Samuel Waller Terman1,2, Wesley T Kerr3,4, Carole E Aubert5,6, Chloe E Hill3,2, Zachary A Marcum7, James F Burke3,2. 1. University of Michigan Department of Neurology, Ann Arbor, MI sterman@umich.edu. 2. University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor, MI. 3. University of Michigan Department of Neurology, Ann Arbor, MI. 4. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA. 5. Department of General Internal Medicine, Bern University Hospital, University of Bern, Bern, Switzerland. 6. Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland. 7. Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA.
Abstract
OBJECTIVE: To 1) compare adherence to antiseizure medications (ASMs) versus non-ASMs among individuals with epilepsy, 2) assess the degree to which variation in adherence is due to differences between individuals versus between medication classes among individuals with epilepsy, and 3) compare adherence in individuals with versus without epilepsy. METHODS: This was a retrospective cohort study using Medicare. We included beneficiaries with epilepsy (≥1 ASM, plus International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes), and a 20% random sample without epilepsy. Adherence for each medication class was measured by the proportion of days covered (PDC) in 2013-2015. We used Spearman correlation coefficients, Cohen's kappa statistics, and multilevel logistic regressions. RESULTS: There were 83,819 beneficiaries with epilepsy. Spearman correlation coefficients between ASM PDCs and each of the 5 non-ASM PDCs ranged 0.44-0.50, Cohen's kappa ranged 0.33-0.38, and within-person differences between each ASM's PDC minus each non-ASM's PDC were all statistically significant (p<0.01) though median differences were all very close to 0. Fifty-four percent of variation in adherence across medications was due to differences between individuals. Adjusted predicted probabilities of adherence were: ASMs 74% (95% confidence interval [CI] 73%-74%), proton pump inhibitors 74% (95% CI 74%-74%), antihypertensives 77% (95% CI 77%-78%), selective serotonin reuptake inhibitors 77% (95% CI 77%-78%), statins 78% (95% CI 78%-79%), and levothyroxine 82% (95% CI 81%-82%). Adjusted predicted probabilities of adherence to non-ASMs were 80% (95% CI 80%-81%) for beneficiaries with epilepsy versus 77% (77%-77%) for beneficiaries without epilepsy. CONCLUSION: Among individuals with epilepsy, ASM and non-ASM adherence were moderately correlated, half of variation in adherence was due to between-person rather than between-medication differences, adjusted adherence was slightly lower for ASMs than several non-ASMs, and epilepsy was associated with a quite small increase in adherence to non-ASMs. Nonadherence to ASMs may provide an important cue to the clinician to inquire about adherence to other potentially life-prolonging medications as well. Although efforts should focus on improving ASM adherence, patient-level rather than purely medication-specific behaviors are also critical to consider when developing interventions to optimize adherence.
OBJECTIVE: To 1) compare adherence to antiseizure medications (ASMs) versus non-ASMs among individuals with epilepsy, 2) assess the degree to which variation in adherence is due to differences between individuals versus between medication classes among individuals with epilepsy, and 3) compare adherence in individuals with versus without epilepsy. METHODS: This was a retrospective cohort study using Medicare. We included beneficiaries with epilepsy (≥1 ASM, plus International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes), and a 20% random sample without epilepsy. Adherence for each medication class was measured by the proportion of days covered (PDC) in 2013-2015. We used Spearman correlation coefficients, Cohen's kappa statistics, and multilevel logistic regressions. RESULTS: There were 83,819 beneficiaries with epilepsy. Spearman correlation coefficients between ASM PDCs and each of the 5 non-ASM PDCs ranged 0.44-0.50, Cohen's kappa ranged 0.33-0.38, and within-person differences between each ASM's PDC minus each non-ASM's PDC were all statistically significant (p<0.01) though median differences were all very close to 0. Fifty-four percent of variation in adherence across medications was due to differences between individuals. Adjusted predicted probabilities of adherence were: ASMs 74% (95% confidence interval [CI] 73%-74%), proton pump inhibitors 74% (95% CI 74%-74%), antihypertensives 77% (95% CI 77%-78%), selective serotonin reuptake inhibitors 77% (95% CI 77%-78%), statins 78% (95% CI 78%-79%), and levothyroxine 82% (95% CI 81%-82%). Adjusted predicted probabilities of adherence to non-ASMs were 80% (95% CI 80%-81%) for beneficiaries with epilepsy versus 77% (77%-77%) for beneficiaries without epilepsy. CONCLUSION: Among individuals with epilepsy, ASM and non-ASM adherence were moderately correlated, half of variation in adherence was due to between-person rather than between-medication differences, adjusted adherence was slightly lower for ASMs than several non-ASMs, and epilepsy was associated with a quite small increase in adherence to non-ASMs. Nonadherence to ASMs may provide an important cue to the clinician to inquire about adherence to other potentially life-prolonging medications as well. Although efforts should focus on improving ASM adherence, patient-level rather than purely medication-specific behaviors are also critical to consider when developing interventions to optimize adherence.
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