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本文引用的文献

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Modeling Contingency in Veteran Community Reintegration: A Mixed Methods Approach.退伍军人社区重新融入中的应急情况建模:一种混合方法
J Mix Methods Res. 2023 Jan;17(1):70-92. doi: 10.1177/15586898211059616. Epub 2022 Feb 24.
2
Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study.在一个大型学术医疗中心实施基于抢先性 DNA 序列的药物基因组学检测:梅奥-贝勒 RIGHT 10K 研究。
Genet Med. 2022 May;24(5):1062-1072. doi: 10.1016/j.gim.2022.01.022. Epub 2022 Mar 21.
3
Evaluation of the Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program at initial test sites.评估退伍军人事务部(VA)退伍军人药物基因组学检测(PHASER)临床项目在初始测试点的情况。
Pharmacogenomics. 2021 Nov;22(17):1121-1133. doi: 10.2217/pgs-2021-0089. Epub 2021 Oct 27.
4
Configurational Causal Modeling and Logic Regression.组态因果建模与逻辑回归。
Multivariate Behav Res. 2023 Mar-Apr;58(2):292-310. doi: 10.1080/00273171.2021.1971510. Epub 2021 Oct 1.
5
Coincidence analysis: a new method for causal inference in implementation science.吻合分析:实施科学中因果推断的一种新方法。
Implement Sci. 2020 Dec 11;15(1):108. doi: 10.1186/s13012-020-01070-3.
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Strategic vision for improving human health at The Forefront of Genomics.基因组学前沿改善人类健康的战略愿景。
Nature. 2020 Oct;586(7831):683-692. doi: 10.1038/s41586-020-2817-4. Epub 2020 Oct 28.
7
Development of an integrative coding framework for evaluating context within implementation science.制定一个综合编码框架,用于评估实施科学中的背景。
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Strategy Configurations Directly Linked to Higher Hepatitis C Virus Treatment Starts: An Applied Use of Configurational Comparative Methods.策略配置与更高的丙型肝炎病毒治疗启动直接相关:配置比较方法的应用。
Med Care. 2020 May;58(5):e31-e38. doi: 10.1097/MLR.0000000000001319.
9
Clarity out of chaos: Use of theory in implementation research.从混沌中理清头绪:在实施研究中运用理论。
Psychiatry Res. 2020 Jan;283:112461. doi: 10.1016/j.psychres.2019.06.036. Epub 2019 Jun 23.
10
Implementing pharmacogenetic testing in rural primary care practices: a pilot feasibility study.在农村基层医疗实践中实施药物遗传学检测:一项试点可行性研究。
Pharmacogenomics. 2019 Apr;20(6):433-446. doi: 10.2217/pgs-2018-0200. Epub 2019 Apr 15.

一项用于确定在临床环境中实施药物遗传学检测最佳实践的混合方法方案。

A Mixed-Methods Protocol to Identify Best Practices for Implementing Pharmacogenetic Testing in Clinical Settings.

作者信息

Sperber Nina R, Cragun Deborah, Roberts Megan C, Bendz Lisa M, Ince Parker, Gonzales Sarah, Haga Susanne B, Wu R Ryanne, Petry Natasha J, Ramsey Laura, Uber Ryley

机构信息

Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA.

Durham VA Health Care System, Durham, NC 27705, USA.

出版信息

J Pers Med. 2022 Aug 13;12(8):1313. doi: 10.3390/jpm12081313.

DOI:10.3390/jpm12081313
PMID:36013262
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9410119/
Abstract

Using a patient's genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers-the cases-at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.

摘要

利用患者的基因信息来指导药物处方在临床上可能是有效的;然而,这种做法尚未得到广泛实施。卫生系统需要有关如何与医疗服务提供者合作以提高药物遗传学检测利用率的指导。实施科学领域的方法可能会揭示影响现实环境中药物遗传学检测使用的复杂因素以及提高利用率的目标领域。本文提出了一种研究精准医学应用的方法,该方法利用定性和定量相结合的方法以及实施科学框架,以了解哪些因素或因素组合始终导致药物遗传学检测的高利用率与低利用率。这种方法包括两个阶段:(1)从四个临床机构的医疗服务提供者(即案例)收集定性和定量数据,了解他们在药物遗传学检测方面的经验和使用情况,以确定突出因素;(2)使用构型比较法(CCM)进行分析,利用数学算法确定区分高利用率医疗服务提供者和低利用率医疗服务提供者的最小必要和充分因素。这种方法的优点是它可用于小到中等规模的样本,并且通过展示现实环境中的各种情况如何相互作用影响利用率,从而考虑到了现实环境中存在的条件。