Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin 54449-5790, USA.
J Am Med Inform Assoc. 2010 Mar-Apr;17(2):178-81. doi: 10.1136/jamia.2009.001651.
Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.
临床医生面临着越来越多的生物医学数据。评估能够准确和及时做出临床决策的系统的疗效值得引起相应的关注。本文讨论了多读者多病例（MRMC）实验设计和线性混合模型，作为评估和比较临床医生读者必须解释数据视觉显示的决策任务的决策准确性和延迟（时间）的方法。这些工具可以评估和比较决策准确性和延迟（时间）。这些在放射学成像研究中广泛使用的实验和统计技术，相对于更传统的定量方法（如百分比正确测量和方差分析）具有许多实际和分析上的优势，并且因其统计效率和通用性而受到推荐。作为附录，提供了一个使用现成的、免费的和商业统计软件的示例分析。虽然这些技术并不适用于所有评估问题，但它们可以为医学信息学研究的评估工具包提供有价值的补充。
