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迈向医疗保健流程挖掘中临床案例研究中标准化术语的使用。

Towards the Use of Standardized Terms in Clinical Case Studies for Process Mining in Healthcare.

机构信息

Research Department Advanced Information Systems and Technology, University of Applied Sciences Upper Austria, 4232 Hagenberg, Austria.

Institute for Applied Knowledge Processing, Johannes Kepler University, 4040 Linz, Austria.

出版信息

Int J Environ Res Public Health. 2020 Feb 19;17(4):1348. doi: 10.3390/ijerph17041348.

DOI:10.3390/ijerph17041348
PMID:32093073
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7068384/
Abstract

Process mining can provide greater insight into medical treatment processes and organizational processes in healthcare. To enhance comparability between processes, the quality of the labelled-data is essential. A literature review of the clinical case studies by Rojas et al. in 2016 identified several common aspects for comparison, which include methodologies, algorithms or techniques, medical fields, and healthcare specialty. However, clinical aspects are not reported in a uniform way and do not follow a standard clinical coding scheme. Further, technical aspects such as details of the event log data are not always described. In this paper, we identified 38 clinically-relevant case studies of process mining in healthcare published from 2016 to 2018 that described the tools, algorithms and techniques utilized, and details on the event log data. We then correlated the clinical aspects of patient encounter environment, clinical specialty and medical diagnoses using the standard clinical coding schemes SNOMED CT and ICD-10. The potential outcomes of adopting a standard approach for describing event log data and classifying medical terminology using standard clinical coding schemes are further discussed. A checklist template for the reporting of case studies is provided in the Appendix A to the article.

摘要

流程挖掘可以提供对医疗处理过程和医疗保健组织过程的更深入了解。为了提高流程之间的可比性,标记数据的质量至关重要。Rojas 等人在 2016 年对临床案例研究进行的文献回顾确定了几个可用于比较的常见方面,包括方法学、算法或技术、医学领域和医疗保健专业。然而,临床方面的报告方式并不统一,也没有遵循标准的临床编码方案。此外,技术方面的细节,如事件日志数据的详细信息,并不总是描述。在本文中,我们确定了 2016 年至 2018 年期间发表的 38 篇在医疗保健中应用流程挖掘的具有临床相关性的案例研究,这些研究描述了所使用的工具、算法和技术,以及有关事件日志数据的详细信息。然后,我们使用标准临床编码方案 SNOMED CT 和 ICD-10 来关联患者就诊环境、临床专业和医疗诊断的临床方面。进一步讨论了采用标准方法描述事件日志数据和使用标准临床编码方案对医疗术语进行分类的潜在结果。文章的附录 A 提供了案例研究报告的检查表模板。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/7068384/9a3aa1e580ab/ijerph-17-01348-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/7068384/9a3aa1e580ab/ijerph-17-01348-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/233d/7068384/9a3aa1e580ab/ijerph-17-01348-g001.jpg

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