Dataset Information

Predicting Adherence With the Glaucoma Treatment Compliance Assessment Tool.

ABSTRACT: PRéCIS:: Univariate and multivariable models using the Glaucoma Treatment Compliance Assessment Tool (GTCAT) statements identified multiple, patient-specific factors associated with adherence that could be used to inform personalized interventions to optimize glaucoma adherence.

Purpose

The purpose of this study was to determine the health behavior factors related to glaucoma adherence in patients with self-reported poor adherence.

Methods

A research coordinator used the Chang Adherence Measure and the Morisky Medication Adherence Scale to identify subjects with poor self-reported glaucoma medication adherence and enrolled them in a 3-month study to electronically monitor medication adherence. At enrollment, the coordinator administered the GTCAT. We calculated the percentage of prescribed doses taken over a 3-month period using an electronic dose monitor (AdhereTech). We used Rasch analysis, and univariate and multivariable regression to determine the GTCAT statements that predicted electronically monitored adherence.

Results

The mean adherence was 73.8% (SD=21.04%, range: 13% to 100%). Rasch analysis showed that the GTCAT had a good overall fit and no differential bias (Anderson likelihood ratio test >0.05). Multiple GTCAT statements were associated with adherence, which represented increased knowledge, increased cues-to-action, decreased barriers, less depression, and increased self-efficacy (P<0.09 for each). The full GTCAT or a subset of statements had a high association with adherence (R range: 0.44 to 0.51, P<0.005 for all). The GTCAT identified >50% of patients who wanted more education about glaucoma; >68% who did not use reminders; and >40% who reported having difficulty using the eye drops.

Conclusions

The GTCAT identified multiple factors associated with adherence. Clinicians and researchers could use this tool to identify specific barriers to adherence and develop potential interventions to improve adherence.

SUBMITTER: Sanchez FG

PROVIDER: S-EPMC7657978 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeTo assess the accuracy of 5 subjective self-assessment tools (3 adherence measures and 2 psychometric scales) and pharmacy refill data in predicting objective electronically monitored nonadherence.DesignProspective cohort study.ParticipantsGlaucoma patients (> 40 years old, >1 medication with poor self-reported adherence) were recruited from University of Michigan Kellogg Eye Center for a study assessing the impact of a personalized glaucoma coaching program on medication adherence.MethodsParticipants completed an initial assessment including 5 self-assessment tools and a 3-month period of electronic monitoring of glaucoma medication adherence (AdhereTech); pharmacy refill data were obtained. Electronically monitored adherence was calculated monthly as the percentage of doses taken on time. The median of these adherence rates was designated as baseline adherence. Patients with adherence of ≤80% by electronic monitoring were considered nonadherent. Self-assessment tools were scored, and pharmacy refill data were summarized as the proportion of days covered. Correlation between measures of adherence was estimated with Pearson and Spearman correlation coefficients. Receiver operating characteristic curves, including estimation of area under the curve (AUC), sensitivity, specificity, and accuracy were used to compare measures of adherence with respect to predicting electronically monitored nonadherence.Main outcome measuresAccuracy of self-reported and pharmacy refill data adherence measures in predicting electronically monitored nonadherence.ResultsNinety-five patients completed 3 months of electronic monitoring with a median monthly adherence of 74 (± 21%); 53 patients (56%) were nonadherent. Pharmacy refill data were not correlated significantly with electronically monitored medication adherence (r = 0.12; P = 0.2). Of all the measures, a single-item adherence question ("Over the past month, what percentage of your drops do you think you took correctly?") showed the largest correlation with median electronically monitored adherence (r = 0.47; P < 0.0001), largest AUC for predicting nonadherence (AUC = 0.76 [95% confidence interval [CI], 0.66-0.87]), best accuracy (71% [95% CI, 61%-82%]), and good sensitivity (84% [95% CI, 73%-96%]).ConclusionsThe single-item question was the most accurate in predicting electronically monitored nonadherence among participants with poor self-reported adherence. In clinical practice, where alternatives are too resource intensive, this free single-item screening question can help to identify glaucoma patients at risk of poor medication adherence with reasonable accuracy.

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