Wen Hu, Li Ma, Shan Xiong, Sifeng Li, Xiaocheng Wang, Min Liu, Zhenni Chen
{"title":"用鱼骨图和帕累托图分析某三级医院非计划再入院的质量。","authors":"Wen Hu, Li Ma, Shan Xiong, Sifeng Li, Xiaocheng Wang, Min Liu, Zhenni Chen","doi":"10.2147/IJGM.S540011","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Existing research on unplanned readmissions has primarily focused on department- or disease-specific analyses, yet it lacks a systematic hospital management perspective. This study employs quality improvement tools to analyze causes of unplanned readmissions, identify key drivers, and lay the groundwork for interventions that reduce readmission rates, alleviate patient burdens, and optimize healthcare resource utilization.</p><p><strong>Patients and methods: </strong>This retrospective study included 341 patients who were readmitted within 31 days due to the same or related diseases. These patients were identified at a public tertiary Grade A general hospital in Chengdu between January 1, 2023, and December 31, 2024. Fishbone diagram was used to analyze the root causes of unplanned readmissions, while Pareto chart was employed to determine the distribution of the primary causes. Data were sourced from the hospital's information management system.</p><p><strong>Results: </strong>The overall unplanned readmission rate was 0.38%. In surgical patients, unplanned readmissions were predominantly attributed to surgical complications (75.79%), which primarily included surgical site infections, respiratory infections, postoperative hemorrhage or hematoma, thromboembolic events, and impaired wound healing. Preventing the above-mentioned surgical complications is a key measure to reduce readmissions among surgical patients. For non-surgical patients, disease exacerbation constituted the primary cause of unplanned readmissions (72.19%), with pancreatitis, chronic obstructive pulmonary disease, cardiac arrhythmia, and fungal pneumonia identified as high-risk diseases leading to readmissions. Strengthening the management of these high-risk diseases is crucial for preventing readmissions among non-surgical patients.</p><p><strong>Conclusion: </strong>Employing integrated fishbone diagram and Pareto chart analyses, this study systematically deciphered the root causes and dominant contributors to unplanned readmissions. These findings enabled the formulation of targeted evidence-based management strategies. This study provides novel insights and methodologies for hospital management practices, serving as a valuable reference for other healthcare institutions seeking to reduce unplanned readmission rates and enhance operational efficiency.</p>","PeriodicalId":14131,"journal":{"name":"International Journal of General Medicine","volume":"18 ","pages":"5295-5302"},"PeriodicalIF":2.0000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12433644/pdf/","citationCount":"0","resultStr":"{\"title\":\"Quality Analysis of Unplanned Readmissions Using Fishbone Diagram and Pareto Chart in a Chinese Tertiary Hospital.\",\"authors\":\"Wen Hu, Li Ma, Shan Xiong, Sifeng Li, Xiaocheng Wang, Min Liu, Zhenni Chen\",\"doi\":\"10.2147/IJGM.S540011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Existing research on unplanned readmissions has primarily focused on department- or disease-specific analyses, yet it lacks a systematic hospital management perspective. This study employs quality improvement tools to analyze causes of unplanned readmissions, identify key drivers, and lay the groundwork for interventions that reduce readmission rates, alleviate patient burdens, and optimize healthcare resource utilization.</p><p><strong>Patients and methods: </strong>This retrospective study included 341 patients who were readmitted within 31 days due to the same or related diseases. These patients were identified at a public tertiary Grade A general hospital in Chengdu between January 1, 2023, and December 31, 2024. Fishbone diagram was used to analyze the root causes of unplanned readmissions, while Pareto chart was employed to determine the distribution of the primary causes. Data were sourced from the hospital's information management system.</p><p><strong>Results: </strong>The overall unplanned readmission rate was 0.38%. In surgical patients, unplanned readmissions were predominantly attributed to surgical complications (75.79%), which primarily included surgical site infections, respiratory infections, postoperative hemorrhage or hematoma, thromboembolic events, and impaired wound healing. Preventing the above-mentioned surgical complications is a key measure to reduce readmissions among surgical patients. For non-surgical patients, disease exacerbation constituted the primary cause of unplanned readmissions (72.19%), with pancreatitis, chronic obstructive pulmonary disease, cardiac arrhythmia, and fungal pneumonia identified as high-risk diseases leading to readmissions. Strengthening the management of these high-risk diseases is crucial for preventing readmissions among non-surgical patients.</p><p><strong>Conclusion: </strong>Employing integrated fishbone diagram and Pareto chart analyses, this study systematically deciphered the root causes and dominant contributors to unplanned readmissions. These findings enabled the formulation of targeted evidence-based management strategies. This study provides novel insights and methodologies for hospital management practices, serving as a valuable reference for other healthcare institutions seeking to reduce unplanned readmission rates and enhance operational efficiency.</p>\",\"PeriodicalId\":14131,\"journal\":{\"name\":\"International Journal of General Medicine\",\"volume\":\"18 \",\"pages\":\"5295-5302\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12433644/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of General Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/IJGM.S540011\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of General Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/IJGM.S540011","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Quality Analysis of Unplanned Readmissions Using Fishbone Diagram and Pareto Chart in a Chinese Tertiary Hospital.
Purpose: Existing research on unplanned readmissions has primarily focused on department- or disease-specific analyses, yet it lacks a systematic hospital management perspective. This study employs quality improvement tools to analyze causes of unplanned readmissions, identify key drivers, and lay the groundwork for interventions that reduce readmission rates, alleviate patient burdens, and optimize healthcare resource utilization.
Patients and methods: This retrospective study included 341 patients who were readmitted within 31 days due to the same or related diseases. These patients were identified at a public tertiary Grade A general hospital in Chengdu between January 1, 2023, and December 31, 2024. Fishbone diagram was used to analyze the root causes of unplanned readmissions, while Pareto chart was employed to determine the distribution of the primary causes. Data were sourced from the hospital's information management system.
Results: The overall unplanned readmission rate was 0.38%. In surgical patients, unplanned readmissions were predominantly attributed to surgical complications (75.79%), which primarily included surgical site infections, respiratory infections, postoperative hemorrhage or hematoma, thromboembolic events, and impaired wound healing. Preventing the above-mentioned surgical complications is a key measure to reduce readmissions among surgical patients. For non-surgical patients, disease exacerbation constituted the primary cause of unplanned readmissions (72.19%), with pancreatitis, chronic obstructive pulmonary disease, cardiac arrhythmia, and fungal pneumonia identified as high-risk diseases leading to readmissions. Strengthening the management of these high-risk diseases is crucial for preventing readmissions among non-surgical patients.
Conclusion: Employing integrated fishbone diagram and Pareto chart analyses, this study systematically deciphered the root causes and dominant contributors to unplanned readmissions. These findings enabled the formulation of targeted evidence-based management strategies. This study provides novel insights and methodologies for hospital management practices, serving as a valuable reference for other healthcare institutions seeking to reduce unplanned readmission rates and enhance operational efficiency.
期刊介绍:
The International Journal of General Medicine is an international, peer-reviewed, open access journal that focuses on general and internal medicine, pathogenesis, epidemiology, diagnosis, monitoring and treatment protocols. The journal is characterized by the rapid reporting of reviews, original research and clinical studies across all disease areas.
A key focus of the journal is the elucidation of disease processes and management protocols resulting in improved outcomes for the patient. Patient perspectives such as satisfaction, quality of life, health literacy and communication and their role in developing new healthcare programs and optimizing clinical outcomes are major areas of interest for the journal.
As of 1st April 2019, the International Journal of General Medicine will no longer consider meta-analyses for publication.