Implementer report: ICD-10 code F44.5 review for functional seizure disorder.

OBJECTIVE: The study aimed to measure the validity of International Classification of Diseases, 10th Edition (ICD-10) code F44.5 for functional seizure disorder (FSD) in the Veterans Affairs Connecticut Healthcare System electronic health record (VA EHR). METHODS: The study used an informatics search tool, a natural language processing algorithm and a chart review to validate FSD coding. RESULTS: The positive predictive value (PPV) for code F44.5 was calculated to be 44%. DISCUSSION: ICD-10 introduced a specific code for FSD to improve coding validity. However, results revealed a meager (44%) PPV for code F44.5. Evaluation of the low diagnostic precision of FSD identified inconsistencies in the ICD-10 and VA EHR systems. CONCLUSION: Information system improvements may increase the precision of diagnostic coding by clinicians. Specifically, the EHR problem list should include commonly used diagnostic codes and an appropriately curated ICD-10 term list for 'seizure disorder,' and a single ICD code for FSD should be classified under neurology and psychiatry.

Prevalence and Predictors of Seizure Clusters in Pediatric Patients With Epilepsy: The Harvard-Yale Pediatric Seizure Cluster Study.

BACKGROUND: Determine the prevalence of seizure clusters (two or more seizures in six hours), use of rescue medications, and adverse outcomes associated with seizure clusters in pediatric patients with a range of epilepsy severities, and identify risk factors predictive of seizure clusters. METHODS: Prospective observational two-center study, including phone call and seizure diary follow-up for 12 months in patients with epilepsy aged one month to 18 years. We classified patients into three risk groups based on seizures within the prior year: high, seizure cluster (two or more seizures within one day); intermediate, at least one seizure but no days with two or more seizures; low, no seizures. RESULTS: One-third (32.3%; high risk, 72.4%; intermediate risk, 30.4%; low risk, 3.1%) of 297 patients had a seizure cluster during the study, including half (46.2%) of the patients with active seizures at baseline (intermediate- and high-risk groups combined). Emergency room visits or injuries were no more likely due to a seizure cluster than an isolated seizure. Rescue medications were utilized in 15.8% of patients in the high-risk group and 19.2% in the intermediate-risk group. History of status epilepticus (adjusted odds ratio [aOR], 2.13; confidence interval [CI], 1.09 to 4.16]), seizure frequency greater than four per month (aOR, 4.27; CI, 1.92 to 9.50), and high-risk group status (aOR, 6.42; CI, 2.97 to 13.87) were associated with greater odds of seizure cluster. CONCLUSIONS: Seizure clusters are common in pediatric patients with epilepsy. High seizure frequency was the strongest predictor of clusters. Rescue medications were underutilized. Future studies should evaluate the applicability and effectiveness of these medications for optimization of pediatric seizure cluster treatment and reduction of seizure-related emergency department visits, injuries, and mortality.

Suicide and Seizures: A National Cohort Study in Veterans.

OBJECTIVE: The increased rate of suicide associated with epilepsy has been described, but no studies have reported the rates of suicide and suicide-related behavior (SRB) associated with psychogenic nonepileptic seizures (PNESs). METHODS: This retrospective cohort study analyzed data from October 2002 to October 2017 within Veterans Health Administration services. Of 801,734 veterans, 0.09% had PNES, 1.37% had epilepsy, and 98.5% had no documented seizures. Veterans coded for completed suicide, suicide attempts, and suicidal ideation were identified from electronic health records. The primary measure was the suicide-specific standardized mortality ratio (SMR) based on the number of suicide deaths and CDC national suicide mortality database. A Poisson regression was used to calculate the relative risk (RR) of suicide across groups. RESULTS: A total of 1,870 veterans (mean age [SD] 33.76 [7.81] years) completed suicide. Veterans with PNES (RR = 1.75, 95% confidence interval [CI] 0.84-4.24) and veterans with epilepsy (RR = 2.19, 95% CI 2.10-2.28) had a higher risk of suicide compared with the general veteran population. Veterans with PNES or epilepsy had a higher risk of suicide and SRB if they had comorbid alcohol abuse, illicit drug abuse, major depression, posttraumatic stress disorder, and use of psychotropic medications. Conversely, those who were married or attained higher education were at a decreased risk. The SMR for completed suicide for PNES, epilepsy, and the comparison group was 2.65 (95% CI 1.95-5.52), 2.04 (95% CI 1.60-2.55), and 0.70 (95% CI 0.67-0.74), respectively. CONCLUSIONS: Veterans with seizures (both psychogenic and epileptic) are at a greater risk of death by suicide and SRB than the comparison group. These findings suggest that although the pathophysiology of PNES and epilepsy is different, the negative impact of seizures is evident in the psychosocial outcomes in both groups.

Managing Functional Neurological Disorders: Protocol of a Cohort Study on Psychogenic Non-Epileptic Seizures Study.

BACKGROUND: Functional neurological disorders (FNDs) are neurological symptoms that cannot be explained by an underlying neurological lesion or other medical illness and that do not have clear neuropathological correlates. Psychogenic non-epileptic seizures (PNES) are a common and highly disabling form of FND, characterized by paroxysmal episodes of involuntary movements and altered consciousness that can appear clinically similar to epileptic seizures. PNES are unique among FNDs in that they are diagnosed by video electroencephalographic (VEEG), a well-established biomarker for the disorder. The course of illness and response to treatment of PNES remain controversial. This study aims to describe the epidemiology of PNES in the Department of Veterans Affairs Healthcare System (VA), evaluate outcomes of veterans offered different treatments, and compare models of care for PNES. METHODS: This electronic health record (EHR) cohort study utilizes an informatics search tool and a natural language processing algorithm to identify cases of PNES nationally. We will use VA inpatient, outpatient, pharmacy, and chart abstraction data across all 170 medical centers to identify cases in fiscal years 2002-2018. Outcome measurements such as seizure frequency, emergency room visits, hospital admissions, suicide-related behavior, and the utilization of psychotherapy prior to and after PNES diagnosis will be used to assess the effectiveness of models of care. DISCUSSION: This study will describe the risk factors and course of treatment of a large cohort of people with PNES. Since PNES are cared for by a variety of different modalities, treatment orientations, and models of care, effectiveness outcomes such as seizure outcomes and utilization of emergency visits for seizures will be assessed. Outcome measurements such as seizure frequency, emergency room visits, hospital admissions, suicide-related behavior, and psychotherapy prior to and after PNES diagnosis will be used to assess the effectiveness of models of care.