Clinical and demographic correlates of medication and visit adherence in a large randomized controlled trial

Adherence is defined as the extent to which a person’s behavior coincides with medical or health advice. This can refer to such diverse behaviors as personal habits (e.g., dietary changes) [1], attendance at scheduled visits (visit adherence) [2], and the extent to which patients take medication as prescribed [3].

Poor medication adherence has been associated with worse blood pressure control, worse clinical outcomes, and increased health care costs [4‐8]. Proposals to link payment to such measures of quality as hypertension control have increased attention to mechanisms to enhance adherence. As participant adherence is considered an essential component of high-quality randomized clinical trials (RCT), efforts to ensure adherence have long been incorporated in RCT design [9, 10].

Extensive literature has examined factors associated with adherence in clinical practice. Medication adherence has been linked to gender, age, race, and ability to pay [11‐15], as well as clinical factors such as the specific drug, dosing schedule, duration of therapy, and indication for therapy [11, 14]. However, many of these studies had serious flaws. Studies using administrative data often lacked detailed clinical information, in particular the indication for which the drug was prescribed. On the other hand, most studies that have used clinical data were smaller and performed in one or a few clinical settings, limiting generalizability. Finally, most studies were carried out in settings that did not have explicit strategies to enhance adherence, raising the question of whether greater use of these strategies could attenuate the association of participant characteristics with adherence.

Policymakers need to consider patient characteristics associated with poor adherence as they design payment systems that reward better outcomes; providers caring for populations with higher levels of poor adherence will be at risk for worse outcomes and therefore lower payments. Similarly, anticipating the likely level of adherence, particularly in population subgroups, is important for RCT design and conduct, as poor adherence to a therapy during a trial could obscure evidence of its efficacy. The evidence for a link between adherence and efficacy is well established for antihypertensive drug therapy [6, 16‐18]. Therefore, we examined predictors of visit and medication adherence among individuals with hypertension who participated in a large RCT that used state-of-the-art methods to facilitate adherence.

We performed secondary analysis of participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) [19, 20]. ALLHAT was a randomized trial of participants with hypertension who were aged 55 or older and at high risk for coronary artery disease events. The study explicitly selected sites able to enroll a diverse study population. Between February 1994 and May 1998, 632 clinics in the United States, Canada, Puerto Rico and the U.S. Virgin Islands recruited participants using mass mailings, media presentations, chart review, and word of mouth. The ALLHAT protocol was approved by the University of Texas Health Science Center at Houston Institutional Review Board (IRB) and all participants recruited into the study provided written informed consent. Each clinic received approval from its site IRB. For most participants, the study site was their primary care clinic. Participants received study drugs at no cost. Follow-up visits were scheduled at intervals established by study protocol; visit costs were not reimbursed. Key individuals at study clinics received ongoing feedback from regional coordinating centers regarding visit adherence and blood pressure control; they also received education regarding strategies to improve visit and medication adherence in regular conference calls, by written communication, and at annual investigator meetings; sites with exceptional performance were recognized at these meetings.

Participants were randomly assigned to 1 of 4 antihypertensive study drugs – amlodipine, chlorthalidone, lisinopril, or doxazosin. The study drug dose was adjusted regularly to achieve blood pressure control. Participants and providers were blinded to the identity of this drug. If blood pressure was uncontrolled on the study drug alone, additional antihypertensive drugs were added, following a study protocol. In the present analysis, we focus on adherence to the randomly assigned antihypertensive drug.

We included only participants who had at least five expected visits (i.e., 1 year of follow-up). We reasoned that the adherence of participants who did not complete a year in the study would not be representative of long term adherence. We also excluded participants randomized to receive doxazosin, as this arm was stopped early due to an excess of cardiovascular disease events and futility compared with chlorthalidone [21].

The ALLHAT study achieved excellent ethnic and gender diversity (Table 1). While 40 % of participants were enrolled from the southern United States, the population was also geographically diverse; Puerto Rico and the Virgin Islands together contributed 13 % of enrollees.

In this large diverse cohort with structured follow-up for hypertension at clinics that received audit and feedback similar to current “best practices” for chronic disease management [23, 24], we found that clinical and demographic participant characteristics remained associated with both visit and medication adherence. While these associations are not large enough to aid clinical decision-making for individual patients, they could significantly affect reimbursement in systems that reward improved adherence. Similarly, these differences could have important implications for designing and powering RCTs. Moreover, while clinic characteristics impact both medication and visit adherence, the ability of larger, more structured clinics (e.g., VAMC, university, or group practices) to achieve better visit adherence did not translate into improved medication adherence. Indeed, better visit adherence was not associated with improved medication adherence at the participant level, suggesting that closer follow-up alone may not improve medication adherence.

The patterns of medication adherence that we observed are consistent with patterns of adherence seen in settings with fewer resources to support adherence. Most, but not all, studies have found lower adherence among Blacks and Hispanic non-Blacks [15, 25‐28] and persons with less education [29]. The association of adherence with age and gender has been less consistent across studies [11]. Although the literature is not as extensive, demographic characteristics have also been associated with visit adherence [3, 30].

In contrast to prior non-randomized studies suggesting better medication adherence among persons receiving angiotensin-converting enzyme inhibitors, we observed decreased medication and visit adherence among participants randomized to lisinopril [31‐33]. However, this association lost significance when we excluded data following clinical events that may have decreased adherence. We note that the lisinopril group had higher rates of strokes, combined cardiovascular disease, and heart failure [19], which may have affected adherence. Further studies should confirm these findings in other settings.

We acknowledge that our findings are most easily generalized to other RCTs. Individuals who participate in RCTs are known to be more adherent than the general population [9]. Similarly, the clinics which participate in randomized trials may systematically differ from the universe of clinics. These factors suggest we may have overestimated adherence. It is also possible the effects of participant variables are attenuated, since these participants may be more uniformly interested in health, causing factors such as race, age, and gender to have less impact on adherence. The same might apply to clinics – the federally-qualified health clinics and VAMCs that participated in this study, for example, may be more like one another than federally-qualified health clinics and VAMCs in general. Thus, the odds ratios we found may be conservative estimates of the impact of patient and clinic characteristics on adherence. Similarly, since ALLHAT began in 1994, with the last closeout visits happening in 2002, it is possible that factors influencing adherence have changed since that time, although the techniques used to support adherence in ALLHAT continue to be viewed as best practices [23, 24]. We acknowledge this may affect extrapolation of our results to current practice.

We also note that we studied adherence in the setting of hypertension, a chronic disease, using drugs from just three classes; our findings may not apply to other disease/medication dyads [28]. Moreover, medication adherence may have been affected by the fact that doctor and participant were unaware of which medication they were using. Finally, our choice of measures of visit and medication adherence influenced our results. Our generous 4 month window for considering a visit “adherent” likely inflates our visit adherence compared to other reports. Our single item self-report measure of medication adherence might give different results than analyses based on more complex self-report measures [17, 34], measures of medication refill behavior [22], or electronic pill counters [35].

Despite these limitations, we believe the strengths of the study make the results noteworthy for clinical practice and policy. We studied adherence in a large, diverse population treated in a wide variety of clinical settings, using standardized measures of visit and medication adherence. Participants and sites used the same drugs on the same schedule for the same indication and received similar support for medication and visit adherence – patients received regular monitoring, reminder contacts, and free prescriptions; clinics received audit and feedback, typically had dedicated staff and were recognized for high performance. All these factors reduce variation due to local clinic policies or clinician choices.

We believe our findings suggest three considerations regarding adherence that may apply to patient care. First, adherence is unpredictable. Although patient characteristics are significantly associated with adherence, they do not identify patient groups with uniformly adequate medication adherence. For example, while the odds of adequate medication adherence among non-Hispanic, non-Blacks were nearly 50 % higher than among Blacks, large majorities of both non-Hispanic, non-Blacks, and Blacks were adherent; significant minorities of both groups were not. Interventions targeting patients at particular risk of poor adherence ignore this fact. Second, patients who come to visits more regularly should not be assumed to take their medications routinely; in our analysis, visit adherence did not predict medication adherence. Finally, poor adherence may persist even in well-run clinics with motivated patients. This suggests that we may still need new approaches to improving adherence. These results from the largest RCT of hypertensive therapy also confirm that study designers must attend to participant factors associated with adherence to ensure adequate power to detect significant differences, particularly in important subgroups.

On the policy level, if our results can be extrapolated to current practice, then they suggest that systematic variation in adherence by patient characteristics will persist despite vigorous efforts to support adherence. This would buttress prior concerns that clinics serving certain populations will be disadvantaged if financial rewards or penalties are distributed based on adherence [36, 37].

ALLHAT, antihypertensive and lipid-lowering treatment to prevent heart attack trial; HMO, Health Maintenance Organization; IRB, institutional review board; RCT, randomized clinical trial; VAMC, Veterans Affairs Medical Center