Racial disparities in the utilization of invasive neuromodulation devices for the treatment of drug-resistant focal epilepsy.

Racial disparities affect multiple dimensions of epilepsy care including epilepsy surgery. This study aims to further explore these disparities by determining the utilization of invasive neuromodulation devices according to race and ethnicity in a multicenter study of patients living with focal drug-resistant epilepsy (DRE). We performed a post hoc analysis of the Human Epilepsy Project 2 (HEP2) data. HEP2 is a prospective study of patients living with focal DRE involving 10 sites distributed across the United States. There were no statistical differences in the racial distribution of the study population compared to the US population using census data except for patients reporting more than one race. Of 154 patients enrolled in HEP2, 55 (36%) underwent invasive neuromodulation for DRE management at some point in the course of their epilepsy. Of those, 36 (71%) were patients who identified as White. Patients were significantly less likely to have a device if they identified solely as Black/African American than if they did not (odds ratio = .21, 95% confidence interval = .05-.96, p = .03). Invasive neuromodulation for management of DRE is underutilized in the Black/African American population, indicating a new facet of racial disparities in epilepsy care.

Seizure documentation in people living with epilepsy.

Seizure documentation is an essential component of epilepsy management. Not all persons with epilepsy choose to document their seizures, but many view the practice as essential to managing their disease. While seizure documentation is a valuable aspect of patient care, clinicians and patients must remain aware that seizure underreport and overreport commonly occur due to lack of seizure awareness. Additionally, in rare cases, persons with epilepsy may intentionally conceal their seizures from clinicians. The continued development of electronic seizure diaries and epilepsy self-management software provides patients with new and expanding options for seizure documentation and disease management. In order for these tools to be utilized most effectively, patient input must be central to their development. Given the limitations of seizure documentation, the development of accurate, non-invasive seizure detection devices is crucial for accurate seizure monitoring.

Establishing a learning healthcare system to improve health outcomes for people with epilepsy.

OBJECTIVE: To describe the organization of the Epilepsy Learning Healthcare System (ELHS), a network that aims to improve care outcomes for people with epilepsy (PWE). MATERIALS AND METHODS: Patients and family partners, providers, researchers, epidemiologists, and other leaders collaborated to recruit epilepsy centers and community services organizations into a novel learning network. A multidisciplinary Coordinating Committee developed ELHS governance and organizational structure, including four key planning Cores (Community, Clinical, Quality Improvement, and Data). Through Quality Improvement (QI) methodology grounded in the Institute for Healthcare Improvement (IHI) model, including iterative Plan-Do-Study-Act (PDSA) rapid learning cycles and other learning and sharing sessions, ELHS equipped epilepsy centers and community organizations with tools to standardize, measure, share, and improve key aspects of epilepsy care. The initial learning cycles addressed provider documentation of seizure frequency and type, and also screening for medication adherence barriers. Rapid learning cycles have been carried out on these initial measures in both clinical centers and community-based settings. Additional key measures have been defined for quality of life, screening, and treatment for mental health and behavioral comorbidities, transition from pediatric to adult care, counseling for women and girls living with epilepsy, referral for specialty care, and prevention and treatment of seizure clusters and status epilepticus. RESULTS: It is feasible to adopt a learning healthcare system framework in epilepsy centers and community services organizations. Through structured collaboration between epilepsy care providers, community support organizations, PWE, and their families/caregivers we have identified new opportunities to improve outcomes that are not available in traditional care models.

A feasibility assessment of functioning and quality-of-life patient-reported outcome measures in adult epilepsy clinics: A systematic review.

OBJECTIVE: The objective of the study was to identify functioning and quality-of-life (QOL) patient-reported outcome measurements (PROMs) feasible for use in the waiting room of adult epilepsy clinics. MATERIAL AND METHODS: We searched PubMed and Web of Science for articles on in English, Spanish, Portuguese, Italian, and French published by the end of February 15th, 2019. We screened retrieved titles and abstracts looking for publications that reported the use of PROMs to measure functioning and QOL in epilepsy. The authors, clinical experts, and patient advocates from the Epilepsy Foundation of America conceptualized a set of desirable feasibility attributes for PROMs implementation in the waiting room of adult epilepsy clinics. These attributes included brief time for completion (i.e., ≤3 min), free cost, coverage of four minimum QOL domains and respective facets, and good evidence of psychometric properties. We defined QOL domains according to the World Health Organization's classification and created psychometric appraisal criteria based on the Food and Drug Administration's (FDA) Guidance. RESULTS: Eighteen candidate instruments were identified and compared with respect to desirable attributes for use in adult epilepsy clinics. We found that the Quality-of-life in epilepsy (QOLIE)-10 and Patient-Reported Outcome Measurement Information System-10 (PROMIS-10) were the most feasible PROMs for implementation in adult epilepsy clinics based on our criteria. The QOLIE-10 and PROMIS-10 still lack ideal evidence of responsiveness in people with epilepsy. CONCLUSION: This is the first systematic review that aimed to assess feasibility properties of available functioning and QOL PROMs. The QOLIE-10 and PROMIS-10 are potentially feasible instruments for implementation in the waiting room of adult epilepsy clinics. Further studies assessing the responsiveness of these PROMs are needed and will contribute to the selection of the most appropriate instrument for longitudinal use in adult epilepsy clinical practice.

Applying participatory action research in traumatic brain injury studies to prevent post-traumatic epilepsy.

The increased focus on stakeholder engagement in determining the aims, design, conduct of research and dissemination of results is substantially changing the biomedical research paradigm. In this era of patient-centered care, incorporating participatory action research methodology into large-scale multi-center studies is essential. The adoption of community engagement facilitates meaningful contribution to the design and implementation of clinical studies. Consequently, encouraging citizen participation and involving key organizations may guide the effective development of future clinical research protocols. Here, we discuss our experience in engaging individuals, their caregivers, as well as scientific and consumer organizations in public outreach and knowledge transfer to assist in the development of effective strategies for recruitment and retention in a future post-traumatic epilepsy prevention randomized controlled trial within the National Institute of Neurologic Disorders and Stroke Center Without Walls, Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx). The study includes a Public Engagement Core with a diverse consortium of stakeholder partners. Based on the Core's ongoing experience, it is recommended that multicenter studies integrate a participatory action research based approach to harness the benefits of a collective inquiry. The blueprint created by the EpiBioS4Rx Public Engagement Core is a resource that could be applied in other areas of biomedical research.

Patient and caregiver preferences for the potential benefits and risks of a seizure forecasting device: A best-worst scaling.

BACKGROUND: Epilepsy is the 4th most common neurological disorder and is characterized by recurrent, unpredictable seizures. The ability to forecast seizures is a significant unmet need and would have a transformative effect on the lives of people living with epilepsy. In an effort to address this need, the Epilepsy Foundation has committed effort and resources to promote the development of seizure forecasting devices (SFD). OBJECTIVE: To promote user-centered design of future SFD, we sought to quantify patient and caregiver preferences for the potential benefits and risks of SFD. METHODS: A community-centered approach was used to develop a survey incorporating a novel best-worst scaling (BWS) to assess preferences for SFD. A main-effect orthogonal array was used to design and generate 18 "prototypes" that systematically varied across six attributes: seizure forecasting probability, seizure forecasting range, inaccuracy of forecasting, amount of time required to use the device, how the device is worn, and cost. The dependent variable was the attributes that respondents selected the best and worst in each profile, and a choice model was estimated using conditional logistic regression, which was also stratified and compared across patients and caregivers. Respondents also indicated that they would accept each of the prototype SFDs if it were real. These acceptance data and net monetary benefits (relative to the least preferred SFD) were explored. RESULTS: There were 633 eligible respondents; 493 (78%) completed at least one task. Responses indicated that 346 (68%) had epilepsy, and 147 (29%) were primary caregivers or family members of someone with epilepsy. The data show that short forecasting range is the most favored among experimental attributes, followed by mid forecasting range and notification of high chance of seizure. Having the device implanted is the least favorable attribute. Stated preferences differed between patients and caregivers (p < 0.001) for range of forecasting and inaccuracy of device. Caregivers preferred any range of forecasting, regardless of length, more than patients. Patients cared less about inaccuracy of the device compared to caregivers. The groups also differ in impact of fear of having seizures (versus actually having seizures) (p = 0.034) and on device acceptance. The acceptance of devices ranged from 42.3% to 95%, with caregivers being more likely to use a device (p < 0.05) for the majority of device profiles. Acceptance of devices varied with net monetary benefit of the best device being $717.44 more per month relative to the least preferred device. CONCLUSION: Our finding extends previous calls for seizure forecasting devices by demonstrating the value that they might provide to patients and caregivers affected by epilepsy and the feature that might be most and least desirable. In addition to guiding device development, the data can help inform regulatory decisions makers.

Comorbidities of Rare Epilepsies: Results from the Rare Epilepsy Network.

OBJECTIVE: To describe the prevalence and characteristics of comorbidities in persons with rare epilepsies. STUDY DESIGN: Persons with rare epilepsies and caregivers of those affected were recruited through the Epilepsy Foundation and more than 30 rare epilepsy advocacy organizations affiliated with the Rare Epilepsy Network (REN). A web-based survey was conducted using a questionnaire consisting of core sections to collect data from affected persons on various aspects, including comorbidities. Comorbidity information was grouped into 15 classes, 12 of which had a stem question followed by detailed branch questions and 3 that were created from a combination of related questions. RESULTS: Of 795 persons with more than 30 different rare epilepsy diagnosis groups, one-half had ≥5 comorbidity classes and 97% were classified as complex chronic disease (C-CD). The highest number of comorbidity classes reported per person were persons with Aicardi syndrome, Phelan-McDermid syndrome (median, 7.0; IQR, 5.0-9.0), and tuberous sclerosis complex (median, 6.0; IQR, 4.0-8.0). The most common comorbidity classes were learning/developmental disability (71%), mental health issues (71%), sleep disorders (60%), brain abnormalities (52%), oral issues (49%), bone-joint issues (42%), hyper/hypotonia (42%), and eye-vision disorders (38%). The prevalence of brain abnormalities, hyper/hypotonia, eye, and cardiac disorders was significantly higher in persons first diagnosed with epilepsy at a younger age (<9 months) than in those first diagnosed at an older age (P < .05 for trend). CONCLUSIONS: Nearly all persons with rare epilepsies are medically complex, with a high prevalence of multiple comorbidities, especially those who were diagnosed with epilepsy in the first year of life. Comorbidities should be carefully considered in the diagnosis and management of persons with rare epilepsies.

SCN8A encephalopathy: Research progress and prospects.

On April 21, 2015, the first SCN8A Encephalopathy Research Group convened in Washington, DC, to assess current research into clinical and pathogenic features of the disorder and prepare an agenda for future research collaborations. The group comprised clinical and basic scientists and representatives of patient advocacy groups. SCN8A encephalopathy is a rare disorder caused by de novo missense mutations of the sodium channel gene SCN8A, which encodes the neuronal sodium channel Nav 1.6. Since the initial description in 2012, approximately 140 affected individuals have been reported in publications or by SCN8A family groups. As a result, an understanding of the severe impact of SCN8A mutations is beginning to emerge. Defining a genetic epilepsy syndrome goes beyond identification of molecular etiology. Topics discussed at this meeting included (1) comparison between mutations of SCN8A and the SCN1A mutations in Dravet syndrome, (2) biophysical properties of the Nav 1.6 channel, (3) electrophysiologic effects of patient mutations on channel properties, (4) cell and animal models of SCN8A encephalopathy, (5) drug screening strategies, (6) the phenotypic spectrum of SCN8A encephalopathy, and (7) efforts to develop a bioregistry. A panel discussion of gaps in bioregistry, biobanking, and clinical outcomes data was followed by a planning session for improved integration of clinical and basic science research. Although SCN8A encephalopathy was identified only recently, there has been rapid progress in functional analysis and phenotypic classification. The focus is now shifting from identification of the underlying molecular cause to the development of strategies for drug screening and prioritized patient care.

Improving Seizure Frequency Documentation and Classification.

Background and Objectives: Accurate and reliable seizure data are essential for evaluating treatment strategies and tracking the quality of care in epilepsy clinics. This quality improvement project aimed to increase seizure documentation (i.e., documentation of seizure frequency from 80% to 100%, date of last seizure from 35% to 50%, and International League Against Epilepsy (ILAE) seizure classification from 35% to at least 50%) over 6 months. Methods: We surveyed 7 epileptologists to determine their perceived seizure frequency, ILAE classification, and date of last seizure documentation habits. Baseline data were collected weekly from September to December 2021. Subsequently, we implemented a newly created flowsheet in our Electronic Health Record (EHR) based on the Epilepsy Learning Healthcare System (ELHS) Case Report Forms to increase seizure documentation in a standardized way. Two epileptologists tested this flowsheet tool in their epilepsy clinics between February 2022 and July 2022. Data were collected weekly and compared with documentation from other epileptologists within the same group. Results: Epileptologists at our center believed they documented seizure frequency for 84%-87% of clinic visits, which aligned with baseline data collection, showing they recorded seizure frequency for 83% of clinic visits. Epileptologists believed they documented ILAE classification for 47%-52% of clinic visits, and baseline data showed this was documented in 33% of clinic visits. They also reported documenting the date of the last seizure for 52%-63% of clinic visits, but this occurred in only 35% of clinic visits. After implementing the new flowsheet, documentation increased to nearly 100% for all fields being completed by the providers who tested the flowsheet. Discussion: We demonstrated that by implementing an easy-to-use standardized EHR documentation tool, our documentation of critical metrics, as defined by the ELHS, improved dramatically. This shows that simple and practical interventions can substantially improve clinically meaningful documentation.

Seizure diaries for clinical research and practice: limitations and future prospects.

PURPOSE: An NINDS-sponsored conference in April of 2011 reviewed issues in epilepsy clinical trials. One goal was to clarify new electronic methods for recording seizure information and other data in clinical trials. METHODS: This selective literature review and compilation of expert opinion considers advantages and limitations of traditional paper-based seizure diaries in comparison to electronic diaries. KEY FINDINGS: Seizure diaries are a type of patient-reported outcome. All seizure diaries depend first on accurate recognition and recording of seizures, which is a problem since about half of seizures recorded during video-EEG monitoring are not known to the patient. Reliability of recording is another key issue. Diaries may not be at hand after a seizure, lost or not brought to clinic visits. On-line electronic diaries have several potential advantages over paper diaries. Smartphones are increasingly accessible as data entry gateways. Data are not easily lost and are accessible from clinic. Entries can be time-stamped and provide immediate feedback, validation or reminders. Data can also can be graphed and pasted into an EMR. Disadvantages include need for digital sophistication, higher cost, increased setup time, and requiring attention to potential privacy issues. The Epilepsy Diary by epilepsy.com and Irody, Inc. has over 13,000 registrants and SeizureTracker over 10,000, and both are used for clinical and research purposes. Some studies have documented patient preference and increased compliance for electronic versus paper diaries. Seizure diaries can be challenging in the pediatric population. Children often have multiple seizure types and limited reporting of subjective symptoms. Multiple caregivers during the day require more training to produce reliable and consistent data. Diary-based observational studies have the advantages of low cost, allowing locus-of-control by the patient and testing in a "real-world" environment. Diary-based studies can also be useful as descriptive "snapshots" of a population. However, the type of information available is very different from that obtained by prospective controlled studies. The act of self-recording observations may itself influence the observation, for example, by causing the subject to attend more vigilantly to seizures after changing medication. Pivotal anti-seizure drug or device trials still mostly rely on paper-based seizure diaries. Industry is aware of the potential advantages of electronic diaries, particularly, the promise of real-time transmission of data, time-stamping of entries, reminders to subjects, and potentially automatic interfaces to other devices. However, until diaries are validated as research tools and the regulatory environment becomes clearer, adoption of new types of diaries as markers for a primary study outcome will be cautious. SIGNIFICANCE: Recommendations from the conference included: further studies of validity of epilepsy diaries and how they can be used to improve adherence; use and further development of core data sets, such as the one recently developed by NINDS; encouraging links of diaries to electronic sensors; development of diary privacy and legal policies; examination of special pediatric diary issues; development of principles for observational research from diaries; and work with the FDA to make electronic diaries more useful in industry-sponsored clinical trials.

Toward an ontology of collaborative learning healthcare systems.

Objective: To establish a basis for a domain ontology - a formal, explicit specification of a shared conceptualization - of collaborative learning healthcare systems (CLHSs) in order to facilitate measurement, explanation, and improvement. Methods: We adapted the "Methontology" approach to begin building an ontology of CLHSs. We specified the purpose of an ontology, acquired domain knowledge via literature review, conceptualized a common framework of CLHSs using a grounded approach, refined these concepts based on expert panel input, and illustrated concept application via four cases. Results: The set of concepts identified as important to include in an ontology includes goals, values, structure, actors, environment, and products. To establish this set of concepts, we gathered input from content experts in two ways. First, expert panel methods were used to elicit feedback on these concepts and to test the elicitation of terms for the vocabulary of the Values concept. Second, from these discussions we developed a mapping exercise to test the intuitiveness of the concepts, requesting that network leaders from four CLHSs complete a mapping exercise to associate characteristics of their networks with the high-level concepts, building the vocabulary for each concept in a grounded fashion. We also solicited feedback from these participants on the experience of completing the mapping exercise, finding that the exercise is acceptable and could aid in CLHS development and collaboration. Respondents identified opportunities to improve the operational definitions of each concept to ensure that corresponding vocabularies are distinct and non-overlapping. Discussion: Our results provide a foundation for developing a formal, explicit shared conceptualization of CLHSs. Once developed, such a tool can be useful for measurement, explanation, and improvement. Further work, including alignment to a top-level ontology, expanding the vocabulary, and defining relations between vocabulary is required to formally build out an ontology for these uses.

A replicable, open-source, data integration method to support national practice-based research & quality improvement systems.

OBJECTIVES: The Epilepsy Learning Healthcare System (ELHS) was created in 2018 to address measurable improvements in outcomes for people with epilepsy. However, fragmentation of data systems has been a major barrier for reporting and participation. In this study, we aimed to test the feasibility of an open-source Data Integration (DI) method that connects real-life clinical data to national research and quality improvement (QI) systems. METHODS: The ELHS case report forms were programmed as EPIC SmartPhrases at Mass General Brigham (MGB) in December 2018 and subsequently as EPIC SmartForms in June 2021 to collect actionable, standardized, structured epilepsy data in the electronic health record (EHR) for subsequent pull into the external national registry of the ELHS. Following the QI methodology in the Chronic Care Model, 39 providers, epileptologists and neurologists, incorporated the ELHS SmartPhrase into their clinical workflow, focusing on collecting diagnosis of epilepsy, seizure type according to the International League Against Epilepsy, seizure frequency, date of last seizure, medication adherence and side effects. The collected data was stored in the Enterprise Data Warehouse (EDW) without integration with external systems. We developed and validated a DI method that extracted the data from EDW using structured query language and later preprocessed using text mining. We used the ELHS data dictionary to match fields in the preprocessed notes to obtain the final structured dataset with seizure control information. For illustration, we described the data curated from the care period of 12/2018-12/2021. RESULTS: The cohort comprised a total of 1806 patients with a mean age of 43 years old (SD: 17.0), where 57% were female, 80% were white, and 84% were non-Hispanic/Latino. Using our DI method, we automated the data mining, preprocessing, and exporting of the structured dataset into a local database, to be weekly accessible to clinicians and quality improvers. During the period of SmartPhrase implementation, there were 5168 clinic visits logged by providers documenting each patient's seizure type and frequency. During this period, providers documented 59% patients having focal seizures, 35% having generalized seizures and 6% patients having another type. Of the cohort, 45% patients had private insurance. The resulting structured dataset was bulk uploaded via web interface into the external national registry of the ELHS. CONCLUSIONS: Structured data can be feasibly extracted from text notes of epilepsy patients for weekly reporting to a national learning healthcare system.

Common data elements in epilepsy research: development and implementation of the NINDS epilepsy CDE project.

The Common Data Element (CDE) Project was initiated in 2006 by the National Institute of Neurological Disorders and Stroke (NINDS) to develop standards for performing funded neuroscience-related clinical research. CDEs are intended to standardize aspects of data collection; decrease study start-up time; and provide more complete, comprehensive, and equivalent data across studies within a particular disease area. Therefore, CDEs will simplify data sharing and data aggregation across NINDS-funded clinical research, and where appropriate, facilitate the development of evidenced-based guidelines and recommendations. Epilepsy-specific CDEs were established in nine content areas: (1) Antiepileptic Drugs (AEDs) and Other Antiepileptic Therapies (AETs), (2) Comorbidities, (3) Electrophysiology, (4) Imaging, (5) Neurological Exam, (6) Neuropsychology, (7) Quality of Life, (8) Seizures and Syndromes, and (9) Surgery and Pathology. CDEs were developed as a dynamic resource that will accommodate recommendations based on investigator use, new technologies, and research findings documenting emerging critical disease characteristics. The epilepsy-specific CDE initiative can be viewed as part of the larger international movement toward "harmonization" of clinical disease characterization and outcome assessment designed to promote communication and research efforts in epilepsy. It will also provide valuable guidance for CDE improvement during further development, refinement, and implementation. This article describes the NINDS CDE Initiative, the process used in developing Epilepsy CDEs, and the benefits of CDEs for the clinical investigator and NINDS.

Identification of clinically relevant biomarkers of epileptogenesis - a strategic roadmap.

Onset of many forms of epilepsy occurs after an initial epileptogenic insult or as a result of an identified genetic defect. Given that the precipitating insult is known, these epilepsies are, in principle, amenable to secondary prevention. However, development of preventive treatments is difficult because only a subset of individuals will develop epilepsy and we cannot currently predict which individuals are at the highest risk. Biomarkers that enable identification of these individuals would facilitate clinical trials of potential anti-epileptogenic treatments, but no such prognostic biomarkers currently exist. Several putative molecular, imaging, electroencephalographic and behavioural biomarkers of epileptogenesis have been identified, but clinical translation has been hampered by fragmented and poorly coordinated efforts, issues with inter-model reproducibility, study design and statistical approaches, and difficulties with validation in patients. These challenges demand a strategic roadmap to facilitate the identification, characterization and clinical validation of biomarkers for epileptogenesis. In this Review, we summarize the state of the art with respect to biomarker research in epileptogenesis and propose a five-phase roadmap, adapted from those developed for cancer and Alzheimer disease, that provides a conceptual structure for biomarker research.

Factors Associated with Caregiver Sleep Quality Related to Children with Rare Epilepsy Syndromes.

Objective: To evaluate the impact of pediatric sleep disturbances and night-time seizure monitoring of children with rare epilepsy syndromes on the sleep quality and mental health of caregivers. Study design: A cross-sectional study was conducted using caregiver entered data from the Rare Epilepsy Network on pediatric sleep disturbances and Patient Reported Outcomes Measurement Information System measures for caregiver fatigue, sleep disturbance, sleep-related impairment, depression, anxiety, companionship, and cognition. Logistic regression was used to examine associations between risk factors and caregiver sleep quality. Results: Non-Hispanic white mothers comprised 83% of the 742 respondents in this study. After adjusting for covariates, difficulty falling asleep, excessive daytime sleepiness, frequent night-time awakenings, and very restless sleep in children were associated with fatigue (aOR 95% CI, 1.5-2.2), sleep-related disturbance (aOR 95% CI, 1.7-2.6) and sleep impairment (aOR 95% CI, 1.5-2.4) in caregivers. Caregiver anxiety (aOR 95% CI, 3.6-6.0) and depression (aOR 95% CI, 2.8-6.0) were also highly associated with their fatigue and sleep quality, whereas companionship (aOR 95% CI, 0.3-0.4) and higher caregiver cognition (aOR 95% CI, 0.1-0.2) were protective. In addition, sharing a room or bed or using methods that require listening for seizures were significantly related to sleep disturbance and fatigue in the caregivers. Conclusions: In rare epilepsies, pediatric sleep disturbances and night-time seizure monitoring are significantly associated with caregiver fatigue and poor sleep quality. In addition to the intense caregiving needs of children with rare epilepsies, fatigue and poor sleep quality in caregivers may contribute to or result from mental health problems.