通过模糊Miner过程挖掘监测二级医疗保健服务的患者路径。

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS
Güzin Özdağoğlu, Muhammet Damar, Fatih Safa Erenay, Hale Turhan Damar, Osman Himmetoğlu, Andrew David Pinto
{"title":"通过模糊Miner过程挖掘监测二级医疗保健服务的患者路径。","authors":"Güzin Özdağoğlu, Muhammet Damar, Fatih Safa Erenay, Hale Turhan Damar, Osman Himmetoğlu, Andrew David Pinto","doi":"10.1186/s12911-025-03016-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study explored workflow pathways followed by patients seeking secondary healthcare services at a local hospital in a rural part of Turkey using process mining to improve hospital resource management.</p><p><strong>Methods: </strong>The study used process mining to discover process flows as patient pathways implied by hospital records for in-patient, out-patient, biochemical laboratory, and radiology services. Utilizing its flexibility, visualizations and robustness, authors implemented fuzzy-miner algorithm. First, we processed the relevant data from patient records. Then, this data was transformed into event and activity logs. Subsequently, all data components were collected into a data warehouse, and the process mining algorithm was applied. The process mining specified resource usage levels and workload, service waiting times, associated bottlenecks in hospital services, and related statistics/measures.</p><p><strong>Results: </strong>The results from the proposed process mining analysis offer insights and decision support to improve hospital resource management. For example, the resulting statistics indicate the high waiting times (e.g., median of waiting times around 2 h within the selected time period) in the General Surgery and Cardiology services, whose resources were highly utilized (2,699 and 6,162 times). Overloads at laboratories and radiological imaging seem to be contributing to these long waiting times, and capacities for the associated services may need to be improved. Waiting times and resource workloads are higher on specific dates related to local commercial and social activities.</p><p><strong>Conclusions: </strong>Process mining successfully identified the real work flows, bottlenecks, and long waiting times at services within the considered local hospital and provided insights to the hospital management for improving their practices. Moreover, the analyses revealed unique challenges in providing care at a local hospital located far from the city center, emphasizing the potential of process mining to improve healthcare delivery tailored to the specific hospital environment.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9340,"journal":{"name":"BMC Medical Informatics and Decision Making","volume":"25 1","pages":"199"},"PeriodicalIF":3.3000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12117757/pdf/","citationCount":"0","resultStr":"{\"title\":\"Monitoring patient pathways at a secondary healthcare services through process mining via Fuzzy Miner.\",\"authors\":\"Güzin Özdağoğlu, Muhammet Damar, Fatih Safa Erenay, Hale Turhan Damar, Osman Himmetoğlu, Andrew David Pinto\",\"doi\":\"10.1186/s12911-025-03016-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>This study explored workflow pathways followed by patients seeking secondary healthcare services at a local hospital in a rural part of Turkey using process mining to improve hospital resource management.</p><p><strong>Methods: </strong>The study used process mining to discover process flows as patient pathways implied by hospital records for in-patient, out-patient, biochemical laboratory, and radiology services. Utilizing its flexibility, visualizations and robustness, authors implemented fuzzy-miner algorithm. First, we processed the relevant data from patient records. Then, this data was transformed into event and activity logs. Subsequently, all data components were collected into a data warehouse, and the process mining algorithm was applied. The process mining specified resource usage levels and workload, service waiting times, associated bottlenecks in hospital services, and related statistics/measures.</p><p><strong>Results: </strong>The results from the proposed process mining analysis offer insights and decision support to improve hospital resource management. For example, the resulting statistics indicate the high waiting times (e.g., median of waiting times around 2 h within the selected time period) in the General Surgery and Cardiology services, whose resources were highly utilized (2,699 and 6,162 times). Overloads at laboratories and radiological imaging seem to be contributing to these long waiting times, and capacities for the associated services may need to be improved. Waiting times and resource workloads are higher on specific dates related to local commercial and social activities.</p><p><strong>Conclusions: </strong>Process mining successfully identified the real work flows, bottlenecks, and long waiting times at services within the considered local hospital and provided insights to the hospital management for improving their practices. Moreover, the analyses revealed unique challenges in providing care at a local hospital located far from the city center, emphasizing the potential of process mining to improve healthcare delivery tailored to the specific hospital environment.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>\",\"PeriodicalId\":9340,\"journal\":{\"name\":\"BMC Medical Informatics and Decision Making\",\"volume\":\"25 1\",\"pages\":\"199\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12117757/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Informatics and Decision Making\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12911-025-03016-5\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL INFORMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Informatics and Decision Making","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12911-025-03016-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
引用次数: 0

摘要

背景:本研究探讨了在土耳其农村地区的一家当地医院寻求二级医疗保健服务的患者使用流程挖掘来改善医院资源管理的工作流程路径。方法:本研究使用流程挖掘的方法来发现住院、门诊、生化实验室和放射服务的医院记录所隐含的患者路径流程流。利用模糊挖掘算法的灵活性、可视化性和鲁棒性,实现了模糊挖掘算法。首先,我们处理了患者记录中的相关数据。然后,将这些数据转换为事件和活动日志。随后,将所有数据组件收集到数据仓库中,并应用过程挖掘算法。流程挖掘指定了资源使用水平和工作负载、服务等待时间、医院服务中的相关瓶颈以及相关的统计数据/度量。结果:流程挖掘分析的结果为改进医院资源管理提供了见解和决策支持。例如,结果统计表明,普通外科和心脏病科的等待时间高(例如,在选定时间段内等待时间的中位数约为2小时),其资源利用率很高(2,699次和6,162次)。实验室和放射成像超载似乎是造成这些长时间等待的原因,相关服务的能力可能需要改进。在与当地商业和社会活动相关的特定日期,等待时间和资源工作量更高。结论:流程挖掘成功地确定了所考虑的当地医院服务的实际工作流程、瓶颈和长时间等待时间,并为医院管理提供了改进实践的见解。此外,分析揭示了在远离市中心的当地医院提供护理的独特挑战,强调了流程挖掘的潜力,以改善针对特定医院环境的医疗保健服务。临床试验号:不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring patient pathways at a secondary healthcare services through process mining via Fuzzy Miner.

Background: This study explored workflow pathways followed by patients seeking secondary healthcare services at a local hospital in a rural part of Turkey using process mining to improve hospital resource management.

Methods: The study used process mining to discover process flows as patient pathways implied by hospital records for in-patient, out-patient, biochemical laboratory, and radiology services. Utilizing its flexibility, visualizations and robustness, authors implemented fuzzy-miner algorithm. First, we processed the relevant data from patient records. Then, this data was transformed into event and activity logs. Subsequently, all data components were collected into a data warehouse, and the process mining algorithm was applied. The process mining specified resource usage levels and workload, service waiting times, associated bottlenecks in hospital services, and related statistics/measures.

Results: The results from the proposed process mining analysis offer insights and decision support to improve hospital resource management. For example, the resulting statistics indicate the high waiting times (e.g., median of waiting times around 2 h within the selected time period) in the General Surgery and Cardiology services, whose resources were highly utilized (2,699 and 6,162 times). Overloads at laboratories and radiological imaging seem to be contributing to these long waiting times, and capacities for the associated services may need to be improved. Waiting times and resource workloads are higher on specific dates related to local commercial and social activities.

Conclusions: Process mining successfully identified the real work flows, bottlenecks, and long waiting times at services within the considered local hospital and provided insights to the hospital management for improving their practices. Moreover, the analyses revealed unique challenges in providing care at a local hospital located far from the city center, emphasizing the potential of process mining to improve healthcare delivery tailored to the specific hospital environment.

Clinical trial number: Not applicable.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信