{"title":"家庭医学中尿液培养物分类算法的验证。","authors":"Jack Zhang, Rachael Morkem, Akshay Rajaram","doi":"10.1055/a-2499-4207","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong> Automation of test follow-up offers potential reductions in workload for clinicians. The primary objective of the study was to evaluate the performance of <i>MicrobEx</i>, a regular expression-based algorithm in classifying urine culture reports in primary care.</p><p><strong>Methods: </strong> A retrospective validation of <i>MicrobEx</i> was performed using urine culture reports abstracted from a single academic family health team. <i>MicrobEx</i> classifications were compared with labels assigned manually by a human reviewer. Measures of diagnostic performance were calculated.</p><p><strong>Results: </strong> <i>MicrobEx</i> achieved 95.3% accuracy, 88.6% sensitivity, and 100% specificity in classifying 1,999 urine culture reports.</p><p><strong>Conclusion: </strong> The accuracy of <i>MicrobEx</i> was comparable to its performance in the original development and validation study by Eickelberg. Additional work is required to explore and improve the accuracy of <i>MicrobEx</i> and assess its performance across primary care settings and with more complex urine culture reports.</p>","PeriodicalId":48956,"journal":{"name":"Applied Clinical Informatics","volume":"16 2","pages":"357-361"},"PeriodicalIF":2.1000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020491/pdf/","citationCount":"0","resultStr":"{\"title\":\"Validation of an Algorithm to Classify Urine Cultures in Family Medicine.\",\"authors\":\"Jack Zhang, Rachael Morkem, Akshay Rajaram\",\"doi\":\"10.1055/a-2499-4207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong> Automation of test follow-up offers potential reductions in workload for clinicians. The primary objective of the study was to evaluate the performance of <i>MicrobEx</i>, a regular expression-based algorithm in classifying urine culture reports in primary care.</p><p><strong>Methods: </strong> A retrospective validation of <i>MicrobEx</i> was performed using urine culture reports abstracted from a single academic family health team. <i>MicrobEx</i> classifications were compared with labels assigned manually by a human reviewer. Measures of diagnostic performance were calculated.</p><p><strong>Results: </strong> <i>MicrobEx</i> achieved 95.3% accuracy, 88.6% sensitivity, and 100% specificity in classifying 1,999 urine culture reports.</p><p><strong>Conclusion: </strong> The accuracy of <i>MicrobEx</i> was comparable to its performance in the original development and validation study by Eickelberg. Additional work is required to explore and improve the accuracy of <i>MicrobEx</i> and assess its performance across primary care settings and with more complex urine culture reports.</p>\",\"PeriodicalId\":48956,\"journal\":{\"name\":\"Applied Clinical Informatics\",\"volume\":\"16 2\",\"pages\":\"357-361\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020491/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Clinical Informatics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1055/a-2499-4207\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/4/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"MEDICAL INFORMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Clinical Informatics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1055/a-2499-4207","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/23 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
Validation of an Algorithm to Classify Urine Cultures in Family Medicine.
Objectives: Automation of test follow-up offers potential reductions in workload for clinicians. The primary objective of the study was to evaluate the performance of MicrobEx, a regular expression-based algorithm in classifying urine culture reports in primary care.
Methods: A retrospective validation of MicrobEx was performed using urine culture reports abstracted from a single academic family health team. MicrobEx classifications were compared with labels assigned manually by a human reviewer. Measures of diagnostic performance were calculated.
Results: MicrobEx achieved 95.3% accuracy, 88.6% sensitivity, and 100% specificity in classifying 1,999 urine culture reports.
Conclusion: The accuracy of MicrobEx was comparable to its performance in the original development and validation study by Eickelberg. Additional work is required to explore and improve the accuracy of MicrobEx and assess its performance across primary care settings and with more complex urine culture reports.
期刊介绍：
ACI is the third Schattauer journal dealing with biomedical and health informatics. It perfectly complements our other journals Öffnet internen Link im aktuellen FensterMethods of Information in Medicine and the Öffnet internen Link im aktuellen FensterYearbook of Medical Informatics. The Yearbook of Medical Informatics being the “Milestone” or state-of-the-art journal and Methods of Information in Medicine being the “Science and Research” journal of IMIA, ACI intends to be the “Practical” journal of IMIA.
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