Factors associated with utilization of healthcare resources among epilepsy patients

Epilepsy Res. 2008 May;79(2-3):120-9. doi: 10.1016/j.eplepsyres.2008.01.003. Epub 2008 Mar 12.

Abstract

Purpose: To determine those variables associated with utilization of healthcare resources in epilepsy patients.

Methods: We interviewed 256 epilepsy patients. Target variables included the number of clinic visits, ER visits and in-patient admissions over the past year and AEDs currently being used. Predictor variables were age, race/ethnicity, marital status, education, income, insurance, seizure frequency and QOLIE-10 results. We used univariate analysis to determine those factors associated with the target variables and multivariate analysis to ascertain those independently significant.

Results: On univariate analysis, higher seizure frequency and poorer QOLIE-10 scores were associated with the number of clinic visits, ER visits and in-patient admissions. Increased seizure frequency and male gender were associated with higher use of AEDs. Using ordinal logistic regression, QOLIE-10 scores was the only variable associated with the number of clinic visits. Both seizure frequency and QOLIE-10 scores were independently associated with the number of in-patient admissions while seizure frequency and male gender remained independently associated with AED use. Using binary logistic regression, QOLIE-10 scores and seizure frequency were independently associated with the number of ER visits.

Conclusion: Seizure frequency and quality of life are major factors associated with utilization of healthcare resources in epilepsy patients.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Ambulatory Care / statistics & numerical data
  • Anticonvulsants / therapeutic use
  • Data Interpretation, Statistical
  • Drug Utilization
  • Epilepsy / economics*
  • Epilepsy / epidemiology
  • Female
  • Health Resources / statistics & numerical data*
  • Hospitalization / statistics & numerical data
  • Humans
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Sex Factors
  • Socioeconomic Factors
  • United States / epidemiology

Substances

  • Anticonvulsants