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Health disparities in medication adherence between African-Americans and Caucasians with epilepsy
Epilepsy & Behavior 22 (2011) 495–498
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Epilepsy & Behavior j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / ye b e h
Health disparities in medication adherence between African-Americans and Caucasians with epilepsy Ramon Edmundo D. Bautista ⁎, Catrina Graham, Shahbuddin Mukardamwala Comprehensive Epilepsy Program, Department of Neurology, University of Florida Health Sciences Center/Jacksonville, Jacksonville, FL, USA
a r t i c l e
i n f o
Article history: Received 16 April 2011 Revised 23 July 2011 Accepted 25 July 2011 Available online 9 September 2011 Keywords: Adherence African-Americans Antiepileptic drugs Caucasians Compliance Epilepsy Health disparities Medication possession ratio Racial disparities Seizure disorder
a b s t r a c t Objective: The goal of this study was to determine whether racial disparities exist with respect to adherence to antiepileptic drugs (AEDs) in patients with epilepsy. Method: We reviewed the pharmacy and clinical records of 108 patients with epilepsy who were part of the indigent care program at Shands–Jacksonville. We determined the medication possession ratio (MPR) for each patient and obtained other demographic and clinical variables. Using univariate analysis we determined which variables were associated with the MPR and used multiple linear regression to determine those that best predicted the MPR. Results: Compared with Caucasians, African-Americans had poorer (lower) MPRs (0.872 for Caucasians vs 0.796 for African-Americans, P = 0.02). Age, gender, high school education, epilepsy classification, seizure freedom, number of AEDs, AED copayment scheme, and number of refills were not significantly affected by race. On stepwise multiple linear regression, race alone best predicted the MPR. Conclusion: Compared with Caucasians, African-Americans have significantly poorer AED adherence, as measured by the MPR. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Epilepsy is a common medical condition affecting nearly 1% of the population [1]. Because of advances in treatment, the majority of patients with epilepsy now have improved seizure control [2]. Recently, attention has turned toward disparities in epilepsy care. The incidence of epilepsy was shown to be higher in African-Americans than in Caucasians [3], and mortality remains higher among non-Caucasians [4]. African-Americans are also more likely to be diagnosed in nonspecialized environments, thus increasing their chances of receiving suboptimal care [5]. Our group recently published a study indicating that AfricanAmericans with epilepsy had poorer scores on the Beliefs about Medicines Questionnaire (BMQ), indicating increased hostility toward and resistance to the use of prescription drugs [6]. Poorer BMQ scores have been associated with poor medication adherence [7]. Snodgrass and colleagues earlier intimated a disparity in medication adherence among patients with epilepsy when they found significantly more nondetectable antiepileptic drug (AED) levels among non-Caucasian (predominantly African-American) children [8]. However, currently ⁎ Corresponding author at: Department of Neurology, University of Florida HSC/Jacksonville, 580 West Eighth Street, Tower One, Ninth Floor, Jacksonville, FL 32209, USA. E-mail address: [email protected]fl.edu (R.E.D. Bautista). 1525-5050/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.yebeh.2011.07.032
there is no study that measures adherence using other acceptable measures such as the medication possession ratio [9]. Such a study would need to control for many factors that potentially confound analysis of adherence, such as heterogeneous socioeconomic status, poor access to medications, and use of multiple pharmacy sites. We attempt to control for these variables by focusing our analysis on a group of patients who have a relatively homogeneous socioeconomic status, have easier access to medications, and receive their medications at a single pharmacy site. Controlling these variables allows us to determine whether race is independently associated with adherence to AEDs. 2. Methods This study was approved by the Institutional Review Board of the University of Florida Health Sciences Center/Jacksonville (UFHSCJ). We reviewed Shands–Jacksonville (UFHSCJ teaching hospital) pharmacy prescription and refill information from January 1, 2006 until December 31, 2010 of patients enrolled in the First Care (indigent) Program who received AEDs for treatment of seizures. The First Care Program is the indigent care program of Shands–Jacksonville and the City of Jacksonville. To be enrolled in the First Care Program, patients had to be residents of Duval County and had to have an annual houseshold income of no more than 200% poverty level. Those whose incomes were 100% poverty level or lower did not have a copay for their prescriptions. First
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Care Program recipients receive medications from a single pharmacy located within Shands–Jacksonville using a set formulary at 30-day refills. AEDs included in the First Care formulary are carbamazepine, ethosuximide, gabapentin, lacosamide, lamotrigine, levetiracetam, oxcarbazepine, phenobarbital, phenytoin, pregabalin, primidone, valproate, tiagabine, topiramate, valproic acid, and zonisamide. To be included in the study, subjects had to be First Care Program recipients and had to have been prescribed AEDs in the period under consideration. On the basis of medical record review, these patients had a diagnosis of epilepsy and were prescribed AEDs by University of Florida/Jacksonville neurologists for this condition. Patients with a history of nonepileptic seizures or who received AEDs for nonepilepsy indications were excluded from the study. By limiting our study to recipients of the First Care Program we were able to focus on patients of a relatively similar socioeconomic status who received their medications from a single pharmacy site and had relatively easy access to AEDs. Because of this, many potential confounders to data analysis were removed. Using pharmacy records, we calculated the medication possession ratio (MPR) [9]. The MPR is an accepted index of medication adherence and is defined as the number of days between prescription refills (30 days for our patient population) divided by the actual number of days between prescription refills. For example, a patient who refilled his or her prescriptions every 36 days would, on average, have a MPR of 30/36, or 0.83. We averaged the MPR of each AED prescription and across various AEDs to obtain the mean MPR for each patient. We also used pharmacy records to determine the number of AEDs patients were using (1, 2, N2), whether they had no to partial copays, and the number of AED refills they had. We reviewed the medical records to obtain demographic and clinical information: current age in years, gender, race (AfricanAmerican, Caucasian), epilepsy classification (idiopathic generalized, cryptogenic localization-related, symptomatic localization-related, symptomatic generalized), and seizure status (seizure free or having seizures) for at least 2 years preceding the time of the last clinic visit. We also obtained each patient's zip code to estimate the likelihood of graduating from high school given the 2000 US census data [10]. 2.1. Statistical analysis Statistical analysis was performed at a 5% level of significance using a two-tailed test with SPSS Version 15.0. MPR was the target variable, and the remaining demographic, clinical, and pharmacy data were the predictor variables. Transformation of interval variables was performed, if necessary, to satisfy the assumptions of normality. Using Pearson's R, we determined whether there was a significant association between the MPR and the different interval predictor variables (age, high school education, and number of refills). ANOVA was employed to determine whether the MPR differed according to the subgroups of various categorical and ordinal variables (gender, race, high school education, epilepsy classification, number of AEDs, and AED copay category). We employed stepwise multiple linear regression to determine which group of predictor variables was best associated with the MPR. 3. Results 3.1. Descriptive data One hundred eight patients met the inclusion criteria and were included in this study. Table 1 summarizes the characteristics of our study sample. The mean age of subjects was 42 years, and 55% were males. Fifty-five percent of subjects were Caucasians, and 45% were African-Americans. Three Caucasian patients were of Hispanic descent. There were no African-Americans of Hispanic descent. Around threequarters of patients were estimated to have completed high school.
Table 1 Descriptive data. Number of subjects Mean (SD) age, years Males Race Caucasians African-Americans High school educationa Epilepsy classificationb Idiopathic generalized Cryptogenic localization-related Symptomatic localization-related Symptomatic generalized Seizure freedom (≥2 years) Number of AEDs One Two More than two AED payment scheme Full charity Partial pay Mean (SD) number of refills Mean (SD) medication possession ratio
108 42.3 (11.4) 59 (54.6%) 59 (54.6%) 49 (45.4%) 76.3 (10.7) 6 (5.6%) 67 (62%) 34 (31.5%) 1 (0.9%) 22 (20.4%) 73 (67.6%) 33 (30.6%) 2 (1.9%) 87 21 10.4 0.84
(80.6%) (19.4%) (11.7) (0.2)
Note. Values are expresssed as n (%) unless otherwise indicated. a Estimated from 2000 U.S. census data. b International League Against Epilepsy Classification, 1989.
The majority of patients had cryptogenic localization-related epilepsy (62%), were not seizure free (80%), and were taking only one AED (67%). More than 80% of subjects had no copay and an average of 10 refills (range: 1–77). The MPR for all patients was 0.84. To normalize the interval data, we performed a logarithmic transformation of the MPR, lg(1.2 – MPR), and a square-root transformation of the number of refills. 3.2. Univariate analysis On univariate analysis, race was the only predictor variable that was significantly associated with MPR scores (P = 0.02) (Table 2). The MPR was 0.872 for Caucasians and 0.796 for African-Americans (Fig. 1). Age, gender, high school education, race, epilepsy classification, seizure freedom, number of AEDs, AED payment scheme, and number of refills were not significantly associated with MPR. The mean difference in MPR between African-Americans and Caucasians (0.076) translates into a difference of 2.3 days when filling a 30-day prescription. 3.3. Multivariate analysis Under stepwise multiple linear regression, a significant model emerged (F[1,103] = 5, P = 0.037, adjusted R 2 = 0.033) (Table 3). After incorporating our predictor variables into the analysis, race Table 2 Association between medication possession ratioa and predictor variables. Predictor variable
P value
Age Gender Race High school education International League Against Epilepsy Classification, 1989 Seizure freedom Number of AEDs AED payment scheme Number of refillsd
0.60b 0.81c 0.02c 0.85b 0.68c 0.18c 0.80c 0.97c 0.32b
a b c d
Data transformation: lg(1.2 – mean MPR). Pearson R. ANOVA. Data transformation: square root.
R.E.D. Bautista et al. / Epilepsy & Behavior 22 (2011) 495–498
Mean Medication Possession Ratio
0.88
0.872
0.86 0.84 0.82 0.796
0.8 0.78 0.76 0.74 Caucasians
African-Americans
Fig. 1. Comparison of medication possession ratios (MPRs) of Caucasians and AfricanAmericans. P = 0.02, ANOVA using transformed data: lg(1.2 – mean MPR) .
remained the only variable significantly associated with MPR (β = 0.205, P = 0.037). Age, gender, high school education, epilepsy classification, seizure control, number of AEDs used, copay status, and number of refills were not significant predictors of MPR (Table 3). 4. Discussion Our study shows that the MPR differs significantly among Caucasians and African-Americans with epilepsy: MPR values of Caucasians are higher than those of African-Americans, indicating better medication adherence. Our multiple linear regression model reveals that race alone (being African-American or Caucasian) can be used to predict medication adherence, although the low adjusted R2 (0.037) indicates that other variables not included in this study also influence MPR. Our study is similar to those of others who have noted poorer medication adherence among African-Americans across several disease states. In a study of veterans with hypertension who had good access to health care, African-Americans had poorer blood pressure control as well as increased odds of being nonadherent to their medications [11]. In another study, African-American veterans had poorer MPRs compared with non-Hispanic Caucasians [12]. Racial inequalities in epilepsy care have also been documented. African-Americans were less likely than non-Hispanic whites to undergo epilepsy surgery [13] and had worse outcomes following temporal lobe surgery [14]. As mentioned earlier, rates of undetectable AED serum levels were significantly higher in pediatric non-Caucasian (predominantly African-American) patients with epilepsy [8]. Our study adds to the existing literature comparing adherence among races by using another widely used measure, the MPR. We studied a group of patients of a similar socioeconomic class who were beneficiaries of our indigent care program and were residents of Table 3 Multiple linear regression of variables associated with medication possession ratioa. Variable Constant Race Age High school education International League Against Epilepsy classification, 1989 Gender Seizure freedom Number of AEDs AED payment scheme Number of refillsb
B
Significance
–0.64 0.10 –0.52 0.14
b 0.01 0.037 0.6 0.21
–0.09 b–0.01 0.12 0.07 0.01 –0.08
0.36 0.95 0.24 0.46 0.91 0.43
Note. P = 0.25. Method: stepwise. a Data transformation: lg(1.2 – mean MPR). b Data transformation: square root.
β
95% CI for B
0.205
0.006–0.19
497
Jacksonville, FL, USA. Our findings complement the results of our earlier study that revealed poorer scores on the Beliefs about Medicines questionnaire among African-American patients with epilepsy, compared with Caucasians, indicating more hostile attitudes towards prescription medications. On the basis of a self-reported survey, this same group of African-American patients had poorer seizure control compared with Caucasians [6]. An earlier study by Swarztrauber and colleagues [15] indicated that African-Americans with refractory epilepsy had higher levels of mistrust of their health care providers. The results of these studies emphasize the need to develop a program designed to enhance patient compliance with AEDs, particularly among African-Americans. Programs that help improve patients’ attitudes toward medication use have been successfully implemented for other diseases. Using a program that incorporates patient education and active participation of the physician and patient in the treatment process, patients with depression developed more favorable attitudes toward the use of antidepressants [16]. In another study, a pharmacist-led patient educational program significantly improved patients’ beliefs about medications as well as medication adherence across a wide range of medical conditions [17]. Our study has several limitations. Because data were obtained from a single tertiary epilepsy center in Jacksonville, the results may be specific to the demographic and clinical characteristics of our study population. The results were based mainly on retrospective review of pharmacy and medical records. Thus, we were not able to obtain data on other potentially pertinent predictor variables that need to be investigated in future studies, likely accounting for the low adjusted R 2 value. These include health literacy of patients, patient attitudes and motivation, and support systems. Interestingly, our results indicate that medication adherence is not influenced by the number of AEDs used, perhaps because most of our patients (80%) received their medications with no copays. Also, although the MPR is a widely used measure of medical adherence, it remains a surrogate measure to other more precise indices such as pill counting and actual medication consumption [9]. Lastly, our data were collected from a group of individuals who were enrolled in the indigent care program and received their medications at Shands–Jacksonville and may not be reflective of other patients with epilepsy who are enrolled in other state, federal, or commercial third-party payer systems. Despite these limitations, our results provide further evidence of actual disparities in medication adherence between African-Americans and Caucasians with epilepsy. These findings emphasize the need to incorporate cultural awareness and sensitivity when developing strategies to improve medication adherence among individuals with epilepsy. References [1] Hauser WA. Epidemiology of epilepsy. Adv Neurol 1978;19:313–39. [2] Kadir ZA, Chadwick DW. Principles of treatment of epilepsy. Drugs Today (Barc) 1999;35:35–41. [3] Hussain SA, Haut SR, Lipton RB, Derby C, Markowitz SY, Shinnar S. Incidence of epilepsy in a racially diverse, community-dwelling, elderly cohort: results from the Einstein Aging Study. Epilepsy Res 2006;71:195–205. [4] Chandra V, Bharucha NE, Schoenberg BS. Deaths related to epilepsy in the United States. Neuroepidemiology 2003;2:148–55. [5] Begley CE, Basu R, Reynolds T, et al. Sociodemographic disparities in epilepsy care: results from the Houston/New York City health care use and outcomes study. Epilepsia 2009;50:1040–50. [6] Bautista RE, Jain D. Detecting health disparities among Caucasians and AfricanAmericans with epilepsy. Epilepsy Behav 2011;20:52–6. [7] Horne R, Weinman J. Patients' beliefs about prescribed medicines and their role in adherence to treatment in chronic physical illness. J Psychosom Res 1999;47: 555–67. [8] Snodgrass SR, Vedanarayanan VV, Parker CC, Parks BR. Pediatric patients with undetectable anticonvulsant blood levels: comparison with compliant patients. J Child Neurol 2001;16:164–8. [9] Andrade SE, Kahler KH, Frech F, Chan KA. Methods for evaluation of medication adherence and persistence using automated databases. Pharmacoepidemiol Drug Saf 2006;15:565–74.
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[10] American Fact Finder. U.S. 2000 census data. Accessed: 2011 July 23. Available at: http://factfinder.census.gov. [11] Bosworth HB, Dudley T, Olsen MK, et al. Racial differences in blood pressure control: potential explanatory factors. Am J Med 2006;119:70.e9–15. [12] Egede LE, Gebregziabher M, Hunt KJ, et al. Regional, geographic, and ethnic differences in medication adherence among adults with type 2 diabetes. Ann Pharmacother 2011;45:2169–78. [13] Burneo JG, Black L, Knowlton RC, Faught E, Morawetz R, Kuzniecky RI. Racial disparities in the use of surgical treatment for intractable temporal lobe epilepsy. Neurology 2005;64:50–4.
[14] Burneo JG, Knowlton RC, Martin R, Faught RE, Kuzniecky RI. Race/ethnicity: a predictor of temporal lobe epilepsy surgery outcome? Epilepsy Behav 2005;7:486–90. [15] Swarztrauber K, Dewar S, Engel Jr J. Patient attitudes about treatments for intractable epilepsy. Epilepsy Behav 2003;4:19–25. [16] Vergouwen AC, Burger H, Verheij TJ, Koerselman F. Improving patients' beliefs about antidepressants in primary care: a cluster-randomized controlled trial of the effect of a depression care program. Prim Care Companion J Clin Psychiatry 2009;11:48–52. [17] Clifford S, Barber N, Elliott R, Hartley E, Horne R. Patient-centered advice is effective in improving adherence to medicines. Pharm World Sci 2006;28:165–70.
Contents lists available at SciVerse ScienceDirect
Epilepsy & Behavior j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / ye b e h
Health disparities in medication adherence between African-Americans and Caucasians with epilepsy Ramon Edmundo D. Bautista ⁎, Catrina Graham, Shahbuddin Mukardamwala Comprehensive Epilepsy Program, Department of Neurology, University of Florida Health Sciences Center/Jacksonville, Jacksonville, FL, USA
a r t i c l e
i n f o
Article history: Received 16 April 2011 Revised 23 July 2011 Accepted 25 July 2011 Available online 9 September 2011 Keywords: Adherence African-Americans Antiepileptic drugs Caucasians Compliance Epilepsy Health disparities Medication possession ratio Racial disparities Seizure disorder
a b s t r a c t Objective: The goal of this study was to determine whether racial disparities exist with respect to adherence to antiepileptic drugs (AEDs) in patients with epilepsy. Method: We reviewed the pharmacy and clinical records of 108 patients with epilepsy who were part of the indigent care program at Shands–Jacksonville. We determined the medication possession ratio (MPR) for each patient and obtained other demographic and clinical variables. Using univariate analysis we determined which variables were associated with the MPR and used multiple linear regression to determine those that best predicted the MPR. Results: Compared with Caucasians, African-Americans had poorer (lower) MPRs (0.872 for Caucasians vs 0.796 for African-Americans, P = 0.02). Age, gender, high school education, epilepsy classification, seizure freedom, number of AEDs, AED copayment scheme, and number of refills were not significantly affected by race. On stepwise multiple linear regression, race alone best predicted the MPR. Conclusion: Compared with Caucasians, African-Americans have significantly poorer AED adherence, as measured by the MPR. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Epilepsy is a common medical condition affecting nearly 1% of the population [1]. Because of advances in treatment, the majority of patients with epilepsy now have improved seizure control [2]. Recently, attention has turned toward disparities in epilepsy care. The incidence of epilepsy was shown to be higher in African-Americans than in Caucasians [3], and mortality remains higher among non-Caucasians [4]. African-Americans are also more likely to be diagnosed in nonspecialized environments, thus increasing their chances of receiving suboptimal care [5]. Our group recently published a study indicating that AfricanAmericans with epilepsy had poorer scores on the Beliefs about Medicines Questionnaire (BMQ), indicating increased hostility toward and resistance to the use of prescription drugs [6]. Poorer BMQ scores have been associated with poor medication adherence [7]. Snodgrass and colleagues earlier intimated a disparity in medication adherence among patients with epilepsy when they found significantly more nondetectable antiepileptic drug (AED) levels among non-Caucasian (predominantly African-American) children [8]. However, currently ⁎ Corresponding author at: Department of Neurology, University of Florida HSC/Jacksonville, 580 West Eighth Street, Tower One, Ninth Floor, Jacksonville, FL 32209, USA. E-mail address: [email protected]fl.edu (R.E.D. Bautista). 1525-5050/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.yebeh.2011.07.032
there is no study that measures adherence using other acceptable measures such as the medication possession ratio [9]. Such a study would need to control for many factors that potentially confound analysis of adherence, such as heterogeneous socioeconomic status, poor access to medications, and use of multiple pharmacy sites. We attempt to control for these variables by focusing our analysis on a group of patients who have a relatively homogeneous socioeconomic status, have easier access to medications, and receive their medications at a single pharmacy site. Controlling these variables allows us to determine whether race is independently associated with adherence to AEDs. 2. Methods This study was approved by the Institutional Review Board of the University of Florida Health Sciences Center/Jacksonville (UFHSCJ). We reviewed Shands–Jacksonville (UFHSCJ teaching hospital) pharmacy prescription and refill information from January 1, 2006 until December 31, 2010 of patients enrolled in the First Care (indigent) Program who received AEDs for treatment of seizures. The First Care Program is the indigent care program of Shands–Jacksonville and the City of Jacksonville. To be enrolled in the First Care Program, patients had to be residents of Duval County and had to have an annual houseshold income of no more than 200% poverty level. Those whose incomes were 100% poverty level or lower did not have a copay for their prescriptions. First
496
R.E.D. Bautista et al. / Epilepsy & Behavior 22 (2011) 495–498
Care Program recipients receive medications from a single pharmacy located within Shands–Jacksonville using a set formulary at 30-day refills. AEDs included in the First Care formulary are carbamazepine, ethosuximide, gabapentin, lacosamide, lamotrigine, levetiracetam, oxcarbazepine, phenobarbital, phenytoin, pregabalin, primidone, valproate, tiagabine, topiramate, valproic acid, and zonisamide. To be included in the study, subjects had to be First Care Program recipients and had to have been prescribed AEDs in the period under consideration. On the basis of medical record review, these patients had a diagnosis of epilepsy and were prescribed AEDs by University of Florida/Jacksonville neurologists for this condition. Patients with a history of nonepileptic seizures or who received AEDs for nonepilepsy indications were excluded from the study. By limiting our study to recipients of the First Care Program we were able to focus on patients of a relatively similar socioeconomic status who received their medications from a single pharmacy site and had relatively easy access to AEDs. Because of this, many potential confounders to data analysis were removed. Using pharmacy records, we calculated the medication possession ratio (MPR) [9]. The MPR is an accepted index of medication adherence and is defined as the number of days between prescription refills (30 days for our patient population) divided by the actual number of days between prescription refills. For example, a patient who refilled his or her prescriptions every 36 days would, on average, have a MPR of 30/36, or 0.83. We averaged the MPR of each AED prescription and across various AEDs to obtain the mean MPR for each patient. We also used pharmacy records to determine the number of AEDs patients were using (1, 2, N2), whether they had no to partial copays, and the number of AED refills they had. We reviewed the medical records to obtain demographic and clinical information: current age in years, gender, race (AfricanAmerican, Caucasian), epilepsy classification (idiopathic generalized, cryptogenic localization-related, symptomatic localization-related, symptomatic generalized), and seizure status (seizure free or having seizures) for at least 2 years preceding the time of the last clinic visit. We also obtained each patient's zip code to estimate the likelihood of graduating from high school given the 2000 US census data [10]. 2.1. Statistical analysis Statistical analysis was performed at a 5% level of significance using a two-tailed test with SPSS Version 15.0. MPR was the target variable, and the remaining demographic, clinical, and pharmacy data were the predictor variables. Transformation of interval variables was performed, if necessary, to satisfy the assumptions of normality. Using Pearson's R, we determined whether there was a significant association between the MPR and the different interval predictor variables (age, high school education, and number of refills). ANOVA was employed to determine whether the MPR differed according to the subgroups of various categorical and ordinal variables (gender, race, high school education, epilepsy classification, number of AEDs, and AED copay category). We employed stepwise multiple linear regression to determine which group of predictor variables was best associated with the MPR. 3. Results 3.1. Descriptive data One hundred eight patients met the inclusion criteria and were included in this study. Table 1 summarizes the characteristics of our study sample. The mean age of subjects was 42 years, and 55% were males. Fifty-five percent of subjects were Caucasians, and 45% were African-Americans. Three Caucasian patients were of Hispanic descent. There were no African-Americans of Hispanic descent. Around threequarters of patients were estimated to have completed high school.
Table 1 Descriptive data. Number of subjects Mean (SD) age, years Males Race Caucasians African-Americans High school educationa Epilepsy classificationb Idiopathic generalized Cryptogenic localization-related Symptomatic localization-related Symptomatic generalized Seizure freedom (≥2 years) Number of AEDs One Two More than two AED payment scheme Full charity Partial pay Mean (SD) number of refills Mean (SD) medication possession ratio
108 42.3 (11.4) 59 (54.6%) 59 (54.6%) 49 (45.4%) 76.3 (10.7) 6 (5.6%) 67 (62%) 34 (31.5%) 1 (0.9%) 22 (20.4%) 73 (67.6%) 33 (30.6%) 2 (1.9%) 87 21 10.4 0.84
(80.6%) (19.4%) (11.7) (0.2)
Note. Values are expresssed as n (%) unless otherwise indicated. a Estimated from 2000 U.S. census data. b International League Against Epilepsy Classification, 1989.
The majority of patients had cryptogenic localization-related epilepsy (62%), were not seizure free (80%), and were taking only one AED (67%). More than 80% of subjects had no copay and an average of 10 refills (range: 1–77). The MPR for all patients was 0.84. To normalize the interval data, we performed a logarithmic transformation of the MPR, lg(1.2 – MPR), and a square-root transformation of the number of refills. 3.2. Univariate analysis On univariate analysis, race was the only predictor variable that was significantly associated with MPR scores (P = 0.02) (Table 2). The MPR was 0.872 for Caucasians and 0.796 for African-Americans (Fig. 1). Age, gender, high school education, race, epilepsy classification, seizure freedom, number of AEDs, AED payment scheme, and number of refills were not significantly associated with MPR. The mean difference in MPR between African-Americans and Caucasians (0.076) translates into a difference of 2.3 days when filling a 30-day prescription. 3.3. Multivariate analysis Under stepwise multiple linear regression, a significant model emerged (F[1,103] = 5, P = 0.037, adjusted R 2 = 0.033) (Table 3). After incorporating our predictor variables into the analysis, race Table 2 Association between medication possession ratioa and predictor variables. Predictor variable
P value
Age Gender Race High school education International League Against Epilepsy Classification, 1989 Seizure freedom Number of AEDs AED payment scheme Number of refillsd
0.60b 0.81c 0.02c 0.85b 0.68c 0.18c 0.80c 0.97c 0.32b
a b c d
Data transformation: lg(1.2 – mean MPR). Pearson R. ANOVA. Data transformation: square root.
R.E.D. Bautista et al. / Epilepsy & Behavior 22 (2011) 495–498
Mean Medication Possession Ratio
0.88
0.872
0.86 0.84 0.82 0.796
0.8 0.78 0.76 0.74 Caucasians
African-Americans
Fig. 1. Comparison of medication possession ratios (MPRs) of Caucasians and AfricanAmericans. P = 0.02, ANOVA using transformed data: lg(1.2 – mean MPR) .
remained the only variable significantly associated with MPR (β = 0.205, P = 0.037). Age, gender, high school education, epilepsy classification, seizure control, number of AEDs used, copay status, and number of refills were not significant predictors of MPR (Table 3). 4. Discussion Our study shows that the MPR differs significantly among Caucasians and African-Americans with epilepsy: MPR values of Caucasians are higher than those of African-Americans, indicating better medication adherence. Our multiple linear regression model reveals that race alone (being African-American or Caucasian) can be used to predict medication adherence, although the low adjusted R2 (0.037) indicates that other variables not included in this study also influence MPR. Our study is similar to those of others who have noted poorer medication adherence among African-Americans across several disease states. In a study of veterans with hypertension who had good access to health care, African-Americans had poorer blood pressure control as well as increased odds of being nonadherent to their medications [11]. In another study, African-American veterans had poorer MPRs compared with non-Hispanic Caucasians [12]. Racial inequalities in epilepsy care have also been documented. African-Americans were less likely than non-Hispanic whites to undergo epilepsy surgery [13] and had worse outcomes following temporal lobe surgery [14]. As mentioned earlier, rates of undetectable AED serum levels were significantly higher in pediatric non-Caucasian (predominantly African-American) patients with epilepsy [8]. Our study adds to the existing literature comparing adherence among races by using another widely used measure, the MPR. We studied a group of patients of a similar socioeconomic class who were beneficiaries of our indigent care program and were residents of Table 3 Multiple linear regression of variables associated with medication possession ratioa. Variable Constant Race Age High school education International League Against Epilepsy classification, 1989 Gender Seizure freedom Number of AEDs AED payment scheme Number of refillsb
B
Significance
–0.64 0.10 –0.52 0.14
b 0.01 0.037 0.6 0.21
–0.09 b–0.01 0.12 0.07 0.01 –0.08
0.36 0.95 0.24 0.46 0.91 0.43
Note. P = 0.25. Method: stepwise. a Data transformation: lg(1.2 – mean MPR). b Data transformation: square root.
β
95% CI for B
0.205
0.006–0.19
497
Jacksonville, FL, USA. Our findings complement the results of our earlier study that revealed poorer scores on the Beliefs about Medicines questionnaire among African-American patients with epilepsy, compared with Caucasians, indicating more hostile attitudes towards prescription medications. On the basis of a self-reported survey, this same group of African-American patients had poorer seizure control compared with Caucasians [6]. An earlier study by Swarztrauber and colleagues [15] indicated that African-Americans with refractory epilepsy had higher levels of mistrust of their health care providers. The results of these studies emphasize the need to develop a program designed to enhance patient compliance with AEDs, particularly among African-Americans. Programs that help improve patients’ attitudes toward medication use have been successfully implemented for other diseases. Using a program that incorporates patient education and active participation of the physician and patient in the treatment process, patients with depression developed more favorable attitudes toward the use of antidepressants [16]. In another study, a pharmacist-led patient educational program significantly improved patients’ beliefs about medications as well as medication adherence across a wide range of medical conditions [17]. Our study has several limitations. Because data were obtained from a single tertiary epilepsy center in Jacksonville, the results may be specific to the demographic and clinical characteristics of our study population. The results were based mainly on retrospective review of pharmacy and medical records. Thus, we were not able to obtain data on other potentially pertinent predictor variables that need to be investigated in future studies, likely accounting for the low adjusted R 2 value. These include health literacy of patients, patient attitudes and motivation, and support systems. Interestingly, our results indicate that medication adherence is not influenced by the number of AEDs used, perhaps because most of our patients (80%) received their medications with no copays. Also, although the MPR is a widely used measure of medical adherence, it remains a surrogate measure to other more precise indices such as pill counting and actual medication consumption [9]. Lastly, our data were collected from a group of individuals who were enrolled in the indigent care program and received their medications at Shands–Jacksonville and may not be reflective of other patients with epilepsy who are enrolled in other state, federal, or commercial third-party payer systems. Despite these limitations, our results provide further evidence of actual disparities in medication adherence between African-Americans and Caucasians with epilepsy. These findings emphasize the need to incorporate cultural awareness and sensitivity when developing strategies to improve medication adherence among individuals with epilepsy. References [1] Hauser WA. Epidemiology of epilepsy. Adv Neurol 1978;19:313–39. [2] Kadir ZA, Chadwick DW. Principles of treatment of epilepsy. Drugs Today (Barc) 1999;35:35–41. [3] Hussain SA, Haut SR, Lipton RB, Derby C, Markowitz SY, Shinnar S. Incidence of epilepsy in a racially diverse, community-dwelling, elderly cohort: results from the Einstein Aging Study. Epilepsy Res 2006;71:195–205. [4] Chandra V, Bharucha NE, Schoenberg BS. Deaths related to epilepsy in the United States. Neuroepidemiology 2003;2:148–55. [5] Begley CE, Basu R, Reynolds T, et al. Sociodemographic disparities in epilepsy care: results from the Houston/New York City health care use and outcomes study. Epilepsia 2009;50:1040–50. [6] Bautista RE, Jain D. Detecting health disparities among Caucasians and AfricanAmericans with epilepsy. Epilepsy Behav 2011;20:52–6. [7] Horne R, Weinman J. Patients' beliefs about prescribed medicines and their role in adherence to treatment in chronic physical illness. J Psychosom Res 1999;47: 555–67. [8] Snodgrass SR, Vedanarayanan VV, Parker CC, Parks BR. Pediatric patients with undetectable anticonvulsant blood levels: comparison with compliant patients. J Child Neurol 2001;16:164–8. [9] Andrade SE, Kahler KH, Frech F, Chan KA. Methods for evaluation of medication adherence and persistence using automated databases. Pharmacoepidemiol Drug Saf 2006;15:565–74.
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