药物信息汇编和药物-药物相互作用信息数据库是临床医生和药剂师努力避免由于暴露于潜在的药物-药物相互作用(PDDI)而导致的不良事件的关键资源。我们的目标是开发信息模型,注释数据,和搜索工具,这将有助于PDDI信息的解释。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检索。两名审稿人对所收录的文章进行了专题分析。进行了与药物信息专家的非结构化访谈,并进行了类似的编码。信息需求,工作流程,并确定了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PDDI信息的解释有关的56类信息需求,包括药物和相互作用信息;研究设计;包括临床细节在内的证据。报告的质量和内容,和后果;以及潜在的建议。我们还确定了PDDI信息系统的优势/劣势。
我们确定了对于总结PDDI可能最有效的信息种类。我们采访的药物信息专家有不同的目标,建议需要详细的信息模型和灵活的演示。确定了以前工作中未讨论的一些信息,包括药物管理的时间重叠,相互作用的生物学合理性,以及评估报告的质量和内容。对PDDI信息的丰富结构化描述可能有助于药物信息专家更有效地解释数据并提出建议。需要有效的信息模型和系统设计,以最大程度地利用这些信息。
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.