Chen Yu, Gao Jing, Lu Minmin
School of Nursing, Fudan University, Shanghai, China.
Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
J Adv Nurs. 2024 Jan;80(1):11-41. doi: 10.1111/jan.15776. Epub 2023 Jul 5.
To synthesize the published studies on medication adherence trajectories among patients with chronic diseases and identify the influencing factors.
Systematic review.
Medline (Ovid), Embase (Ovid) and Web of Science core collection were searched from database inception to 1 July 2022.
Potentially eligible articles were independently screened by three reviewers using set inclusion and exclusion criteria. The Joanna Briggs Institute critical appraisal checklist for cohort studies was used to appraise the quality of the included articles. Three reviewers independently evaluated the quality, extracted data and resolved differences by consensus. Results were presented using descriptive synthesis, and the prevalence of recategorised medication adherence trajectories was calculated from the published data.
Fifty studies were included. Medication adherence trajectories among patients with chronic diseases were synthesized into six categories: adherence, non-adherence, decreasing adherence, increasing adherence, fluctuating adherence and moderate adherence. Low and moderate evidence showed that (1) patient-related factors, including age, sex, race, marital status and mental status; (2) healthcare team and system-related factors, including healthcare utilization, insurance and primary prescriber specialty; (3) socioeconomic factors including education, income and employment status; (4) condition-related factors including complications and comorbidities and (5) therapy-related factors including the number of medications, use of other medications, and prior medication adherence behaviours were factors influencing the medication adherence trajectory. Marital status and prior medication adherence behaviour were the only influencing factors with moderate evidence of an effect.
The medication adherence trajectory among patients with chronic diseases varied widely. Further studies are warranted to determine contributory factors.
Healthcare providers should be aware that patients' medication adherence has different trajectories and should take appropriate measures to improve patients' medication adherence patterns.
None. As a systematic review, patients and the public were not involved.
综合已发表的关于慢性病患者药物治疗依从性轨迹的研究，并确定影响因素。
系统评价。
检索了Medline（Ovid）、Embase（Ovid）和Web of Science核心合集，检索时间从数据库建立至2022年7月1日。
由三名评审员根据设定的纳入和排除标准独立筛选潜在符合条件的文章。使用乔安娜·布里格斯研究所队列研究批判性评价清单来评估纳入文章的质量。三名评审员独立评估质量、提取数据并通过协商解决分歧。结果采用描述性综合呈现，并根据已发表的数据计算重新分类的药物治疗依从性轨迹的患病率。
纳入50项研究。慢性病患者的药物治疗依从性轨迹被综合分为六类：依从、不依从、依从性下降、依从性增加、依从性波动和中度依从。低质量和中等质量证据表明：（1）患者相关因素，包括年龄、性别、种族、婚姻状况和精神状态；（2）医疗团队和系统相关因素，包括医疗服务利用、保险和初级开方医生专业；（3）社会经济因素，包括教育、收入和就业状况；（4）病情相关因素，包括并发症和合并症；（5）治疗相关因素，包括药物数量、其他药物的使用以及既往药物治疗依从行为，这些都是影响药物治疗依从性轨迹的因素。婚姻状况和既往药物治疗依从行为是仅有的有中等证据表明有影响的因素。
慢性病患者的药物治疗依从性轨迹差异很大。有必要进行进一步研究以确定促成因素。
医疗服务提供者应意识到患者的药物治疗依从性有不同轨迹，应采取适当措施改善患者的药物治疗依从模式。
无。作为一项系统评价，患者和公众未参与。
