\textbf{Trial design} Crossover randomized controlled trial. \textbf{Methods} An AI tool, Easy-ICD, was developed to assist clinical coders and was tested for improving both accuracy and time in a user study in Norway and Sweden. Participants were randomly assigned to two groups, and crossed over between coding complex (longer) texts versus simple (shorter) texts, while using our tool versus not using our tool. \textbf{Results} Based on Mann-Whitney U test, the median coding time difference for complex clinical text sequences was 123 seconds (\emph{P}\textless.001, 95\% CI: 81 to 164), representing a 46\% reduction in median coding time when our tool is used. There was no significant time difference for simpler text sequences. For coding accuracy, the improvement we noted for both complex and simple texts was not significant. \textbf{Conclusions} This study demonstrates the potential of AI to transform common tasks in clinical workflows, with ostensible positive impacts on work efficiencies for complex clinical coding tasks. Further studies within hospital workflows are required before these presumed impacts can be more clearly understood.

本研究针对临床编码实践中的效率问题，开发了一种名为Easy-ICD的人工智能工具，以提高编码的准确性和速度。研究结果显示，使用该工具时，处理复杂文本的编码时间中位数减少了46%，表明AI可以显著改善复杂临床编码任务的工作效率，尽管准确性未见显著提高。

人工智能改善斯堪的纳維亚的临床编码实践：一项交叉随机对照试验