Meta-Analysis of Interventions to Improve Medication Adherence

改善药物依从性干预措施的荟萃分析

• 批准号: 7860126
• 负责人: Vicki S Conn
• 金额: $ 51.26万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-07 至 2013-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7860126
• 关键词: Address; Area; Characteristics; Clinical; Code; Computers; Conflict (Psychology); Cues; Data; Databases; Diagnosis; Disease; Dose; Drug Prescriptions; Effectiveness of Interventions; Elderly; Employee Strikes; Ethnic Origin; Feedback; Frustration; Funding; Future; Gender; Goals; Hand; Health; Health Care Costs; Health behavior change; Intervention; Intervention Studies; Journals; Knowledge; Label; Language; Link; Literature; Meta-Analysis; Methodology; Methods; Metric; Minority; Modeling; Modification; Monitor; Morbidity - disease rate; Outcome; Participant; Patients; Pharmaceutical Preparations; Principal Investigator; Procedures; Provider; Public Health; Publication Bias; Race; Recommendation; Registries; Relative (related person); Research; Research Design; Research Personnel; Sample Size; Sampling; Science; Sex Characteristics; Specific qualifier value; Testing; Therapeutic; Treatment Efficacy; Variant; Weight; Work; World Health Organization; abstracting; analog; base; cost; experience; improved; indexing; innovation; intervention effect; medication compliance; mortality; patient population; programs; public health relevance; randomized trial; study characteristics; symposium; text searching; therapy design

DESCRIPTION (provided by applicant): Meta-Analysis of Interventions to Improve Medication Adherence Inadequate medication adherence (MA) contributes to increased morbidity, mortality, patient and provider frustration, and health care costs. Alarming persistent nonadherence is consistently documented in diverse samples. Scientific evidence about the efficacy of interventions is essential to develop MA interventions that improve health outcomes and reduce costs. Research testing many MA interventions has yielded results that are sometimes conflicting and often unclear. These primary studies have not been quantitatively synthesized, which seriously impedes progress in both practice and research. This project's purpose is to integrate scientific knowledge about interventions designed to increase MA. The project addresses these specific aims: " Determine the strength of the research base about interventions to increase MA. " Specify and quantify the effect of interventions on MA. " Distinguish factors (e.g., intervention characteristics such as dose reduction or packaging, participant attributes such as diagnoses or ethnicity) that moderate the effect of interventions to increase MA. This research team has used the proposed methods in several syntheses, including a recent preliminary meta- analysis of MA interventions tested in randomized trials with older adults. An extensive and rigorous literature search will avoid the bias that typical limited searches can cause. Strategies include searches by computer and journal searches by hand, searches of ancestry lists and registries databases, reviews of graduate projects, examinations of conference/association abstracts, and contacts with senior authors on retrieved studies and principal investigators of NIH-funded studies. Independent data extractors will reliably code for intervention, methodological, and participant attributes. Analysis plans include: d-index to standardize the magnitude of effect, sample size weighted calculations, random-effects models, homogeneity (Q) assessment, publication bias analysis (I2), and to facilitate interpretation - Common Language Effect Size and conversion to original metric. Moderator analyses using meta-analysis analogues of regression and ANOVA will reveal which intervention characteristics (e.g., MA feedback, prompts) are associated with larger increases in MA. Minority and gender differences in intervention effectiveness will be examined as well. Provisional multivariate moderator analyses using meta-regression with selected subsets of moderators will be conducted. The major impact of the project will be derived from the moderator analyses which will determine which intervention characteristics are linked with the best MA outcomes. Findings will improve public health by synthesizing diverse results in order to aid the design of interventions that help people increase their MA and achieve therapeutic goals. Study findings will have a major immediate impact on science by identifying unanswered research questions as well as areas in which the science has been settled. This work's compelling importance and broad scope make funding necessary to achieve these important aims. PUBLIC HEALTH RELEVANCE: This project will statistically summarize the effects of hundreds of previous studies testing interventions to improve medication adherence. The findings will clarify which interventions work best to improve medication adherence. The study will also determine if interventions work best for people with particular characteristics.

描述（由申请人提供）：改善药物依从性干预措施的荟萃分析 药物依从性 (MA) 不足会导致发病率、死亡率、患者和提供者的挫败感以及医疗保健成本增加。不同样本中一致记录了令人震惊的持续不依从性。关于干预措施有效性的科学证据对于制定可改善健康结果和降低成本的 MA 干预措施至关重要。对许多 MA 干预措施进行测试的研究得出的结果有时是相互矛盾的，而且往往不明确。这些初步研究尚未定量综合，严重阻碍了实践和研究的进展。该项目的目的是整合有关旨在提高 MA 的干预措施的科学知识。该项目致力于实现以下具体目标：“确定有关增加 MA 的干预措施的研究基础的强度。”指定并量化干预措施对 MA 的影响。 “区分调节干预措施增加 MA 效果的因素（例如剂量减少或包装等干预特征、诊断或种族等参与者属性）。该研究小组在多项综合中使用了所提出的方法，包括最近在老年人随机试验中测试的 MA 干预措施的初步荟萃分析。广泛而严格的文献检索将避免典型的有限搜索可能导致的偏差。 策略包括计算机检索和手工期刊检索、祖先列表和登记数据库检索、研究生项目审查、会议/协会摘要检查以及与检索研究的资深作者和 NIH 资助研究的主要研究人员联系。独立的数据提取器将为干预、方法和参与者属性进行可靠的编码。分析计划包括：标准化影响大小的 d 指数、样本量加权计算、 随机效应模型、同质性 (Q) 评估、发表偏倚分析 (I2) 以及促进解释 - 通用语言效应大小和转换为原始指标。使用回归和方差分析的荟萃分析类似物进行的调节分析将揭示哪些干预特征（例如，MA 反馈、提示）与 MA 的较大增加相关。干预效果中的少数民族和性别差异也将受到审查。 将使用元回归对选定的调节器子集进行临时多变量调节器分析。该项目的主要影响将来自调节分析，该分析将确定哪些干预特征与最佳 MA 结果相关。研究结果将通过综合不同的结果来改善公共卫生，以帮助设计干预措施，帮助人们提高 MA 并实现治疗目标。研究结果将对 通过确定未解答的研究问题以及科学已解决的领域来研究科学。这项工作具有引人注目的重要性和广泛的范围，因此需要资金来实现这些重要目标。 公共卫生相关性：该项目将统计总结之前数百项测试干预措施以提高药物依从性的研究的效果。研究结果将阐明哪些干预措施最能提高药物依从性。该研究还将确定干预措施是否最适合具有特定特征的人。