School of Nursing, University of North Carolina at Chapel Hill, NC, USA.
College of Nursing, University of Kentucky, Lexington, KY, USA.
Eur J Cardiovasc Nurs. 2019 Dec;18(8):667-678. doi: 10.1177/1474515119860321. Epub 2019 Jun 27.
Adherence to evidence-based therapy is essential for optimal management of heart failure. Yet, medication adherence is poor in heart failure patients. The Ascertaining Barriers to Compliance Project decomposed the medication adherence process into initiation, implementation, and discontinuation stages, but electronic monitoring-based adherence analyses usually do not consider this process.
The aim of this study was to describe individual-patient patterns of medication adherence from electronic monitoring data among adults with chronic heart failure, adherence types, and risk factors for increased all-cause hospitalization including measures of poor adherence such as discontinuation.
Data from two prospective studies of adherence measured with electronic monitoring for heart failure patients were combined and restricted to monitoring of angiotensin-converting enzyme inhibitors and beta-blockers over an initial three-month period. Hospitalizations were recorded for this period as well as for a three-month follow-up period. Analyses were conducted using adaptive modeling methods to identify individual-patient adherence patterns, adherence types, and risk factors for an increased hospitalization rate.
Using electronic monitoring data for 254 heart failure patients, four adherence types were identified: highly consistent, consistent but variable, moderately consistent, and poorly consistent. Sixteen individually significant risk factors for increased hospitalization rates were identified and used to generate a multiple risk factors model. Medication discontinuation was the most important individual risk factor and most important in the multiple risk factors model.
Discontinuation of angiotensin-converting enzyme inhibitors or beta-blockers increases hospitalization rates for heart failure patients. Interventions that effectively address this problem are urgently needed.
遵循基于证据的治疗是心力衰竭最佳管理的关键。然而,心力衰竭患者的药物治疗依从性很差。“确定依从性障碍项目”将药物治疗依从性过程分解为起始、实施和停药阶段,但基于电子监测的依从性分析通常不考虑这一过程。
本研究旨在从慢性心力衰竭患者电子监测数据中描述个体患者的药物治疗依从性模式、依从类型以及导致全因住院率增加的危险因素,包括停药等不良依从性的衡量标准。
合并了两项使用电子监测评估心力衰竭患者依从性的前瞻性研究的数据,并将其限制在初始三个月期间监测血管紧张素转换酶抑制剂和β受体阻滞剂。在此期间以及三个月的随访期间记录住院情况。使用自适应建模方法进行分析,以确定个体患者的依从性模式、依从类型以及增加住院率的危险因素。
使用 254 例心力衰竭患者的电子监测数据,确定了四种依从类型:高度一致、一致但可变、中度一致和不一致。确定了 16 个与增加住院率相关的个体显著危险因素,并用于生成多危险因素模型。药物停药是最重要的个体危险因素,也是多危险因素模型中最重要的因素。
血管紧张素转换酶抑制剂或β受体阻滞剂的停药会增加心力衰竭患者的住院率。迫切需要有效的干预措施来解决这个问题。