{"title":"医疗保健中的过程挖掘:一项高等研究。","authors":"Adauto Santos, Gislaine Camila Lapasini Leal, Renato Balancieri","doi":"10.1186/s12911-025-02967-z","DOIUrl":null,"url":null,"abstract":"<p><p>Business processes in healthcare are complex and multidisciplinary, involving various professional profiles and different healthcare structures, and each medical treatment may require distinct clinical pathways. Process mining can assist in discovering trajectories, verifying compliance, and enabling an understanding of the involvement of different organizational aspects. The main goal of this study is to provide a comprehensive overview of the application of process mining in healthcare. For this, a tertiary review was conducted, gathering 18 secondary reviews that addressed different aspects, such as the objectives of process mining in healthcare, types of activities and perspectives, available resources, primary medical specialties, types of medical processes, and limitations and challenges. The study reveals that process discovery is the most common activity, while the control flow was the most used perspective. The Heuristics Miner and Fuzzy Miner algorithms were the most relevant, and oncology was the medical specialty in which process mining was most used. Process mining has proven to be an effective tool for analyzing healthcare workflows, improving understanding of clinical guidelines and protocols, and supporting decision-making. However, it is necessary to deal with noisy or missing data and establish visualization mechanisms that ensure clarity in data presentation.</p>","PeriodicalId":9340,"journal":{"name":"BMC Medical Informatics and Decision Making","volume":"25 1","pages":"306"},"PeriodicalIF":3.8000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12355893/pdf/","citationCount":"0","resultStr":"{\"title\":\"Process mining in healthcare: a tertiary study.\",\"authors\":\"Adauto Santos, Gislaine Camila Lapasini Leal, Renato Balancieri\",\"doi\":\"10.1186/s12911-025-02967-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Business processes in healthcare are complex and multidisciplinary, involving various professional profiles and different healthcare structures, and each medical treatment may require distinct clinical pathways. Process mining can assist in discovering trajectories, verifying compliance, and enabling an understanding of the involvement of different organizational aspects. The main goal of this study is to provide a comprehensive overview of the application of process mining in healthcare. For this, a tertiary review was conducted, gathering 18 secondary reviews that addressed different aspects, such as the objectives of process mining in healthcare, types of activities and perspectives, available resources, primary medical specialties, types of medical processes, and limitations and challenges. The study reveals that process discovery is the most common activity, while the control flow was the most used perspective. The Heuristics Miner and Fuzzy Miner algorithms were the most relevant, and oncology was the medical specialty in which process mining was most used. Process mining has proven to be an effective tool for analyzing healthcare workflows, improving understanding of clinical guidelines and protocols, and supporting decision-making. However, it is necessary to deal with noisy or missing data and establish visualization mechanisms that ensure clarity in data presentation.</p>\",\"PeriodicalId\":9340,\"journal\":{\"name\":\"BMC Medical Informatics and Decision Making\",\"volume\":\"25 1\",\"pages\":\"306\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12355893/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Informatics and Decision Making\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12911-025-02967-z\",\"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/s12911-025-02967-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
Business processes in healthcare are complex and multidisciplinary, involving various professional profiles and different healthcare structures, and each medical treatment may require distinct clinical pathways. Process mining can assist in discovering trajectories, verifying compliance, and enabling an understanding of the involvement of different organizational aspects. The main goal of this study is to provide a comprehensive overview of the application of process mining in healthcare. For this, a tertiary review was conducted, gathering 18 secondary reviews that addressed different aspects, such as the objectives of process mining in healthcare, types of activities and perspectives, available resources, primary medical specialties, types of medical processes, and limitations and challenges. The study reveals that process discovery is the most common activity, while the control flow was the most used perspective. The Heuristics Miner and Fuzzy Miner algorithms were the most relevant, and oncology was the medical specialty in which process mining was most used. Process mining has proven to be an effective tool for analyzing healthcare workflows, improving understanding of clinical guidelines and protocols, and supporting decision-making. However, it is necessary to deal with noisy or missing data and establish visualization mechanisms that ensure clarity in data presentation.
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.