Readmission after epilepsy monitoring unit discharge in a nationally representative sample

Polypharmacy composition and patient- and provider-related variation in patients with epilepsy

OBJECTIVE

To describe polypharmacy composition, and the degree to which patients versus providers contribute to variation in medication fills, in people with epilepsy.

METHODS

We performed a retrospective study of Medicare beneficiaries with epilepsy (antiseizure medication plus diagnostic codes) in 2014 (N = 78,048). We described total number of medications and prescribers, and specific medications. Multilevel models evaluated the percentage of variation in two outcomes (1. number of medications per patient-provider dyad, and 2. whether a medication was filled within thirty days of a visit) due to patient-to-patient differences versus provider-to-provider differences.

RESULTS

Patients filled a median of 12 (interquartile range [IQR] 8-17) medications, from median of 5 (IQR 3-7) prescribers. Twenty-two percent filled an opioid, and 61% filled at least three central nervous system medications. Levetiracetam was the most common medication (40%), followed by hydrocodone/acetaminophen (27%). The strongest predictor of medications per patient was Charlson comorbidity index (7.5 [95% confidence interval (CI) 7.2-7.8] additional medications for index 8+ versus 0). Provider-to-provider variation explained 36% of variation in number of medications per patient, whereas patient-to-patient variation explained only 2% of variation. Provider-to-provider variation explained 57% of variation in whether a patient filled a medication within 30 days of a visit, whereas patient-to-patient variation explained only 30% of variation.

CONCLUSION

Patients with epilepsy fill a large number of medications from a large number of providers, including high-risk medications. Variation in medication fills was substantially more related to provider-to-provider rather than patient-to-patient variation. The better understanding of drivers of high-prescribing practices may reduce avoidable medication-related harms.

Hospital readmissions in older adults with epilepsy in the US - A population-based study

OBJECTIVE

Our objective was to determine proportions, causes, and predictors of 30-day readmissions among older adults with epilepsy. Understanding predictors of readmissions may inform future interventions aimed at reducing avoidable hospitalizations in this vulnerable population.

METHODS

Individuals 65 years or older with epilepsy were identified using previously validated ICD-9-CM codes in any diagnostic position in the 2014 Nationwide Readmissions Database. Proportions of 30-day readmissions and causes of readmissions in older adults with epilepsy were compared to both older adults without and younger adults (18-64 years old) with epilepsy. We identified predictors of readmission in older adults with epilepsy using logistic regression.

RESULTS

There were 92,030 older adults with, 3,166,852 older adults without, and 168,622 younger adults with epilepsy. Proportions of readmissions were higher in older adults with (16.2%) than older adults without (12.5%) and younger adults with epilepsy (15.1%). The main cause of readmission for older adults with and without epilepsy was septicemia, and epilepsy/seizure in younger adults with epilepsy. Predictors of 30-day readmissions in older adults with epilepsy were: non-elective admissions (OR 1.37, 95%CI 1.27-1.48), public insurance (Medicaid vs. private insurance OR 1.19, 95%CI 1.02-1.39; Medicare vs. private insurance OR 1.11, 95%CI 1.00-1.22), lower median household income for patient's zip code ($1-$39,999 vs. $66,000 + OR 1.15, 95% CI 1.08-1.22), hospital location in large metropolitan areas (OR 1.22, 95%CI 1.05-1.42), higher Charlson-Deyo comorbidity index (OR 1.11, 95%CI 1.10-1.02), and male sex (OR 1.04, 95%CI 1.00-1.09).

SIGNIFICANCE

Our findings suggest that targeted interventions to reduce the risk of infection may potentially reduce readmission in older people with epilepsy, similarly to those without. Provision of coordinated care and appropriate discharge planning may reduce readmissions particularly in those who are males, are of lower socioeconomic status and with more comorbidities.