during the study period of January 1, 2019-December 31, 2019. Descriptive analyses of patient demographics were performed and then stratified by race and ethnicity. Results: There were a total of 633,672 patients included in these analyses. Separate analyses were performed for race (64% White, 8% Black, 1% Asian, and 27% unknown) and ethnicity (52% not Hispanic, 5% Hispanic, and 43% unknown). The mean age ranged from 18 to 55 years, with 61% female and 39% male. Quality measures were chosen based on completeness of R/E data and were either process or outcomes focused. Statistically significant differences were noted after controlling for multiple comparisons. Discussion: The large proportion of missing or unknown R/E data and low overall rate of performance on these quality measures made the relevance of small differences difficult to determine. This analysis demonstrates the feasibility of using the Axon Registry to assess neurologic disparities in outpatient care. More education and training are required on the accurate capture of R/E data in the EHR.

Quality of Neurologic Care in the United States: Initial Report From the Axon Registry.

OBJECTIVE: To provide the initial description of the quality of outpatient US neurologic care as collected and reported in the Axon Registry. METHODS: We describe characteristics of registry participants and the performance of neurology providers on 20 of the 2019 Axon Registry quality measures. From the distribution of providers' scores on a quality measure, we calculate the median performance for each quality measure. We test for associations between quality measure performance, provider characteristics, and intrinsic measure parameters. RESULTS: There were 948 neurology providers who contributed a total of 6,480 provider-metric observations. Overall, the average quality measure performance score at the provider level was 66 (median 77). At the measure level (n = 20), the average quality measure performance score was 53 (median 55) with a range of 2 to 100 (interquartile range 20-91). Measures with a lower-complexity category (e.g., discrete orders, singular concepts) or developed through the specialty's qualified clinical data registry pathway had higher performance distributions. There was no difference in performance between Merit-Based Incentive Payment System (MIPS) and non-MIPS providers. There was no association between quality measure performance and practice size, measure clinical topic/neurologic condition, or measure year of entry. CONCLUSIONS: This cross-sectional assessment of quality measure performance in 2019 Axon Registry data demonstrates modest performance scores and considerable variability across measures and providers. More complex measures were associated with lower performance. These findings serve as a baseline assessment of quality of ambulatory neurologic care in the United States and provide insights into future measure design.

Personalizing Dual-Target Cortical Stimulation with Bayesian Parameter Optimization Successfully Treats Central Post-Stroke Pain: A Case Report.

Central pain disorders, such as central post-stroke pain, remain clinically challenging to treat, despite many decades of pharmacological advances and the evolution of neuromodulation. For treatment refractory cases, previous studies have highlighted some benefits of cortical stimulation. Recent advances in new targets for pain and the optimization of neuromodulation encouraged our group to develop a dual cortical target approach paired with Bayesian optimization to provide a personalized treatment. Here, we present a case report of a woman who developed left-sided facial pain after multiple thalamic strokes. All previous pharmacologic and interventional treatments failed to mitigate the pain, leaving her incapacitated due to pain and medication side effects. She subsequently underwent a single burr hole for placement of motor cortex (M1) and dorsolateral prefrontal cortex (dlPFC) paddles for stimulation with externalization. By using Bayesian optimization to find optimal stimulation parameters and stimulation sites, we were able to reduce pain from an 8.5/10 to a 0/10 during a 5-day inpatient stay, with pain staying at or below a 2/10 one-month post-procedure. We found optimal treatment to be simultaneous stimulation of M1 and dlPFC without any evidence of seizure induction. In addition, we found no worsening in cognitive performance during a working memory task with dlPFC stimulation. This personalized approach using Bayesian optimization may provide a new foundation for treating central pain and other functional disorders through systematic evaluation of stimulation parameters.

Futures Planning at the AAN: Approach and Initial Outcome.

We describe a process of organizational strategic future forecasting, with a horizon of 2035, as implemented by the American Academy of Neurology (AAN) on behalf of its members, and as a model approach for other organizations. The participants were members of the 2018-2020 AAN Boards of Directors and Executive Team, moderated by a consultant with expertise in future forecasting. Four predetermined model scenarios of import to our field (1 "expectable," 1 "challenging," and 2 "visionary") were discussed in small groups, with alternative scenarios developed in specific domains. Common themes emerged among all scenarios: the importance of thoughtful integration of biomedical and information technology tools into neurologic practice; continued demonstration of the value of neurologic care to society; and emphasis on population management and prevention of neurologic disease. Allowing for the inherent uncertainties of predicting the future, the AAN's integration of structured forecasting into its strategic planning process has allowed the organization to prepare more effectively for change, such as the disruptions stemming from the coronavirus disease 2019 (COVID-19) pandemic. The approaches outlined here will be integrated into future AAN operations and may be implemented to a similar effect by other organizations.

Axon Registry® data validation: Accuracy assessment of data extraction and measure specification.

OBJECTIVE: To conduct a data validation study encompassing an accuracy assessment of the data extraction process for the Axon Registry®. METHODS: Data elements were abstracted from electronic health records (EHRs) by an external auditor (IQVIA) using virtual site visits at participating sites. IQVIA independently calculated Axon Registry quality measure performance rates based on American Academy of Neurology measure specifications and logic using Axon Registry data. Agreement between Axon Registry and IQVIA data elements and measure performance rates was calculated. Discordance was investigated to elucidate underlying systemic or idiosyncratic reasons for disagreement. RESULTS: Nine sites (n = 720 patients; n = 80 patients per site) with diversity among EHR vendor, practice settings, size, locations, and data transfer method were included. There was variable concordance between the data elements in the Axon Registry and those abstracted independently by IQVIA; high match rates (≥92%) were observed for discrete elements (e.g., demographics); lower match rates (<44%) were observed for elements with free text (e.g., plan of care). Across all measures, there was a 76% patient-level measure performance agreement between Axon Registry and IQVIA (κ = 0.53, p < 0.001). CONCLUSION: There was a range of concordance between data elements and quality measures in the Axon Registry and those independently abstracted and calculated by an independent vendor. Validation of data and processes is important for the Axon Registry as a clinical quality data registry that utilizes automated data extraction methods from the EHR. Implementation of remediation strategies to improve data accuracy will support the ability of the Axon Registry to perform accurate quality reporting.

Methane emissions from the Marcellus Shale in southwestern Pennsylvania and northern West Virginia based on airborne measurements.

Natural gas production in the U.S. has increased rapidly over the past decade, along with concerns about methane (CH4) leakage (total fugitive emissions), and climate impacts. Quantification of CH4 emissions from oil and natural gas (O&NG) operations is important for establishing scientifically sound, cost-effective policies for mitigating greenhouse gases. We use aircraft measurements and a mass balance approach for three flight experiments in August and September 2015 to estimate CH4 emissions from O&NG operations in the southwestern Marcellus Shale region. We estimate the mean ± 1σ CH4 emission rate as 36.7 ± 1.9 kg CH4 s-1 (or 1.16 ± 0.06 Tg CH4 yr-1) with 59% coming from O&NG operations. We estimate the mean ± 1σ CH4 leak rate from O&NG operations as 3.9 ± 0.4% with a lower limit of 1.5% and an upper limit of 6.3%. This leak rate is broadly consistent with the results from several recent top-down studies but higher than the results from a few other observational studies as well as in the U.S. Environmental Protection Agency CH4 emission inventory. However, a substantial source of CH4 was found to contain little ethane (C2H6), possibly due to coalbed CH4 emitted either directly from coalmines or from wells drilled through coalbed layers. Although recent regulations requiring capture of gas from the completion venting step of the hydraulic fracturing appear to have reduced losses, our study suggests that for a 20 year time scale, energy derived from the combustion of natural gas extracted from this region will require further controls before it can exert a net climate benefit compared to coal.

Effect of general anesthesia in patients with epilepsy: a population-based study.

General anesthesia may be required for particular diagnostic and therapeutic procedures in patients with seizure disorders. There is concern regarding the safety of anesthetic drugs in these individuals because of the reported proconvulsant effect of selected medications. Potentially, general anesthesia may be associated with perioperative seizures or increased adverse effects in people with epilepsy. The rationale for the present study was to evaluate the outcome of general anesthesia in a population-based cohort with seizure disorders undergoing interventions that were unlikely to alter the seizure tendency, for example, magnetic resonance imaging study. Seizures were observed in only 6 of 297 (2%) anesthetic procedures, and intravenous therapy was required in only one patient. None of the patients had any reported adverse effect from general anesthesia. The current findings may be useful in counseling and guiding patients with seizure disorders, their caregivers, and their guardians regarding the risk of general anesthesia.