Pironet Antoine, Phillips L Alison, Vrijens Bernard
AARDEX Group, Seraing, Belgium.
Iowa State University, Ames, IA, United States.
Interact J Med Res. 2025 Feb 6;14:e63987. doi: 10.2196/63987.
Medication adherence, or how patients take their medication as prescribed, is suboptimal worldwide. Improving medication-taking habit might be an effective way to improve medication adherence. However, habit is difficult to quantify, and conventional habit metrics are self-reported, with recognized limitations. Recently, several objective habit metrics have been proposed, based on objective medication-taking data.
We aim to explore the correlation between objective habit metrics and objective medication adherence on a large dataset.
The Medication Event Monitoring System Adherence Knowledge Center, a database of anonymized electronic medication intake data from ambulant participants enrolled in past clinical studies, was used as the data source. Electronic medication intake data from participants following a once-daily regimen and monitored for 14 days or more were used. Further, two objective habit metrics were computed from each participant's medication intake history: (1) SD of the hour of intake, representing daily variability in the timing of medication intakes, and (2) weekly cross-correlation, representing weekly consistency in the timing of medication intakes. The implementation component of medication adherence was quantified using (1) the proportion of doses taken and (2) the proportion of correct days.
A total of 15,818 participants met the criteria. These participants took part in 108 clinical studies mainly focused on treatments for hypertension (n=4737, 30%) and osteoporosis (n=3353, 21%). The SD of the hour of intake was significantly negatively correlated with the 2 objective adherence metrics: proportion of correct days (Spearman correlation coefficient, ρ=-0.62, P<.001) and proportion of doses taken (ρ=-0.09, P<.001). The weekly cross-correlation was significantly positively correlated with the 2 objective adherence metrics: proportion of correct days (ρ=0.55, P<.001) and proportion of doses taken (ρ=0.32, P<.001). A lower daily or weekly variability in the timing of medication intakes is thus associated with better medication adherence. However, no variability is not the norm, as only 3.6% of participants have 95% of their intakes in a 1-hour window. Among the numerous factors influencing medication adherence, habit strength is an important one as it explains over 30% of the variance in medication adherence.
Objective habit metrics are correlated to objective medication adherence. Such objective habit metrics can be used to monitor patients and identify those who may benefit from habit-building support.
药物依从性，即患者按照医嘱服药的情况，在全球范围内都不尽人意。改善服药习惯可能是提高药物依从性的有效方法。然而，习惯难以量化，传统的习惯指标是自我报告的，存在公认的局限性。最近，基于客观的服药数据提出了几种客观的习惯指标。
我们旨在探讨在一个大型数据集中客观习惯指标与客观药物依从性之间的相关性。
使用药物事件监测系统依从性知识中心，这是一个来自过去临床研究中纳入的门诊参与者的匿名电子服药数据数据库，作为数据源。使用来自遵循每日一次服药方案并监测14天或更长时间的参与者的电子服药数据。此外，从每个参与者的服药历史中计算出两个客观的习惯指标：（1）服药时间的标准差，代表每日服药时间的变异性，以及（2）每周互相关性，代表每周服药时间的一致性。使用（1）服药剂量比例和（2）正确服药天数比例来量化药物依从性的执行情况。
共有15818名参与者符合标准。这些参与者参加了108项临床研究，主要集中在高血压治疗（n = 4737，30%）和骨质疏松症治疗（n = 3353，21%）。服药时间的标准差与两个客观依从性指标显著负相关：正确服药天数比例（斯皮尔曼相关系数，ρ = -0.62，P <.001）和服药剂量比例（ρ = -0.09，P <.001）。每周互相关性与两个客观依从性指标显著正相关：正确服药天数比例（ρ = 0.55，P <.001）和服药剂量比例（ρ = 0.32，P <.001）。因此，服药时间的每日或每周变异性较低与更好的药物依从性相关。然而，没有变异性并非常态，因为只有3.6%的参与者95%的服药时间在1小时窗口内。在影响药物依从性的众多因素中，习惯强度是一个重要因素，因为它解释了药物依从性超过30%的方差。
客观习惯指标与客观药物依从性相关。这种客观习惯指标可用于监测患者并识别那些可能从习惯养成支持中受益的人。
