改善成人慢性病患者服药依从性的行为经济学见解:一项范围审查方案。

Jacqueline Roseleur, Gillian Harvey, Nigel Stocks, Jonathan Karnon
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引用次数: 1

摘要

目的:本综述的目的是绘制关于使用行为经济学见解来改善慢性疾病成人药物依从性的证据。药物不依从性是有效管理慢性病的障碍,导致患者预后较差,并给卫生保健系统带来额外的经济负担。随着人口老龄化和慢性病患病率的增加,需要新的方法来影响患者的行为。使用行为经济学见解的方法可能有助于改善药物依从性,从而降低发病率、死亡率和未经管理的慢性病的财务成本。纳入标准:符合条件的研究将包括服用药物治疗慢性疾病的成年人。将考虑所有与高收入环境相关的干预措施,使用行为经济学的见解来改善成人的药物依从性。背景可能包括但不限于初级卫生保健、企业健康计划和健康保险计划。任何以英文发表的研究设计都将被考虑。在对患者进行药物治疗的机构进行的研究将被排除在外。方法:检索PubMed、Embase、Scopus、PsycINFO、EconLit、CINAHL等数据库。灰色文献将使用Google Scholar、OpenGrey和灰色文献报告进行搜索。一名审稿人将审查标题,然后两名审稿人将独立审查摘要以确定合格的研究。一位审稿人将提取研究特征、研究设计和研究结果的数据。第二个审稿人将验证抽取信息的25%。数据提取的结果将以表格形式呈现,并将呈现叙述性摘要。
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Behavioral economic insights to improve medication adherence in adults with chronic conditions: a scoping review protocol.

Objective: The objective of this review is to map the evidence on the use of behavioral economic insights to improve medication adherence in adults with chronic conditions.

Introduction: Medication non-adherence is a barrier to effectively managing chronic conditions, leading to poorer patient outcomes and placing an additional financial burden on healthcare systems. As the population ages and the prevalence of chronic disease increases, new ways to influence patient behavior are needed. Approaches that use insights from behavioral economics may help improve medication adherence, thus reducing morbidity, mortality and financial costs of unmanaged chronic diseases.

Inclusion criteria: Eligible studies will include adults taking medication for a chronic condition. All interventions relevant to high-income settings using insights from behavioral economics to improve medication adherence in adults will be considered. Contexts may include, but are not limited to, primary health care, corporate wellness programs and health insurance schemes. Any study design published in English will be considered. Studies in facilities where medication is administered to patients will be excluded.

Methods: PubMed, Embase, Scopus, PsycINFO, EconLit and CINAHL will be searched from database inception to present. Gray literature will be searched using Google Scholar, OpenGrey and the Grey Literature Report. One reviewer will review titles, and then two reviewers will independently review abstracts to identify eligible studies. One reviewer will extract data on study characteristics, study design and study outcomes. A second reviewer will validate 25% of the extracted information. The results of the data extraction will be presented in a table, and a narrative summary will be presented.

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