Disparities in the nationwide distribution of epilepsy centers

The Impact of Neighborhood and Socioeconomic Disparities on Distal Radius Fracture Follow-Up Adherence

BACKGROUND

The aims of this retrospective cohort study were (1) to assess whether the Area Deprivation Index (ADI), a novel neighborhood-level socioeconomic disparities metric, is associated with follow-up nonadherence, and (2) to determine the individual-level socioeconomic factors associated with follow-up nonadherence after treatment of distal radius fractures (DRFs).

METHODS

The authors included all patients who underwent nonoperative or operative management of DRFs at an academic level I trauma center between 2019 and 2021. A manual chart review was performed to collect data on ADI, sociodemographic factors, injury characteristics, conservative and surgical interventions, and health care utilization.

RESULTS

There was a significant weak negative Spearman-ranked correlation between ADI state deciles and clinic attendance rates ( rs [220] = -0.144 [95% CI, -0.274 to -0.009]; P = 0.032). Socioeconomic factors associated with significant differences in clinic attendance rates were having a spouse or partner (protective) ( P = 0.007), Medicaid insurance ( P = 0.013), male sex ( P = 0.023), and current smoking ( P = 0.026). Factors associated with differences in no-show rates were having a spouse or partner (odds ratio [OR], 0.326 [95% CI, 0.123 to 0.867]; P = 0.025), Medicaid insurance (OR, 7.78 [95% CI, 2.15 to 28.2]; P = 0.002), male sex (OR, 4.09 [95% CI, 1.72 to 9.74]; P = 0.001), and cigarette use (OR, 5.07 [95% CI, 1.65 to 15.6]; P = 0.005).

CONCLUSIONS

ADI has a weak, negative correlation with clinic attendance rates after DRF treatment. Significant disparities in clinic follow-up adherence exist between patients on the basis of marital status, insurance, sex, and cigarette use.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, III.

Disparities in Access to Deep Brain Stimulation and Responsive Neurostimulation Approaches to Drug-Resistant Epilepsy

BACKGROUND

Epilepsy affects 1% to 2% of the global population, and those who are resistant to medical treatment may be candidates for neuromodulation. In select populations, brain stimulation approaches including deep brain stimulation (DBS) and responsive neurostimulation (RNS) are used. Although studies have shown that patients from Black, Hispanic, lower income, and rural communities have less access to epilepsy care and have lower rates of epilepsy surgery, disparities in the use of brain stimulation for epilepsy treatment are currently not known.

MATERIALS AND METHODS

We queried the US National Inpatient Sample data base from January 1, 2014 to December 31, 2019 for all patients discharged with an International Classification of Diseases (ICD) Ninth Revision or ICD Tenth Revision diagnosis of drug-resistant epilepsy. Among these patients discharged, the rates of brain stimulation treatment, including DBS and RNS, were reported in each subgroup of race, ethnicity, and insurance. To generate national estimates, all analyses were weighted.

RESULTS

A total of 237,895 patients discharged with drug-resistant epilepsy were identified, of whom 4,925 (2.1%) received brain stimulation treatment for drug-resistant epilepsy. Black patients (n = 420, 0.9%, odds ratio [OR] = 0.51, 95% CI [0.40, 0.64]) were less likely to receive brain stimulation treatment than were White patients (n = 3300, 2.4%). There was no significant difference between Asian (n = 105, 2.3%, OR = 0.80, 95% CI [0.53, 1.33]) and Hispanic (n = 655, 2.6%, OR = 0.95, 95% CI [0.77, 1.17]) patients and White patients. No significant difference was observed between female (n = 2515, 2.1%, OR = 1.02, 95% CI [0.89, 1.17]) and male (n = 2410, 2.0%) patients either. Patients with Medicare (n = 1150, 1.2%, OR = 0.69, 95% CI [0.57, 0.84]) or Medicaid (n = 1150, 1.8%, OR = 0.52, 95% CI [0.44, 0.62]) were less likely to receive brain stimulation treatment than were those with private insurance as the primary payer (n = 2370, 3.9%).

CONCLUSIONS

We discovered significant disparities in the use of brain stimulation treatments for drug-resistant epilepsy based on race and insurance status. More research will be required to determine the cause of these disparities.

Mortality and mortality disparities among people with epilepsy in the United States, 2011-2021

Studies on epilepsy mortality in the United States are limited. We used the National Vital Statistics System Multiple Cause of Death data to investigate mortality rates and trends during 2011-2021 for epilepsy (defined by the International Classification of Diseases, 10th Revision, codes G40.0-G40.9) as an underlying, contributing, or any cause of death (i.e., either an underlying or contributing cause) for U.S. residents. We also examined epilepsy as an underlying or contributing cause of death by selected sociodemographic characteristics to assess mortality rate changes and disparities in subpopulations. During 2011-2021, the overall age-standardized mortality rates for epilepsy as an underlying (39 % of all deaths) or contributing (61 % of all deaths) cause of death increased 83.6 % (from 2.9 per million to 6.4 per million population) as underlying cause and 144.1 % (from 3.3 per million to 11.0 per million population) as contributing cause (P < 0.001 for both based on annual percent changes). Compared to 2011-2015, in 2016-2020 mortality rates with epilepsy as an underlying or contributing cause of death were higher overall and in nearly all subgroups. Overall, mortality rates with epilepsy as an underlying or contributing cause of death were higher in older age groups, among males than females, among non-Hispanic Black or non-Hispanic American Indian/Alaska Native persons than non-Hispanic White persons, among those living in the West and Midwest than those living in the Northeast, and in nonmetro counties compared to urban regions. Results identify priority subgroups for intervention to reduce mortality in people with epilepsy and eliminate mortality disparity.

Telemedicine as a path to bridging inequities in patients with epilepsy

OBJECTIVE

Access to epilepsy specialist care is not uniform in the USA, with prominent gaps in rural areas. Understanding the reasons for nonattendance at epilepsy appointments may help identify access hurdles faced by patients. This study was undertaken to better understand clinic absenteeism in epilepsy and how it may be influenced by telemedicine.

METHODS

In this retrospective study, social determinants of health were collected for all adult patients scheduled in epilepsy clinic, as either an in-person or telemedicine appointment, at University of Kentucky between July 2021 and December 2022. The primary outcome measure was attendance or absence at the appointment. Subgroup analyses were done to better understand the drivers of attendance at telemedicine visits and evaluate telemedicine utilization by underserved populations.

RESULTS

A total of 3025 patient encounters of in-person and telemedicine visits were included. The no-show rate was significantly higher for in-person visits (32%) compared with telemedicine visits (20%, p < .001). A nominal logistic regression model identified seven factors increasing risk of absenteeism, including in-person visits, prior missed appointments, longer lead times to appointment, Medicaid/Medicare as payors, no significant other, lower mean annual income, and minority race. For each $10 000 increase in mean annual income, the odds of missing the appointment decreased by 8% (odds ratio = .92, 95% confidence interval = .89-.96, p < .001). Forty-one percent of underserved population opted for telemedicine visits, and they had a lower no-show rate (22%) as compared with in-person visits (33%, p < .001). Predictors of no-shows to televisits (1382) included Medicare/Medicaid coverage (as opposed to private insurance), no significant others, and a history of missing appointments.

SIGNIFICANCE

Telemedicine is effective at improving attendance, overcoming socioeconomic hurdles, and widening access to epilepsy care, particularly among underserved populations. Access to telecare depends on insurance coverage and emphasizes the need to include telemedicine in insurance plans to ensure uniform access to high-quality epilepsy care, irrespective of socioeconomic status.

Association of neighborhood deprivation with white matter connectome abnormalities in temporal lobe epilepsy

OBJECTIVE

Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality.

METHODS

Participants including 74 TLE patients (47 male, mean age = 39.2 years) and 45 healthy controls (27 male, mean age = 31.9 years) from the Epilepsy Connectome Project were classified into ADI-defined low and high disadvantage groups. Graph theoretic metrics were applied to multishell connectome diffusion-weighted imaging (DWI) measurements to derive 162 × 162 structural connectivity matrices (SCMs). The SCMs were harmonized using neuroCombat to account for interscanner differences. Threshold-free network-based statistics were used for analysis, and findings were correlated with ADI quintile metrics. A decrease in cross-sectional area (CSA) indicates reduced white matter integrity.

RESULTS

Sex- and age-adjusted CSA in TLE groups was significantly reduced compared to controls regardless of disadvantage status, revealing discrete aberrant white matter tract connectivity abnormalities in addition to apparent differences in graph measures of connectivity and network-based statistics. When comparing broadly defined disadvantaged TLE groups, differences were at trend level. Sensitivity analyses of ADI quintile extremes revealed significantly lower CSA in the most compared to least disadvantaged TLE group.

SIGNIFICANCE

Our findings demonstrate (1) the general impact of TLE on DWI connectome status is larger than the association with neighborhood disadvantage; however, (2) neighborhood disadvantage, indexed by ADI, revealed modest relationships with white matter structure and integrity on sensitivity analysis in TLE. Further studies are needed to explore this relationship and determine whether the white matter relationship with ADI is driven by social drift or environmental influences on brain development. Understanding the etiology and course of the disadvantage-brain integrity relationship may serve to inform care, management, and policy for patients.

Predictors of referral for long-term EEG monitoring for Medicare beneficiaries with drug-resistant epilepsy

OBJECTIVE

For people with drug-resistant epilepsy, the use of epilepsy surgery is low despite favorable odds of seizure freedom. To better understand surgery utilization, we explored factors associated with inpatient long-term EEG monitoring (LTM), the first step of the presurgical pathway.

METHODS

Using 2001-2018 Medicare files, we identified patients with incident drug-resistant epilepsy using validated criteria of ≥2 distinct antiseizure medication (ASM) prescriptions and ≥1 drug-resistant epilepsy encounter among patients with ≥2 years pre- and ≥1 year post-diagnosis Medicare enrollment. We used multilevel logistic regression to evaluate associations between LTM and patient, provider, and geographic factors. We then analyzed neurologist-diagnosed patients to further evaluate provider/environmental characteristics.

RESULTS

Of 12 044 patients with incident drug-resistant epilepsy diagnosis identified, 2% underwent surgery. Most (68%) were diagnosed by a neurologist. In total, 19% underwent LTM near/after drug-resistant epilepsy diagnosis; another 4% only underwent LTM much prior to diagnosis. Patient factors most strongly predicting LTM were age <65 (adjusted odds ratio 1.5 [95% confidence interval 1.3-1.8]), focal epilepsy (1.6 [1.4-1.9]), psychogenic non-epileptic spells diagnosis (1.6 [1.1-2.5]) prior hospitalization (1.7, [1.5-2]), and epilepsy center proximity (1.6 [1.3-1.9]). Additional predictors included female gender, Medicare/Medicaid non-dual eligibility, certain comorbidities, physician specialties, regional neurologist density, and prior LTM. Among neurologist-diagnosed patients, neurologist <10 years from graduation, near an epilepsy center, or epilepsy-specialized increased LTM likelihood (1.5 [1.3-1.9], 2.1 [1.8-2.5], 2.6 [2.1-3.1], respectively). In this model, 37% of variation in LTM completion near/after diagnosis was explained by individual neurologist practice and/or environment rather than measurable patient factors (intraclass correlation coefficient 0.37).

SIGNIFICANCE

A small proportion of Medicare beneficiaries with drug-resistant epilepsy completed LTM, a proxy for epilepsy surgery referral. While some patient factors and access measures predicted LTM, non-patient factors explained a sizable proportion of variance in LTM completion. To increase surgery utilization, these data suggest initiatives targeting better support of neurologist referral.

Hospital EEG Capability and Associations With Interhospital Transfer in Status Epilepticus

Background and Objectives

EEG is widely recommended for status epilepticus (SE) management. However, EEG access and use across the United States is poorly characterized. We aimed to evaluate changes in inpatient EEG access over time and whether availability of EEG is associated with interhospital transfers for patients hospitalized with SE.

Methods

We performed a cross-sectional study using data available in the National Inpatient Sample data set from 2012 to 2018. We identified hospitals that used continuous or routine EEG during at least 1 seizure-related hospitalization in a given year using ICD-9 and ICD-10 procedure codes and defined these hospitals as EEG capable. We examined annual change in the proportion of hospitals that were EEG capable during the study period, compared characteristics of hospitals that were EEG capable with those that were not, and fit multivariable logistic regression models to determine whether hospital EEG capability was associated with likelihood of interhospital transfer.

Results

Among 4,550 hospitals in 2018, 1,241 (27.3%) were EEG capable. Of these, 1,188 hospitals (95.7%) were in urban settings. From 2012 to 2018, the proportion of hospitals that were EEG capable increased in urban settings (30.5%-41.1%, Mann-Kendall [M-K] test p < 0.001) and decreased in rural settings (4.0%-3.2%, M-K p = 0.026). Among 130,580 patients hospitalized with SE, 80,725 (61.8%) presented directly to an EEG-capable hospital. However, EEG use during hospitalization varied from 8% to 98%. Initial admission to a hospital without EEG capability was associated with 22% increased likelihood of interhospital transfer (adjusted RR 1.22, [95% CI, 1.09-1.37]; p < 0.01). Among those hospitalized at an EEG-capable hospital, patients admitted to hospitals in the lowest quintile of EEG volume were more than 2 times more likely to undergo interhospital transfer (adjusted RR 2.22, [95% CI 1.65-2.93]; p < 0.001).

Discussion

A minority of hospitals are EEG capable yet care for most patients with SE. Inpatient EEG use, however, varies widely among EEG-capable hospitals, and lack of inpatient EEG access is associated with interhospital transfer. Given the high incidence and cost of SE, there is a need to better understand the importance and use of EEG in this patient population to further organize inpatient epilepsy systems of care to optimize outcomes.

Neighborhood disadvantage and health-related quality of life in pediatric epilepsy

INTRODUCTION

While several demographic and epilepsy-specific characteristics are associated with diminished HRQoL in children and adolescents with epilepsy, prior investigations have failed to incorporate and address the influence of broader social contextual factors on functional outcomes. To address this gap, the purpose of the current study was to investigate the role of neighborhood disadvantage on HRQoL, including the extent to which familial and seizure-specific risk factors are impacted.

METHODS

Data included parental ratings on the Quality of Life in Childhood Epilepsy (QOLCE) questionnaire for 135 children and adolescents with epilepsy, and the Area Deprivation Index (ADI) to measure neighborhood disadvantage. Bivariate correlations were conducted to identify significant associations with neighborhood disadvantage, followed by a three-stage hierarchical multiple regression to predict HRQoL. Follow-up binary logistic regressions were used to determine the risk conferred by neighborhood disadvantage on sociodemographic, seizure-specific, and HRQoL factors.

RESULTS

Moderate associations between neighborhood disadvantage and familial factors, including parental psychiatric history and Medicaid insurance, were identified, while disadvantage and greater seizure frequency were marginally associated. Neighborhood disadvantage independently predicted HRQoL, and was the sole significant predictor of HRQoL when familial factors were incorporated. Children with epilepsy living in disadvantaged areas were four times more likely to have diminished HRQoL, five times more likely to live with a parent with a significant psychiatric history, and four times more likely to reside with a family receiving Medicaid insurance.

CONCLUSIONS

These results highlight the importance of identifying high-risk groups, as the cumulative burden of social context, familial factors, and seizure-specific characteristics contribute to lower HRQoL in pediatric epilepsy which disproportionately affects patients from lower-resourced backgrounds. Potentially modifiable factors such as parental psychiatric status exist within the child's environment, emphasizing the importance of a whole-child approach to patient care. Further exploration of disadvantage in this population is needed to better understand these relationships over time.