School of Pharmacy, Dublin, Ireland.
School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen, Scotland, UK.
Clin Pharmacol Ther. 2018 Jun;103(6):1052-1060. doi: 10.1002/cpt.865. Epub 2017 Oct 10.
Antihypertensive medication nonadherence is highly prevalent, leading to uncontrolled blood pressure. Methods that facilitate the targeting and tailoring of adherence interventions in clinical settings are required. Group-Based Trajectory Modeling (GBTM) is a newer method to evaluate adherence using pharmacy dispensing (refill) data that has advantages over traditional refill adherence metrics (e.g. Proportion of Days Covered) by identifying groups of patients who may benefit from adherence interventions, and identifying patterns of adherence behavior over time that may facilitate tailoring of an adherence intervention. We evaluated adherence to antihypertensive medication in 905 patients over a 12-month period in a community pharmacy setting using GBTM, identifying three subgroups of adherence patterns: 52.8%, 40.7%, and 6.5% had very high, high, and low adherence, respectively. However, GBTM failed to demonstrate predictive validity with blood pressure at 12 months. Further research on the validity of adherence measures that facilitate interventions in clinical settings is required.
抗高血压药物不依从的现象非常普遍,导致血压控制不良。因此,需要在临床环境中采用能够方便地确定药物依从性干预目标和调整干预措施的方法。基于群组的轨迹建模(GBTM)是一种使用药房配药( refill )数据评估依从性的新方法,它通过识别可能受益于依从性干预的患者群体,并识别随时间推移的依从行为模式,从而为传统的 refill 依从性指标(例如“覆盖率”)提供了优势。我们使用 GBTM 评估了 905 名患者在社区药房环境中 12 个月的抗高血压药物依从性,确定了三种依从模式亚组:分别有 52.8%、40.7%和 6.5%的患者具有非常高、高和低的依从性。然而,GBTM 未能在 12 个月时证明对血压具有预测性。需要进一步研究能够在临床环境中促进干预的依从性测量的有效性。