How Medication Adherence Affects Disease Management in Veterans with Glaucoma: Lessons Learned from a Clinical Trial

Glaucoma is the leading cause of irreversible blindness worldwide, with a current estimate of nearly 76 million people afflicted in 2020 [1‒3]. The prevalence is expected to increase to 111.8 million by the year 2040 [3]. The most common form of management for this incurable disease is eye drops, most taken at least once daily for an indefinite amount of time [4].

As with other chronic, asymptomatic diseases, adherence to the prescribed glaucoma medication regimen is often poor, and poor adherence is associated with increased disease progression [5‒8]. Eye-drop nonadherence has been reported as high as 80% [9], with up to half of patients not taking their drops as prescribed [10]. To complicate the matter, studies have established that patients often over-report their eye-drop adherence [11, 12]. This over-reporting of adherence implies that some nonadherent patients could be slipping through the cracks and not receiving appropriate treatment. Hypothesized reasons for over-reporting adherence include patients not wanting to disappoint their physicians, forgetfulness, and the patient’s poor understanding of the medication schedules [13].

In attempts to improve eye-drop adherence, various forms of interventions are in existence or development. Ranging from individualized education sessions and reminder phone calls to smartphone apps and visual chart aids, developers try to provide aid for those who struggle to consistently take their eye drops [4, 14]. However, only a few studies have examined the association between their interventions and clinical outcomes (fourteen of 42 in a recent review), with all but one having a follow-up period of 12 months or less [15]. Additionally, these reports do not consistently show positive results [16]; only three of the aforementioned 14 found improvements in intraocular pressure (IOP) [15]. This implies that while some interventions do appear to impact adherence, their effect on disease progression has not been consistently shown. For instance, Leshno et al. [17] reported improved adherence and IOP after use of their intervention involving the “EyePhone” App, a smartphone reminder system. At the same time, Dreer et al. [18] did not find an improvement in IOP despite their multifaceted intervention that also improved adherence. Other studies that exhibit conflicting clinical conclusions include those reported by Okeke et al. [19], Beckers et al. [20], and Sakai et al. [21]. Overall, this lack of consistency in findings implies that there is a need for further research concerning the clinical outcomes and benefits of adherence interventions.

We conducted a secondary, real-world clinical assessment of a randomized controlled trial to address this need. The parent study tested the effectiveness of an intervention developed to improve glaucoma medication adherence [22]. We have reported that participants in the intervention group took a greater proportion of the prescribed medications in the 6 months following randomization compared to participants in the control group (0.85 vs. 0.62, respectively, p < 0.0001) [23]. The purpose of the study described in this manuscript is to determine if participants who received the intervention had better clinical outcomes in the 12 months following randomization compared to participants who received usual care in the control group. To measure clinical outcomes, we examined if those in the intervention group experienced less escalation of glaucoma treatment or less worsening of glaucomatous field loss. We hypothesized that those real-world clinical outcomes measured would be better for participants who received the intervention compared with those in the control group.

The parent study was a single-site randomized controlled trial conducted under the approval of the Institutional Review Board of the Durham VA Medical Center and registered with ClinicalTrials.gov (# NCT03052257). It has been reported in detail previously [23]. In brief, veterans with glaucoma who reported poor adherence to their prescribed glaucoma medication regimen were randomized to receive a multifaceted intervention developed to improve glaucoma medication adherence (intervention group) or an educational session regarding general eye health and usual care (control group). Participants in both arms received a “smart bottle” (AdhereTech; New York, NY, USA) to record the date and time of medication dosing events. For participants in the intervention arm only, a reminder function from AdhereTech was activated. Patients had the option of choosing up to three reminder methods: text message, phone call, or a beep from the bottle. The primary outcome of interest for the parent study was the average proportion of prescribed doses taken in the 6 months following randomization.

As described previously [22], the multifaceted intervention for the participants in the intervention group included a one-time glaucoma educational session with individualized drop administration instruction conducted by an ophthalmic technician. If the participant indicated that a companion was involved in his or her glaucoma care, the companion was invited to the educational session as well. Participants in the intervention group also received a virtual reminder from the “smart bottle” given to hold their prescribed eye drops. The virtual reminder could take the form of an audible alert, a flashing light, a text message, or a call to a landline, depending on the participant’s preference. The control group received a general eye health session (with companion, if applicable) and a “smart bottle” with the reminder function turned off. The glaucoma educational session for the intervention group and the general eye health educational session for the control group were each conducted one time only and lasted approximately 45 min.

In order to determine if the intervention was associated with differences in clinical outcomes, several measures were investigated for each participant at 12 months post-randomization via clinical chart abstraction. These measures were chosen as pragmatic, “real-world” outcomes within the limitations of the primary study’s setting and resources. These included (1) if a glaucoma medication was added (including an additional drop of the medication already in use) due to inadequate IOP control in one or both eyes, (2) if a glaucoma laser procedure or surgery was recommended by the treating physician due to inadequate IOP control in one or both eyes, and (3) visual field progression. We did not examine the more traditional measures of glaucomatous disease progression due to limited resources, such as standardized assessment of IOP, visual fields performed at specific intervals, or masked optic nerve assessment.

The addition of a medication and/or procedure was determined based on provider recommendation as opposed to completion or patient agreement. For example, if the treating physician recommended laser trabeculoplasty and the patient declined, this was counted as escalation of therapy. Visual field progression was determined by one of two glaucoma specialists who were masked to treatment assignment for grading purposes. They reviewed the visual fields from baseline through 12 months after randomization and indicated, for each eye separately, if glaucomatous progression had occurred. If either eye of a participant was judged to have progressed, then that participant was labeled as “progressed by visual field.” Visual fields were performed as part of routine clinical care, not per study protocol. The study staff performing the chart abstraction for added medication or surgeries was not masked to treatment assignment.

Those 3 clinical outcomes (treatment escalation with medications, treatment escalation with surgery or laser, or visual field progression) were combined, if present, into a composite progression outcome, such that if any one of those outcomes occurred, that was defined as “disease intensification.” If there was a question concerning whether disease intensification occurred for a participant, the three staff members discussed the case as a group to come to a conclusion.

The primary measure for the investigation described in this manuscript, the presence of disease intensification for each participant, which includes treatment escalation (with medications, surgery, or laser) or visual field progression, in the 12 months following randomization, was compared between the intervention (n = 100) and control (n = 100) groups. This is denoted by the orange box in the study schematic demonstrated in Figure 1. Secondary measures included descriptive frequencies of the treatment escalation indicators.

Proportions and frequencies were used to summarize the primary and secondary clinical outcomes. Differences in disease intensification between the intervention and control groups were evaluated via multiple logistic regressions, where the primary coefficient of interest was the intervention group indicator. The randomization stratification variables (dosing frequency and companion status) as well as age, race, and disease severity were all included in the adjusted regression models.

At baseline, treatment groups did not differ by age, gender, how often the participants were prescribed to take their drops, if they had a companion that accompanied them at the education session, their health literacy as measured by the Rapid Assessment of Adult Literacy in Medicine (REALM; a word recognition test of functional health literacy) scores, employment status, marital status, financial status, or the severity of their disease at the start of the trial (Table 1).

Overall, at 12 months, there was no difference between the intervention and control groups in terms of disease intensification, the composite outcome that includes treatment escalation (with medication, surgery, or laser), and visual field progression (intervention vs. control group odds ratio: 1.20; 95% confidence interval: [0.67, 2.15]). Of note, age, race, and disease severity were accounted for in the logistic regression model. Thirty-six versus 32% of the intervention (n = 100) versus control (n = 100) groups, respectively, experienced disease intensification (Fig. 2). Additionally, the between-group difference was not significant when assessed by the three individual measures of disease intensification. Most veterans in the study (>60%) did not experience glaucomatous disease intensification as measured by the variables collected in this study at all during the 12 months following randomization.

To determine whether the COVID-19 pandemic may have impacted the outcomes, we identified those participants whose study period included time during the COVID-19 pandemic, starting March 20, 2020, when non-urgent ophthalmology appointments were systematically canceled at the Durham VA Medical Center due to the pandemic. Thirty-six participants had study-related outcomes potentially impacted by the COVID-19 pandemic. A sensitivity analysis showed that they were evenly distributed among the treatment groups; there were 19 individuals in the intervention group and 17 individuals in the control group participating in the study during the pandemic.

Overall, these results suggest that even though a multifaceted adherence intervention improved medication adherence for 6 months, it did not improve this study’s pragmatic, “real-world” clinical outcomes at 12 months after randomization. Despite these results showing no effect from the intervention within 12 months, some lessons can be drawn, particularly when combined with the published literature.

One likely explanation for this negative finding is that more time is needed between the intervention and the ability to measure its effect on clinical outcomes. This idea is supported by the observation that the majority of our study’s patients (>60%) did not experience any form of disease intensification (Fig. 2). The explanation is further supported by the majority negative outcomes of previously published studies, those of which do systematically examine glaucomatous disease progression. As described in a recent review, only 14 of the 42 identified glaucoma adherence studies examined clinical outcomes of the used glaucoma adherence tools [15]. Thirteen of these same 14 studies lasted 12 months or less (the 14th study was 24 months), and only 3 of 14 found positive clinical outcomes [15]. The results of our analyses do not dispute this trend; instead, they strongly argue that not only does clinical impact need to be addressed in adherence trials but that more time is needed to adequately assess these outcomes. In most cases, glaucoma is a slowly progressing disease. While multi-year studies utilize more resources and time, the combined results from this study and others suggest that 12 months or less may not be long enough to see the clinical benefit of this intervention and others. We therefore propose that others consider lengthening their studies when designing future trials that examine the clinical effects of glaucoma medication adherence.

Alternatively, the 6-month-long intervention may not have been long enough to impact the clinical outcomes, or the intervention’s benefit may have worn off in the following 6 months of time; perhaps a “booster” intervention might be needed to reenforce the previously developed habits. Again, based on the current literature, studies that evaluate clinical outcomes vary widely in time to assess outcomes, with little correlation between time and effectiveness of the intervention [15]. Consequently, a second lesson from this analysis is to consider how a gap between intervention and measured clinical outcomes might affect results, with the goal of minimizing a gap’s size to remove a potential confounding factor.

Because COVID-19 provoked clinic appointment cancelations at the end of the study for some participants, we completed an additional sensitivity analysis of those with a post-randomization date after than March 20, 2020, when the Durham VA Medical Center first canceled appointments due to the pandemic (36 patients). This analysis shows that the pandemic was unlikely to affect the intervention or control groups disproportionately.

There are several limitations to this real-world clinical study. The first is that all participants are veterans at the Durham VA Medical Center, where the majority are male. Also, medications are provided at the Durham VA at low or no cost. Thus, some barriers experienced by many people with glaucoma, such as access to medication and care, were minimized. Additionally, the sample size calculation was based on the primary outcome of the parent study, to find a difference in adherence rates, not on the clinical outcomes described here; the sample size therefore may not have been large enough to capture a between-group difference. This is supported by the observation that >60% of patients did not experience disease progression. The resources and available setting also stemmed from the parent study. Therefore, we considered the measured outcomes to be pragmatic and “real world” as opposed to more traditional measures of glaucomatous disease progression, such as standardized assessment of IOP, visual fields performed at specific intervals, or masked optic nerve assessment. A related potential limitation is that our definition of “disease intensification” only examined 3 outcomes, but others such as quality of life, self-efficacy, or structural measures such as optical coherence tomography might have displayed a between-group difference.

Overall, this study shows that while this multifaceted intervention improved medication adherence for glaucoma after 6 months of use, it did not affect real-world clinical outcomes at 12 months post-randomization. Future work, particularly with regard to longer follow-up given the nature of the clinical outcomes of improved adherence, is needed to improve care and vision for the patients who may struggle the most with adherence to glaucoma treatments.

This trial was conducted under the approval of the Institutional Review Board of the Durham VA Medical Center, approval number 2007, and adhered to the tenets of the Declaration of Helsinki. Written, informed consent was gathered from all participants at the baseline visit.

The authors have no conflicts of interest to report.

The study was funded by the VA Health Services Research and Development IIR 15-113 (Muir). Trial registration: # NCT03052257.

Kristen L. Buehne wrote the manuscript and gathered the data for this secondary study. Jullia A. Rosdahl and Kelly W. Muir met with Kristen L. Buehne weekly to assist with data collection and questions. Sandra Woolson and Maren Olsen conducted statistical analyses. Miriam Kirshner and Malina Sexton assisted with patient enrollment and study administrative duties. Kristen L. Buehne, Jullia A. Rosdahl, Aaron M. Hein, Sandra Woolson, Maren Olsen, Miriam Kirshner, Malina Sexton, Hayden B. Bosworth, and Kelly W. Muir assisted with interpretation of data and manuscript editing.

The data that support the findings of this study are not publicly available due to their containing information that could compromise the privacy of research participants but are available as allowable from the VA from Kelly W. Muir.