AI工具助医生更快完成复杂病历编码，效率提升46%。
Artificial intelligence to improve clinical coding practice in Scandinavia: a crossover randomized controlled trial
- 用AI辅助编码，复杂文本处理速度显著加快
- 复杂文本编码时间减少123秒，降幅达46%
- 适合医院临床编码员及医疗AI落地研究者
本研究采用交叉随机对照试验设计，在挪威和瑞典开展用户实验，评估AI工具Easy-ICD对临床编码准确性和效率的影响。参与者被随机分配至两组，交替使用工具与不使用工具，分别处理复杂（较长）和简单（较短）的临床文本。结果显示，使用该工具后，复杂临床文本的编码时间中位数减少123秒（P<0.001，95%置信区间：81至164），即效率提升46%；而简单文本无显著时间差异。编码准确性在复杂与简单文本上均未出现显著提升。研究证明，AI在复杂临床编码任务中具有提升工作效率的潜力，但需进一步在真实医院流程中验证其效果。
原文摘要 · Abstract (English)
\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.
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