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Meta-Analysis of Interventions to Improve Medication Adherence

改善药物依从性干预措施的荟萃分析

基本信息

批准号：
8454502
负责人：
Vicki S Conn
金额：
$ 21.9万
依托单位：
UNIVERSITY OF MISSOURI-COLUMBIA
依托单位国家：
美国
项目类别：
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/8454502
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 Healthcare 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 Sampling Science Sex Characteristics Specific qualifier value Testing Therapeutic Treatment Efficacy United States National Institutes of Health Variant Weight Work World Health Organization abstracting analog base cost experience improved indexing innovation intervention effect medication compliance mortality programs public health relevance randomized trial study characteristics symposium text searching therapy design

项目摘要

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.

描述（由申请人提供）：改善药物依从性的干预措施的荟萃分析药物依从性不足（MA）会导致发病率、死亡率、患者和提供者的挫折感以及医疗保健成本增加。令人担忧的持续不依从性在不同样本中一致记录。关于干预措施有效性的科学证据对于制定改善健康结果和降低成本的MA干预措施至关重要。对许多千年生态系统评估干预措施进行的研究得出的结果有时相互矛盾，而且往往不明确。这些初步的研究还没有得到定量的综合，这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增加MA的干预措施的科学知识。该项目致力于实现这些具体目标：“确定关于增加千年生态系统评估的干预措施的研究基础的实力。 “具体说明并量化干预措施对MA的影响。 “区分因素（例如，干预特征，如剂量减少或包装，受试者属性，如诊断或种族），这些因素会缓和干预措施对增加MA的影响。这个研究小组已经在几个合成中使用了所提出的方法，包括最近对在老年人随机试验中测试的MA干预措施的初步Meta分析。广泛而严格的文献检索将避免典型的有限检索可能导致的偏倚。策略包括计算机检索和手工期刊检索，祖先列表和注册数据库的检索，研究生项目的审查，会议/协会摘要的检查，以及与检索到的研究的资深作者和NIH资助研究的主要研究者的联系。独立的数据提取器将可靠地编码干预，方法和参与者属性。分析计划包括：d指数用于标准化效应大小、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），并便于解释-通用语言效应大小和转换为原始指标。使用回归和ANOVA的荟萃分析类似物进行的主持人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。还将审查干预效果方面的少数群体和性别差异。将使用荟萃回归对选定的调节因子子集进行临时多变量调节因子分析。该项目的主要影响将来自主持人分析，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各种结果来改善公共卫生，以帮助设计干预措施，帮助人们增加MA并实现治疗目标。研究结果将通过确定未回答的研究问题以及科学已经解决的领域对科学产生重大的直接影响。这项工作的紧迫重要性和广泛的范围，使得有必要提供资金来实现这些重要目标。