Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.
Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.
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DOI：
10.1186/s12911-017-0419-3
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发表时间：
2017-02-22
影响因子：
3.5
通讯作者：
Hochheiser H
中科院分区：
文献类型：
--
作者：
Romagnoli KM;Nelson SD;Hines L;Empey P;Boyce RD;Hochheiser H
药物信息概要和药物-药物相互作用信息数据库是临床医生和药剂师避免暴露于潜在药物-药物相互作用(PDDIs)引起的不良事件的重要资源。我们的目标是开发有助于解释PDDI信息的信息模型、带注释的数据和搜索工具。为了更好地了解为药物信息资源搜索和合成PDDI证据的专家的信息需求和工作实践，我们进行了一项调查，将对已发表文献的主题分析与非结构化访谈相结合。从最初的一组相关文章开始，我们开发了搜索词并进行了文献搜索。两名审查员对收录的文章进行了专题分析。对药物信息专家进行了非结构化采访，并进行了类似的编码。确定了信息需求、工作流程以及信息系统潜在优势和劣势的指标。对92篇论文和10次访谈的审查确定了与解释PDDI信息有关的56类信息需求，包括药物和相互作用信息；研究设计；证据包括临床细节、报告的质量和内容、结果；以及可能的建议。我们还确定了PDDI信息系统的优势/劣势。我们确定了可能对总结PDDIS最有效的信息类型。我们采访的药物信息专家有不同的目标，表明需要详细的信息模型和灵活的陈述。确定了以前工作中没有讨论的几个信息需求，包括给药的时间重叠、相互作用的生物学可信度以及对报告质量和内容的评估。对PDDI信息的结构丰富的描述可能有助于药物信息专家更有效地解释数据和制定建议。需要有效的信息模型和系统设计，以最大限度地利用这些信息。本文的在线版本(doi：10.1186/s12911-0170419-3)包含补充材料，授权用户可以使用。
Drug information compendia and drug-drug interaction information databases are critical resources for clinicians and pharmacists working to avoid adverse events due to exposure to potential drug-drug interactions (PDDIs). Our goal is to develop information models, annotated data, and search tools that will facilitate the interpretation of PDDI information. To better understand the information needs and work practices of specialists who search and synthesize PDDI evidence for drug information resources, we conducted an inquiry that combined a thematic analysis of published literature with unstructured interviews. Starting from an initial set of relevant articles, we developed search terms and conducted a literature search. Two reviewers conducted a thematic analysis of included articles. Unstructured interviews with drug information experts were conducted and similarly coded. Information needs, work processes, and indicators of potential strengths and weaknesses of information systems were identified. Review of 92 papers and 10 interviews identified 56 categories of information needs related to the interpretation of PDDI information including drug and interaction information; study design; evidence including clinical details, quality and content of reports, and consequences; and potential recommendations. We also identified strengths/weaknesses of PDDI information systems. We identified the kinds of information that might be most effective for summarizing PDDIs. The drug information experts we interviewed had differing goals, suggesting a need for detailed information models and flexible presentations. Several information needs not discussed in previous work were identified, including temporal overlaps in drug administration, biological plausibility of interactions, and assessment of the quality and content of reports. Richly structured depictions of PDDI information may help drug information experts more effectively interpret data and develop recommendations. Effective information models and system designs will be needed to maximize the utility of this information. The online version of this article (doi:10.1186/s12911-017-0419-3) contains supplementary material, which is available to authorized users.