The concept of compliance is important because negative outcomes such as increased seizure frequency, increased hospital admissions, loss of driving privileges, loss of employment, status epilepticus, and death are often related to the inability to take medications as ordered (non-compliance).
The findings of this literature review will be used to determine what is currently known about patient compliance, identify the gaps in the literature, and, based on findings, suggest clinical and research implications. The authors conducted a comprehensive review of compliance literature using the key words ‘patient compliance,’ ‘epilepsy,’ and ‘patient adherence,’ in ‘Medline’ and ‘Cumulative Index to Nursing & Allied Health’ (‘CINAHL’) to retrieve all the related research studies from 1975 until the present. In addition, a manual search was conducted using the reference lists of related articles. Inclusion criteria were: articles in which at least one dependent variable was compliance rate with a detailed description of the measurement of compliance; research articles focusing on examining medication compliance issues in adult patients with epilepsy; and articles written in English. Articles were not included if they focused on the pharmacological aspects of antiepileptic medications and not compliance.
The authors found 22 research studies for this review, which were divided into five groups related to content focus as follows:
• rates of compliance;
• measurement of compliance;
• correlates of compliance;
• intervention to improve compliance rate; and
• qualitative studies exploring compliance behaviors.
The Measurement and Rates of Compliance
Multiple strategies have been used to measure medication compliance. Each method has serious measurement flaws and no ‘gold standard’ for measuring compliance exists.
Patient self-report, the most commonly used measure of patient compliance, can provide information about the patterns of medication use and patients’ perception and barriers to medication compliance. However, it is reported that this method often overestimates compliance rates because patients do not always remember or report exactly how they took their medications. Moreover, they may not want to disappoint their healthcare provider by reporting that they have not kept up with the prescription.
Pill counts and prescription refills have been used to provide a more objective measure of compliance. Each method presents similar problems. Researchers have counted pills during clinic visits to identify the number of pills taken by the patients. Likewise, researchers have tracked the frequency of prescription refills and compared actual refill times to ideal refill times. Studies have demonstrated that prescription refills, when using records from central pharmacies, correlate well with the compliance data measured by medication serum concentration and self-report. Neither pill counts nor prescription refills provide information about patterns of actual medication-taking behavior. There is no way to be sure that patients take all the medications on time and in correct dosage once the medications are gone. Tracking serum levels of AEDs has been used in several studies. This method was thought to give information about the relationship between medication dose and patients’ response. However, it was found that pharmacodynamic factors (individual differences in drug responsiveness) are more important than pharmacokinetic factors in explaining the different serum levels of AEDs between patients. It is difficult to differentiate the effects of pharmacodynamic factors and compliance on patients’ serum levels of AEDs. Therefore, this method is questionable, in addition to being very expensive and intrusive.
Medication Event Monitoring System™ (MEMS) is a microprocessor technology used to track patients’ medication-taking behaviors. The microprocessor can detect both the frequency and the time that the medication bottle was opened. With long-term monitoring, it was thought to be able to track the detailed daily medication-taking pattern. However, as with similar previous compliance measures, it is impossible to be sure of actual medication-taking behavior once the bottle is opened.
Finally, seizure frequency as an outcome measure has also been used to measure compliance behaviors.This method is not a valid measure of compliance because patients’ conditions can improve or worsen for a variety of reasons, not just medication compliance. The variance in estimated compliance rates is wide (17–71%) and does not seem to be dependent on the measurement methods, which did not yield differences in compliance rates.The only real difference in variance was the number of daily doses ordered.This review found no single measurement that adequately captured patients’ medication compliance. Multiple measurements for patients’ medication-taking behaviors may be the best method.
The Correlates of Compliance
Reported correlates of compliance are mostly based on cross-sectional studies and therefore it is impossible to determine causality. However, conclusions may be drawn to guide future studies:
• Perception seems to be an important factor in compliance behavior. Dilirio et al. used a psychosocial model of medication self-management to study the determinates of patients’ compliance behaviors. Several variables in this model, including the perceived effectiveness of the medications, the perceived benefits of medication, the perceived susceptibility to seizure, and the perceived barriers to medication compliance, were reported to be correlated with compliance behaviors. This selfmanagement model might give some direction to future compliance work.
• The complexity of the regimen (e.g. times per day) was related to compliance in patients with epilepsy. While most studies suggested that poor compliance was related to a more complex regimen, one study suggested the opposite.
• Compliance is related to quality of information received, though it appeared that patient education was necessary but not sufficient to improve compliance.
• Side effects of the medication affected compliance behavior.
• Compliance was affected by a fear of dependency.
• The communication between doctor and patients and visiting frequencies were related to good compliance behaviors.
• Beliefs such as those related to susceptibility to seizures and the perceived benefits and effectiveness of AEDs were related to compliance.
• Additional factors such as financial issues or forgetfulness may be related to compliance behavior, but were reported only in single studies. The demographic variables were not consistently reported to affect compliance.
Interventions to Improve Compliance
We found only five intervention studies aimed at enhancing patients’ medication compliance behaviors. Though the results were varied, some conclusions may be drawn.
• Patient education did not consistently improve compliance (one study reported positive effects and one did not.
• Multiple strategies might improve medication compliance rates like patient counseling, special medication containers, and a reminder system for both appointment and medication refills.
• One study demonstrated that using a reminder system helped to improve compliance, supporting findings in descriptive studies suggesting that forgetting to take medications was one cause of non-compliance.
• Medication compliance might be improved by simplifying the medication-taking regimen (switching to an extended-release formula). This supports descriptive studies suggesting that a complicated medication-taking regimen decreased compliance.
• Increasing clinic visits, was shown to improve compliance, which supports the descriptive studies finding that time between clinic visits was associated with poor compliance.
Qualitative Studies Exploring Medication-taking Behaviors in Patients with Epilepsy
Three qualitative studies were found that explored the problem of compliance. The strength of these studies was the depth of information given regarding the problem with compliance and how patients think about taking medication. In these studies, the findings were generally consistent with the factors identified in the quantitative studies.
Schneider and Conrad (1987) interviewed 18 persons with epilepsy to investigate the experiences of having epilepsy from the patients’ perspectives. The results showed that about 42% of participants deviated from the prescribed medication-management behaviors for reasons of gaining independence, testing the effects of medications, and avoiding stigma. They also reported that the patients taking AED medications decided how to weave their daily medication intake into their lives, and most times these decisions were different from what the physicians had ordered. For example, patients commonly reduced their medication intake to avoid being dependent on drugs. Moreover, patients did not want to take medication in front of their colleagues to avoid the stigma associated with having epilepsy. Finally, they reported that patients sometimes tested medication effectiveness by skipping doses to see if that would cause them to have seizures.
Trostle (1983) used participant observation to follow seven epilepsy patients for their self-care behaviors, including taking medications, over 10 months in a variety of social contexts.The results showed that most patients were not compliant. The medication-taking behaviors were so complex that no repeated pattern of compliance could be found and most patients used more than one drug strategy to manage their medication. Furthermore, some patients were found to be non-compliant with biomedical regimens, yet actively and consistently pursued alternative regimens. A range of such alternative therapies was identified both for low-income and middle-income patients. Although this was a small sample size, it provided an in-depth look at actual medication-taking behavior.
Buelow & Smith (2004) investigated 25 adults to understand if perception of medication management matched actual medication management. In that study, the authors interviewed 25 persons with epilepsy and measured compliance using the MEMS Cap. They reported that 10 participants consistently did not follow physicians’ directions. The authors suggested that most of those with poor compliance actively made decisions about taking medications (self-regulation).
This review clearly shows that medication compliance rates are poor in this patient population and there is little agreement about the cause of poor compliance. Some researchers have argued that the absence of the patient’s perspective in compliance research might explain the lack of improvement in compliance behavior and that researchers should focus more on decision-making related to medications. From the three qualitative research studies, it is evident that patients are not always passive in medication-taking behavior. Patients deviated from the prescribed medication management behaviors for stated reasons of gaining independence, testing the effects of medications, and avoiding stigma. Most patients are trying to weave taking medication into their normal life, making decisions that work for them.They make such decisions based on their beliefs, knowledge about how to control seizures, and impact on a normal life. Therefore, patients are active decision-makers regarding how to take their medications. In other words, patients do not fail to comply, but rather they choose to take medications in a way that may or may not be different from what their doctors have ordered for them.
The term compliance implies that patients blindly follow their healthcare provider’s directions. The majority of the reviewed research articles were conducted based on the assumption that noncompliance is the patients’ fault, which is an incorrect assumption. Missing medications might be either intentional or unintentional. If the patient engages in non-compliant behavior intentionally, an active decision-making process regarding their medicationtaking behavior applies. Medication management should be thought of as a partnership between the healthcare provider and patient, with the healthcare provider assisting the patient in making good decisions.
Some of the findings from this review can be applied to clinical practice. For example, because frequency of communication between the HCP and the patient was shown to affect patient medication-taking behavior, as medication regimens becomes more complicated, communication should be increased either through more clinic visits or via telephone. Frequent communications can help patients to develop appropriate medication management skills and understand the consequences of their decisions.
The research findings were varied and not consistent from patient to patient. This suggests that treatment regimens need to be individualized to fit each patient’s lifestyle. Moreover, because patients seem to have more problems remembering to take their medications when the regimen is complicated, medication regimens should be simplified when possible.
Future research should be conducted to explore the decision-making process regarding medication-taking behaviors. This theoretical perspective might provide a more promising perspective upon which to base future interventions.