PDF(Pubmed)
Abstract：
BACKGROUND: Information overflow, a common problem in the present clinical environment, can be mitigated by summarizing clinical data. Although there are several solutions for clinical summarization, there is a lack of a complete overview of the research relevant to this field.
OBJECTIVE: This study aims to identify state-of-the-art solutions for clinical summarization, to analyze their capabilities, and to identify their properties.
METHODS: A scoping review of articles published between 2005 and 2022 was conducted. With a clinical focus, PubMed and Web of Science were queried to find an initial set of reports, later extended by articles found through a chain of citations. The included reports were analyzed to answer the questions of where, what, and how medical information is summarized; whether summarization conserves temporality, uncertainty, and medical pertinence; and how the propositions are evaluated and deployed. To answer how information is summarized, methods were compared through a new framework \"collect-synthesize-communicate\" referring to information gathering from data, its synthesis, and communication to the end user.
RESULTS: Overall, 128 articles were included, representing various medical fields. Exclusively structured data were used as input in 46.1% (59/128) of papers, text in 41.4% (53/128) of articles, and both in 10.2% (13/128) of papers. Using the proposed framework, 42.2% (54/128) of the records contributed to information collection, 27.3% (35/128) contributed to information synthesis, and 46.1% (59/128) presented solutions for summary communication. Numerous summarization approaches have been presented, including extractive (n=13) and abstractive summarization (n=19); topic modeling (n=5); summary specification (n=11); concept and relation extraction (n=30); visual design considerations (n=59); and complete pipelines (n=7) using information extraction, synthesis, and communication. Graphical displays (n=53), short texts (n=41), static reports (n=7), and problem-oriented views (n=7) were the most common types in terms of summary communication. Although temporality and uncertainty information were usually not conserved in most studies (74/128, 57.8% and 113/128, 88.3%, respectively), some studies presented solutions to treat this information. Overall, 115 (89.8%) articles showed results of an evaluation, and methods included evaluations with human participants (median 15, IQR 24 participants): measurements in experiments with human participants (n=31), real situations (n=8), and usability studies (n=28). Methods without human involvement included intrinsic evaluation (n=24), performance on a proxy (n=10), or domain-specific tasks (n=11). Overall, 11 (8.6%) reports described a system deployed in clinical settings.
CONCLUSIONS: The scientific literature contains many propositions for summarizing patient information but reports very few comparisons of these proposals. This work proposes to compare these algorithms through how they conserve essential aspects of clinical information and through the \"collect-synthesize-communicate\" framework. We found that current propositions usually address these 3 steps only partially. Moreover, they conserve and use temporality, uncertainty, and pertinent medical aspects to varying extents, and solutions are often preliminary.
OBJECTIVE: This study aims to identify state-of-the-art solutions for clinical summarization, to analyze their capabilities, and to identify their properties.
METHODS: A scoping review of articles published between 2005 and 2022 was conducted. With a clinical focus, PubMed and Web of Science were queried to find an initial set of reports, later extended by articles found through a chain of citations. The included reports were analyzed to answer the questions of where, what, and how medical information is summarized; whether summarization conserves temporality, uncertainty, and medical pertinence; and how the propositions are evaluated and deployed. To answer how information is summarized, methods were compared through a new framework \"collect-synthesize-communicate\" referring to information gathering from data, its synthesis, and communication to the end user.
RESULTS: Overall, 128 articles were included, representing various medical fields. Exclusively structured data were used as input in 46.1% (59/128) of papers, text in 41.4% (53/128) of articles, and both in 10.2% (13/128) of papers. Using the proposed framework, 42.2% (54/128) of the records contributed to information collection, 27.3% (35/128) contributed to information synthesis, and 46.1% (59/128) presented solutions for summary communication. Numerous summarization approaches have been presented, including extractive (n=13) and abstractive summarization (n=19); topic modeling (n=5); summary specification (n=11); concept and relation extraction (n=30); visual design considerations (n=59); and complete pipelines (n=7) using information extraction, synthesis, and communication. Graphical displays (n=53), short texts (n=41), static reports (n=7), and problem-oriented views (n=7) were the most common types in terms of summary communication. Although temporality and uncertainty information were usually not conserved in most studies (74/128, 57.8% and 113/128, 88.3%, respectively), some studies presented solutions to treat this information. Overall, 115 (89.8%) articles showed results of an evaluation, and methods included evaluations with human participants (median 15, IQR 24 participants): measurements in experiments with human participants (n=31), real situations (n=8), and usability studies (n=28). Methods without human involvement included intrinsic evaluation (n=24), performance on a proxy (n=10), or domain-specific tasks (n=11). Overall, 11 (8.6%) reports described a system deployed in clinical settings.
CONCLUSIONS: The scientific literature contains many propositions for summarizing patient information but reports very few comparisons of these proposals. This work proposes to compare these algorithms through how they conserve essential aspects of clinical information and through the \"collect-synthesize-communicate\" framework. We found that current propositions usually address these 3 steps only partially. Moreover, they conserve and use temporality, uncertainty, and pertinent medical aspects to varying extents, and solutions are often preliminary.
摘要：
背景：信息溢出，当前临床环境中的一个常见问题，可以通过总结临床数据来缓解。虽然临床总结有几种解决方案，缺乏与该领域相关的完整研究概述。
目的：本研究旨在为临床总结确定最先进的解决方案，分析他们的能力，并确定它们的属性。
方法：对2005年至2022年发表的文章进行了范围审查。以临床为重点，对PubMed和WebofScience进行了查询，以找到一组初始报告，后来通过一系列引用发现的文章进行了扩展。对所包含的报告进行了分析，以回答以下问题：什么,以及如何总结医疗信息；总结是否保留时间性，不确定性,和医学针对性；以及如何评估和部署命题。为了回答信息是如何总结的，方法通过一个新的框架“收集-综合-通信”进行了比较，该框架涉及从数据中收集信息，它的合成，以及与最终用户的通信。
结果：总体而言，共包括128篇文章，代表了各种医学领域。46.1%(59/128)的论文使用纯结构化数据作为输入，41.4%(53/128)的文章中的文本，在10.2%(13/128)的论文中。使用拟议的框架，42.2%(54/128)的记录有助于信息收集，27.3%(35/128)对信息合成做出了贡献，46.1%(59/128)的人提出了总结沟通的解决方案。已经提出了许多总结方法，包括提取（n=13）和抽象摘要（n=19）;主题建模（n=5）;摘要规范（n=11）;概念和关系提取（n=30）;视觉设计注意事项（n=59）;和使用信息提取的完整管道（n=7），合成，和沟通。图形显示（n=53），短文本(n=41)，静态报告(n=7)，以问题为导向的观点(n=7)是总结沟通中最常见的类型。尽管大多数研究中的时间性和不确定性信息通常不保守(74/128,57.8%和113/128,88.3%,分别)，一些研究提出了处理这些信息的解决方案。总的来说,115篇(89.8%)文章显示了评估结果，方法包括对人类参与者的评估（中位数15，IQR24参与者）：对人类参与者的实验测量（n=31），真实情况(n=8)，和可用性研究(n=28)。没有人类参与的方法包括内在评估(n=24)，代理上的性能(n=10)，或域特定的任务（n=11）。总的来说,11（8.6％）报告描述了在临床环境中部署的系统。
结论：科学文献包含许多总结患者信息的建议，但很少报道这些建议的比较。这项工作提出了通过它们如何保存临床信息的基本方面以及通过“收集-合成-通信”框架来比较这些算法。我们发现当前的命题通常仅部分解决这3个步骤。此外，他们保存和使用时间性，不确定性,以及不同程度的相关医学方面，解决方案通常是初步的。
目的：本研究旨在为临床总结确定最先进的解决方案，分析他们的能力，并确定它们的属性。
方法：对2005年至2022年发表的文章进行了范围审查。以临床为重点，对PubMed和WebofScience进行了查询，以找到一组初始报告，后来通过一系列引用发现的文章进行了扩展。对所包含的报告进行了分析，以回答以下问题：什么,以及如何总结医疗信息；总结是否保留时间性，不确定性,和医学针对性；以及如何评估和部署命题。为了回答信息是如何总结的，方法通过一个新的框架“收集-综合-通信”进行了比较，该框架涉及从数据中收集信息，它的合成，以及与最终用户的通信。
结果：总体而言，共包括128篇文章，代表了各种医学领域。46.1%(59/128)的论文使用纯结构化数据作为输入，41.4%(53/128)的文章中的文本，在10.2%(13/128)的论文中。使用拟议的框架，42.2%(54/128)的记录有助于信息收集，27.3%(35/128)对信息合成做出了贡献，46.1%(59/128)的人提出了总结沟通的解决方案。已经提出了许多总结方法，包括提取（n=13）和抽象摘要（n=19）;主题建模（n=5）;摘要规范（n=11）;概念和关系提取（n=30）;视觉设计注意事项（n=59）;和使用信息提取的完整管道（n=7），合成，和沟通。图形显示（n=53），短文本(n=41)，静态报告(n=7)，以问题为导向的观点(n=7)是总结沟通中最常见的类型。尽管大多数研究中的时间性和不确定性信息通常不保守(74/128,57.8%和113/128,88.3%,分别)，一些研究提出了处理这些信息的解决方案。总的来说,115篇(89.8%)文章显示了评估结果，方法包括对人类参与者的评估（中位数15，IQR24参与者）：对人类参与者的实验测量（n=31），真实情况(n=8)，和可用性研究(n=28)。没有人类参与的方法包括内在评估(n=24)，代理上的性能(n=10)，或域特定的任务（n=11）。总的来说,11（8.6％）报告描述了在临床环境中部署的系统。
结论：科学文献包含许多总结患者信息的建议，但很少报道这些建议的比较。这项工作提出了通过它们如何保存临床信息的基本方面以及通过“收集-合成-通信”框架来比较这些算法。我们发现当前的命题通常仅部分解决这3个步骤。此外，他们保存和使用时间性，不确定性,以及不同程度的相关医学方面，解决方案通常是初步的。
