Utility of mental health and sleep screening questionnaires for patients admitted to a seizure monitoring unit.

RATIONALE: Patients with seizure disorders have relatively high rates of comorbid psychological and sleep disorders. Because these can profoundly affect quality of life, early recognition and treatment are of potential benefit. As a quality improvement project, we evaluated the performance and utility of a set of mental health and sleep quality screening questionnaires in patients admitted to a VA seizure monitoring unit (SMU). METHODS: Questionnaires, including the Beck Depression Inventory-II (BDI-II), the post-traumatic stress disorder (PTSD) checklist (PCL), the Quality of Life in Epilepsy Inventory-31 (QOLIE-31), and the Pittsburgh Sleep Quality Index (PSQI), were administered to 100 patients admitted to the Portland VAMC SMU. Scored results were entered into the electronic medical record (EMR) within 72 h of hospital admission. We assessed how many patients exceeded questionnaire cutoff scores, and whether these patients had prior mental health or sleep diagnoses or evaluations within the six months preceding admission. Following hospital discharge, providers completed a survey regarding the utility of the questionnaire results. We also reviewed EMR documented mental health and sleep visits during the six months following the SMU admission. RESULTS: Forty-seven patients (47.5%) exceeded the cutoff score for the BDI-II, including 15 without an admission diagnosis of depression, and 14 who had not seen a mental health provider in the previous six months. Similarly, 33 patients (33.3%) exceeded the cutoff score for the PCL, including nine without a diagnosis of PTSD. Scores on the BDI-II and PCL were highly correlated with the QOLIE-31 total score (r = 0.7). Seventy patients (70.7%) exceeded the cutoff score for poor sleep quality, and 37 did not have a sleep disorder diagnosis. Providers indicated that the questionnaire results were moderately or very helpful in most cases and influenced discharge recommendations to patients and referring providers in more than 50% of cases. Discharge recommendations for mental health or sleep follow-up were associated with EMR documented consultations within the six months following SMU admission. CONCLUSIONS: The results suggest that a standard set of screening questionnaires can identify SMU patients at risk for mental health and sleep disorders, including patients not currently diagnosed or recently evaluated. Questionnaire results were perceived as helpful by providers and influenced discharge recommendations. Given that these disorders are treatable and have a major influence on health-related quality of life, the effort to collect and document this information is well justified.

Health care utilization following diagnosis of psychogenic nonepileptic seizures.

OBJECTIVES: The long-term outcome of patients with psychogenic nonepileptic seizures (PNES) is of importance given the disabling symptoms and tendency to affect patients early in their productive years. Health care utilization (HCU) is an important outcome measure reflecting overall health status and costs. There is little information regarding long-term HCU following diagnosis of PNES. METHODS: We retrospectively reviewed records of Veterans diagnosed with PNES during epilepsy monitoring unit (EMU) evaluation. For the three-year period following diagnosis of PNES, we reviewed emergency department (ED) visits, hospitalizations, outpatient clinic visits, and radiology procedures. We compared the three years following PNES diagnosis with the three years preceding diagnosis. We also compared patients with PNES and patients with epileptic seizures (ES). RESULTS: Emergency department visits and hospitalizations were more frequent in patients with PNES compared with those in patients with ES (p=0.01). There was no overall improvement in HCU during the three-year interval following diagnosis of PNES. A transient decrease during the year following diagnosis was not sustained over three-year follow-up. Pain complaints rather than seizures were the most common reason for presentation, whereas the opposite was true for patients with ES (p<0.01). There was a sharp decrease in neurology outpatient visits (p<0.001) and a decrease in primary care visits (p<0.05) after PNES was diagnosed. Total outpatient visits were unchanged. CONCLUSIONS: Overall HCU did not improve during the three years following diagnosis of PNES, compared with three years preceding diagnosis. The results add to studies documenting poor seizure outcomes following diagnosis of PNES and underscore the need for more effective and comprehensive treatments, addressing comorbid symptoms.

Providers' perspectives on treating psychogenic nonepileptic seizures: frustration and hope.

Recent diagnostic and treatment advances in psychogenic nonepileptic seizures (PNES) have the potential to improve care for patients, but little is known about the current state of PNES care delivery in the Veterans Health Administration (VA). We conducted semistructured interviews with 74 health-care clinicians and workers in the VA, eliciting provider perceptions of PNES care. Data were analyzed according to principles of Grounded Theory. The results revealed variation in care and two emergent domain themes of frustration and hope. Frustration was manifest in subthemes including Complexity, Patient Acceptance, Uncertainty About Treatment, Need for Evidence-based Treatment, and Failure of Cross-Disciplinary Collaboration between neurologists and mental health providers. Hope encompassed subthemes of Positive Attitudes, Developing Cross-Disciplinary Treatment, and Specific PNES Care. Increased resources for diagnosing, treating, and researching PNES have improved awareness of the disorder. More research is needed to understand patients' and caregivers' perceptions of PNES care.

Assessment of CNS effects of antiepileptic drugs by using quantitative EEG measures.

PURPOSE: Antiepileptic drugs (AEDs) can be associated with adverse neurologic effects including cognitive dysfunction. Objective methods for recognizing AED effects on the brain could be valuable for long-term management. We compared quantitative EEG measures and cognitive tests in a group of patients beginning or ending AED therapy. METHODS: Subjects included 20 patients beginning AED therapy (AEDon), 12 patients stopping AED therapy (AEDoff), 33 patient controls receiving stable AED therapy (AEDco), and 73 healthy controls (Nco). All subjects underwent structured EEG recording and a cognitive test battery before change in AED dose and again 12-16 weeks later, >or=4 weeks after the last dose change. Four occipital EEG measures (peak frequency, median frequency, relative theta and delta power) were analyzed. Cognitive test changes were scored by using test-retest regression equations based on the Nco subjects. Wilcoxon tests were used for two-group comparisons. RESULTS: AEDons had a significant decrease, and AEDoffs, a significant increase in the peak frequency of the EEG rhythm, as compared with controls. Results for median frequency and theta power were similar. Change in the EEG peak frequency correlated with an aggregate cognitive change measure (r2= 0.71; p < 0.001), individual cognitive measures, and subjective complaints. Of the combined AEDon/AEDoff patients, 58% exceeded the 95% confidence interval for test-retest change in EEG peak frequency. CONCLUSIONS: Quantitative measures derived from the occipital EEG are sensitive to AEDs and correlate with AED-related cognitive effects and subjective complaints. Although this correlation does not indicate a direct relation, quantified EEG may be a practical measure of AED impact on the brain.