Thirty-day readmission after status epilepticus in the United States: Insights from the nationwide readmission database.

OBJECTIVE: To determine the incidence, causes, predictors, and costs of 30-day readmissions in patients admitted with status epilepticus (SE) from a large representative United States (US) population. METHODS: Adults (age ≥18 years) hospitalized with a primary diagnosis of SE (International Classification of Diseases-Ninth Revision-CM codes 345.2 or 345.3) between January 2013 and September 2015 were identified using the Nationwide Readmissions Database. A multivariable logistic regression model was used to identify predictors of 30-day readmissions. RESULTS: Of 42,232 patients with index SE, 6372 (15.0%) were readmitted within 30 days. In the multivariable analysis, intracranial hemorrhage (odds ratio, 1.56; 95% confidence interval, 1.12-2.18), psychosis (1.26 95%, 1.05-1.50), diabetes mellitus (1.12, 95%, 1.00-1.25), chronic kidney disease (1.50, 95%, 1.31-1.72), chronic liver disease (1.51; 95%, 1.24-1.84), >3 Elixhauser comorbidities (1.18; 95%, 1.06-1.31), length of stay >4 days during index hospitalization (1.41; 95%, 1.28-1.56) and discharge to skilled nursing facility (SNF) (1.14; 95%, 1.01-1.28) were independent predictors of 30-day readmission. The most common reason for readmission was seizures (45.1%). Median length of stay and costs of readmission were 4 days (interquartile range [IQR], 2-7 days) and $7882 (IQR, $4649-$15,012), respectively. CONCLUSION: Thirty-day readmissions after SE occurs in 15% of patients, the majority of which were due to seizures. Readmitted patients are more likely to have multiple comorbidities, a longer length of stay, and discharge to SNF. Awareness of these predictors can help identify and target high-risk patients for interventions to reduce readmissions and costs.

Assessment and effect of a gap between new-onset epilepsy diagnosis and treatment in the US.

OBJECTIVE: To estimate the treatment gap between a new epilepsy diagnosis and antiepileptic drug (AED) initiation in the United States. METHODS: Retrospective claims-based cohort study using Truven Health MarketScan databases (commercial and supplemental Medicare, calendar years 2010-2015; Medicaid, 2010-2014) and a validation study using PharMetrics Plus Database linked to LRx claims database (2009-2014). Persons met epilepsy diagnostic criteria, had an index date (first epilepsy diagnosis) with a preceding 2-year baseline (1 year for persons aged 1 to <2 years; none for persons <1 year), and continuous medical and pharmacy enrollment without epilepsy/seizure diagnosis or AED prescription during baseline. Outcomes included percentage of untreated persons (no AED prescription) up to 3 years' follow-up and comparative outcomes (incidence rate ratio: untreated persons/treated persons), including medical events and health care resource utilization. RESULTS: In the primary study, 59,970 persons met selection (or inclusion) criteria; 36.7% of persons with newly diagnosed epilepsy remained untreated up to 3 years after diagnosis. In the validation study (N = 30,890), 31.8% of persons remained untreated up to 3 years after diagnosis. Lack of AED treatment was associated with an adjusted incidence rate ratio (95% confidence interval) of 1.2 (1.2-1.3) for medical events, 2.3 (2.2-2.3) for hospitalizations, and 2.8 (2.7-2.9) for emergency department visits. CONCLUSIONS: One-third of newly diagnosed persons remain untreated up to 3 years after epilepsy diagnosis. The increased risk of medical events and health care utilization highlights the consequences of delayed treatment after epilepsy diagnosis, which might be preventable.

Estimating Epilepsy Incidence and Prevalence in the US Pediatric Population Using Nationwide Health Insurance Claims Data.

This study aims to determine prevalence and incidence of epilepsy in the US pediatric population. We analyzed commercial claims and Medicaid insurance claims data between 2008 and 2012. Over 8 million continuously enrolled lives aged 0 to 19 years were included. Our definition of a prevalent case of epilepsy was based on International Classification of Diseases-coded diagnoses of epilepsy or seizures and evidence of prescribed antiepileptic drugs. Incident cases were identified in subjects continuously enrolled for ≥2 years of which the first 2 years had no indication of epilepsy or seizures. The overall prevalence estimate for 2012 was 6.8 per 1,000 children. The overall incidence estimate for 2012 was 104 per 100,000 pediatric population. This study provides estimates of the prevalence and incidence of epilepsy in the US pediatric population, using large claims datasets from multiple US population sectors. The findings appear reasonably representative of the US-insured pediatric population.

Health-care access among adults with epilepsy: The U.S. National Health Interview Survey, 2010 and 2013.

INTRODUCTION: Community-based and other epidemiologic studies within the United States have identified substantial disparities in health care among adults with epilepsy. However, few data analyses addressing their health-care access are representative of the entire United States. This study aimed to examine national survey data about adults with epilepsy and to identify barriers to their health care. MATERIALS AND METHODS: We analyzed data from U.S. adults in the 2010 and the 2013 National Health Interview Surveys, multistage probability samples with supplemental questions on epilepsy. We defined active epilepsy as a history of physician-diagnosed epilepsy either currently under treatment or accompanied by seizures during the preceding year. We employed SAS-callable SUDAAN software to obtain weighted estimates of population proportions and rate ratios (RRs) adjusted for sex, age, and race/ethnicity. RESULTS: Compared to adults reporting no history of epilepsy, adults reporting active epilepsy were significantly more likely to be insured under Medicaid (RR=3.58) and less likely to have private health insurance (RR=0.58). Adults with active epilepsy were also less likely to be employed (RR=0.53) and much more likely to report being disabled (RR=6.14). They experience greater barriers to health-care access including an inability to afford medication (RR=2.40), mental health care (RR=3.23), eyeglasses (RR=2.36), or dental care (RR=1.98) and are more likely to report transportation as a barrier to health care (RR=5.28). CONCLUSIONS: These reported substantial disparities in, and barriers to, access to health care for adults with active epilepsy are amenable to intervention.

Descriptive epidemiology of epilepsy in the U.S. population: A different approach.

OBJECTIVE: Determine prevalence and incidence of epilepsy within two health insurance claims databases representing large sectors of the U.S. METHODS: A retrospective observational analysis using Commercial Claims and Medicare (CC&M) Supplemental and Medicaid insurance claims data between January 1, 2007 and December 31, 2011. Over 20 million continuously enrolled lives of all ages were included. Our definition of a prevalent case of epilepsy was based on International Classification of Diseases, Ninth Revision, Clinical Modification-coded diagnoses of epilepsy or seizures and evidence of prescribed antiepileptic drugs. Incident cases were identified among prevalent cases continuously enrolled for ≥ 2 years before the year of incidence determination with no epilepsy, seizure diagnoses, or antiepileptic drug prescriptions recorded. RESULTS: During 2010 and 2011, overall age-adjusted prevalence estimate, combining weighted estimates from all datasets, was 8.5 cases of epilepsy/1,000 population. With evaluation of CC&M and Medicaid data separately, age-adjusted prevalence estimates were 5.0 and 34.3/1,000 population, respectively, for the same period. The overall age-adjusted incidence estimate for 2011, combining weighted estimates from all datasets, was 79.1/100,000 population. Age-adjusted incidence estimates from CC&M and Medicaid data were 64.5 and 182.7/100,000 enrollees, respectively. Incidence data should be interpreted with caution due to possible misclassification of some prevalent cases. SIGNIFICANCE: The large number of patients identified as having epilepsy is statistically robust and provides a credible estimate of the prevalence of epilepsy. Our study draws from multiple U.S. population sectors, making it reasonably representative of the U.S.-insured population.

Sudden unexpected death in epilepsy: assessing the public health burden.

OBJECTIVE: There is not yet a clear consensus on the incidence of sudden unexpected death in epilepsy (SUDEP) or the extent of its burden on public health. In this systematic review, we seek to summarize the incidence of SUDEP and its age distribution, as well as the years of potential life lost and cumulative risks of SUDEP for persons with epilepsy. METHODS: We conducted a systematic search for epidemiologic studies of sudden death in epilepsy and rated their quality of evidence. We pooled data from comparable higher quality population-based studies of SUDEP incidence across all age groups, calculating the overall incidence of SUDEP per 100,000 population, and per 1,000 people with epilepsy. Using standard formulas, we also calculated the years of potential life lost and cumulative risks associated with SUDEP. RESULTS: SUDEP has an estimated overall crude annual incidence rate of 0.81 cases per 100,000 population, or 1.16 cases per 1,000 patients with epilepsy. Comparing years of potential life lost from SUDEP with selected other neurologic diseases, SUDEP ranks second only to stroke. SIGNIFICANCE: Despite limitations to the data on which our analysis is based, we conclude that the public health burden of SUDEP, which has previously been underappreciated, is substantial and deserves much more attention from clinicians, researchers, and the public health community.

Standards for epidemiologic studies and surveillance of epilepsy.

Worldwide, about 65 million people are estimated to have epilepsy. Epidemiologic studies are necessary to define the full public health burden of epilepsy; to set public health and health care priorities; to provide information needed for prevention, early detection, and treatment; to identify education and service needs; and to promote effective health care and support programs for people with epilepsy. However, different definitions and epidemiologic methods complicate the tasks of these studies and their interpretations and comparisons. The purpose of this document is to promote consistency in definitions and methods in an effort to enhance future population-based epidemiologic studies, facilitate comparison between populations, and encourage the collection of data useful for the promotion of public health. We discuss: (1) conceptual and operational definitions of epilepsy, (2) data resources and recommended data elements, and (3) methods and analyses appropriate for epidemiologic studies or the surveillance of epilepsy. Variations in these are considered, taking into account differing resource availability and needs among countries and differing purposes among studies.

Unmet health care needs among CSHCN with neurologic conditions.

OBJECTIVE: Children with neurologic conditions require a variety of services. With this study we examined health care needs and unmet needs among children with neurologic conditions. METHODS: Cross-sectional data reported by parents of 3- to 17-year-olds in the 2005-2006 National Survey of Children With Special Health Care Needs were analyzed. Demographic characteristics, health care needs, and unmet needs of children with special health care needs (CSHCN) and neurologic conditions were descriptively compared with an independent referent group of children without special health care needs; statistical contrasts were performed as a function of the type (conditions included in the Diagnostic and Statistical Manual of Mental Disorders [DSM] or not) and number of reported neurologic conditions. RESULTS: Compared with the parents of children without special health care needs, parents of CSHCN with neurologic conditions were more likely to report unmet health care needs for their child. After adjustment for demographic factors and severity of functional limitation, CSHCN with at least 2 conditions had more visits to a health care provider, needed more services, and reported more unmet needs than CSHCN with a single DSM condition. The magnitude of need among CSHCN was greatest among those with at least 1 of each type of neurologic condition. CONCLUSIONS: Unmet health care needs exist among CSHCN with neurologic conditions and are particularly pronounced among children with a combination of both DSM and non-DSM disorders. The health care needs among CSHCN with multiple neurologic conditions may be better served by targeted efforts to improve care coordination.

Disparities in epilepsy: report of a systematic review by the North American Commission of the International League Against Epilepsy.

PURPOSE: We undertook a systematic review of the evidence on disparities in epilepsy with a focus on North American data (Canada, United States, and the English-speaking Caribbean). METHODS: We identified and evaluated: access to and outcomes following medical and surgical treatment, disability, incidence and prevalence, and knowledge and attitudes. An exhaustive search (1965-2007) was done, including: (1) disparities by socioeconomic status (SES), race/ethnicity, age, or education of subgroups of the epilepsy population; or (2) disparities between people with epilepsy (PWE) and healthy people or with other chronic illnesses. RESULTS: From 1,455 citations, 278 eligible abstracts were identified and 44 articles were reviewed. Comparative research data were scarce in all areas. PWE have been shown to have lower education and employment status; among PWE, differences in access to surgery have been shown by racial/ethnic groups. Aboriginals, women, and children have been shown to differ in use of health resources. Poor compliance has been shown to be associated with lower SES, insufficient insurance, poor relationship with treating clinicians, and not having regular responsibilities. DISCUSSION: Comprehensive, comparative research on all aspects of disparities in epilepsy is needed to understand the causes of disparities and the development of any policies aimed at addressing health disparities and minimizing their impact.

Prevalence of active epilepsy and health-related quality of life among adults with self-reported epilepsy in California: California Health Interview Survey, 2003.

PURPOSE: To examine the prevalence of self-reported epilepsy and active epilepsy, associated burden of impaired health-related quality of life, risk factors, and access to care in adults with self-reported epilepsy, and those classified as having active epilepsy with and without recent seizures. METHODS: We analyzed data from adults aged >or=18 years (n = 41,494) who participated in the 2003 California Health Interview Survey (CHIS). RESULTS: In California, 1.2% of adults reported ever being told they had epilepsy or seizure disorder, and 0.7% were classified as having active epilepsy. About three-fourths of adults with active epilepsy with recent seizures reported fair or poor health status. Adults with active epilepsy with recent seizures reported almost two weeks of poor physical or mental health and activity limitation days compared with two to 4 days per month in those without epilepsy. Among adults with active epilepsy and recent seizures, about one-quarter reported not taking any medicine to control their seizure disorder or epilepsy. About one-third reported physical disability/unable to work compared to a small proportion of the general population. The majority of adults with active epilepsy reported having a regular source of medical care. CONCLUSION: Our findings highlight the burden of epilepsy among adults in California. CHIS serves as a model demonstrating the value of including questions about epilepsy on public health surveillance systems to ascertain the burden of the disorder and to guide intervention research and public policy to improve HRQOL in people with epilepsy.

Estimating prevalence, incidence, and disease-related mortality for patients with epilepsy in managed care organizations.

PURPOSE: The purpose of the present study was to apply computer algorithms to an administrative data set to identify the prevalence of epilepsy, incidence of epilepsy, and epilepsy-related mortality of patients in a managed care organization (MCO). METHODS: The study population consisted of members enrolled in Lovelace Health Plan, a component of Lovelace Health Systems, a statewide MCO headquartered in Albuquerque, New Mexico. Patient records were obtained from July 1996 to June 2001. Four logistic regression models with high sensitivity and specificity were applied to 1-, 3-, and 5-year time frames in which members were continuously enrolled in the MCO. Incidence was defined for patients who did not have an epilepsy-associated code in the 18 months before the first diagnosis entry. Mortality estimates in the population also were assessed by using a matched control group and linkage to a statewide death registry. RESULTS: The data yielded estimated prevalence rates of 7-10 per 1,000, depending on age, sex, ethnicity, and time interval. Annualized incidence was 47 per 100,000 for members continuously enrolled for 3 years and 71 per 100,000 for members continuously enrolled for 5 years. Crude mortality rates were 2-2.5 times higher for epilepsy patients identified with the algorithms than for the matched controls. Conditional logistic regression indicated that the odds of death for epilepsy patients as compared with controls ranged from 1.24 to 2.06. CONCLUSIONS: Accurate estimation of prevalence, incidence, and mortality rates for epilepsy is an essential component of disease management in MCOs. The algorithms in this project can be used to monitor trends in prevalence, incidence, and mortality to inform decisions critical to improving the health care needs and quality of life for patients with epilepsy.

Developing a computer algorithm to identify epilepsy cases in managed care organizations.

The goal of this study was to develop an algorithm for detecting epilepsy cases in managed care organizations (MCOs). A data set of potential epilepsy cases was constructed from an MCO's administrative data system for all health plan members continuously enrolled in the MCO for at least 1 year within the study period of July 1, 1996 through June 30, 1998. Epilepsy status was determined using medical record review for a sample of 617 cases. The best algorithm for detecting epilepsy cases was developed by examining combinations of diagnosis, diagnostic procedures, and medication use. The best algorithm derived in the exploratory phase was then applied to a new set of data from the same MCO covering the period of July 1, 1998 through June 30, 2000. A stratified sample based on ethnicity and age was drawn from the preliminary algorithm-identified epilepsy cases and non-cases. Medical record review was completed for 644 cases to determine the accuracy of the algorithm. Data from both phases were combined to permit refinement of logistic regression models and to provide more stable estimates of the parameters. The best model used diagnoses and antiepileptic drugs as predictors and had a positive predictive value of 84% (sensitivity 82%, specificity 94%). The best model correctly classified 90% of the cases. A stable algorithm that can be used to identify epilepsy patients within MCOs was developed. Implications for use of the algorithm in other health care settings are discussed.