Feasibility and utilization of a national virtual EEG course for Canadian residents and fellows.

OBJECTIVE: Electroencephalography (EEG) is an essential tool for the diagnosis and management of epilepsy. There is a gap in EEG education for residents in Canadian neurology programs as EEG is only listed in the training requirements as a procedural skill. There is currently no standardized EEG curriculum among Canadian epilepsy fellowship programs. METHODS: We conducted two iterations of a structured virtual EEG course from June to October 2021, and from March to June 2022. Trainees were recruited via Canadian neurology residency and epilepsy fellowship programs and were required to join the Canadian League Against Epilepsy (CLAE) as junior members. We obtained trainee demographic information before and after each course as well as analytical data on the video recordings posted on the CLAE website. RESULTS: A total of 77 trainees registered for the two courses; majority of trainees were adult neurology residents (34%) and adult epilepsy fellows (32%). Prior theoretical EEG teaching was reported as limited by more than half (53%) of participants. The average number of unique viewers per recorded video in 2021 was 29.7 interquartile range (16-35.5), while in 2022, the average was 22.5, interquartile range (16-28). Post-course questionnaire data revealed that 82% of participants strongly agreed that the course enhanced their knowledge. All participants were either likely (27%) or very likely (73%) to recommend the course to their peers. SIGNIFICANCE: National virtual EEG education is both feasible and accessible; therefore, this is a promising modality of teaching to meet the significant demand for high-quality EEG education among neurology trainees.

Epilepsy is associated with unmet health care needs compared to the general population despite higher health resource utilization--a Canadian population-based study.

PURPOSE: (1) To determine whether health resource utilization (HRU) and unmet health care needs differ for individuals with epilepsy compared to the general population or to those with another chronic condition (asthma, diabetes, migraine); and (2) to assess the association among epilepsy status, sociodemographic variables and HRU. METHODS: Data on HRU were assessed using the 2001-2005 Canadian Community Health Surveys, a nationally representative population-based survey. Weighted estimates of association were produced as adjusted odds ratio with 95% confidence intervals, and logistic regression was used to explore the association between sociodemographic variables and HRU in those with epilepsy. All data on disease status, HRU, and unmet health care needs were self-reported. KEY FINDINGS: Individuals with epilepsy had the highest rate of hospitalizations and the highest mean number of consultations with physicians. Despite higher rates of consultation with psychologists and social workers compared to the general population, those with epilepsy were significantly more likely to say they had unmet mental health care needs. People with epilepsy were also less likely to use dental services compared to the general population. Epilepsy was a significant predictor of HRU in logistic regression models. SIGNIFICANCE: Given the prevalence of psychiatric comorbidities in those with epilepsy, it is concerning that this group perceives unmet mental health care needs. It is also troublesome that there was decreased utilization of dental health care resources in those with epilepsy considering that these patients are more likely to have poor oral health. Although individuals with epilepsy use more health care services than the general population, this increase appears to be insufficient to address their health care needs.

How accurate is ICD coding for epilepsy?

PURPOSE: Assess the validity of ICD-9-CM and ICD-10 epilepsy coding from an emergency visit (ER) and a hospital discharge abstract database (DAD). METHODS: Two separate sources of patient records were reviewed and validated. (1) Charts of patients admitted to our seizure monitoring unit over 2 years (n = 127, ICD-10 coded records) were reviewed. Sensitivity (Sn), specificity (Sp), and positive and negative predictive values (PPV and NPV) were calculated. (2) Random sample of charts for patients seen in the ER or admitted to hospital under any services, and whose charts were coded with epilepsy or an epilepsy-like condition, were reviewed. Two time-periods were selected to allow validation of both ICD-9-CM (n = 486) and ICD-10 coded (n = 454) records. Only PPV and NPV were calculated for these records. All charts were reviewed by two physicians to confirm the presence/absence of epilepsy and compare to administrative coding. RESULTS: Sample 1: Sn, Sp, PPV, and NPV of ICD-10 epilepsy coding from the seizure monitoring unit (SMU) chart review were 99%, 70%, 85%, and 97% respectively. Sample 2: The PPV and NPV for ICD-9-CM coding from the ER database were, respectively, 99% and 97% and from the DAD were 98% and 99%. The PPV and NPV for ICD-10 coding from the ER database were, respectively, 100% and 90% and from the DAD were 98% and 99%. The epilepsy subtypes grand mal status and partial epilepsy with complex partial seizures both had PPVs >75% (ICD-9-CM and ICD-10 data). DISCUSSION: Administrative emergency and hospital discharge data have high epilepsy coding validity overall in our health region.