Kayla V Dlugos, Mjaye Mazwi, Robert Lao, Osami Honjo
{"title":"在医疗决策中,噪音是一个未被充分认识到的问题,它被称为“范围审查”。","authors":"Kayla V Dlugos, Mjaye Mazwi, Robert Lao, Osami Honjo","doi":"10.1186/s12911-025-02905-z","DOIUrl":null,"url":null,"abstract":"<p><p>Unwanted random variability in day-to-day decision making referred to as 'noise' is associated with unhelpful variation that affects both the reproducibility and quality of decision making. Although this is described in other fields, the prevalence of noise in medical decision making and its effects on patient outcomes and the process and efficiency of care have not been reported and are unknown. This review sought to explore noise as a feature of medical decision making, as well as explore potential sources of noise in this setting. The search generated 2,082 results. Analysis of 14 studies included in the review (11 PubMed, 3 reference mining) suggests noise is a driver of unhelpful practice variation and may have important effects on care efficiency and reproducibility. 7 of the 14 studies demonstrated pattern noise, 3 demonstrated occasion noise, and 5 demonstrated stable pattern noise. The decision making in 8 studies demonstrated level noise, and lastly the decision making in 4 of the studies demonstrated system noise, a combination of both pattern and level noise. Additional study is required to ascertain how to measure and mitigate noise in medical decision making, as well as better understand the sources of noise present. Clinical trial number not applicable.</p>","PeriodicalId":9340,"journal":{"name":"BMC Medical Informatics and Decision Making","volume":"25 1","pages":"86"},"PeriodicalIF":3.3000,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11834221/pdf/","citationCount":"0","resultStr":"{\"title\":\"Noise is an underrecognized problem in medical decision making and is known by other names: a scoping review.\",\"authors\":\"Kayla V Dlugos, Mjaye Mazwi, Robert Lao, Osami Honjo\",\"doi\":\"10.1186/s12911-025-02905-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Unwanted random variability in day-to-day decision making referred to as 'noise' is associated with unhelpful variation that affects both the reproducibility and quality of decision making. Although this is described in other fields, the prevalence of noise in medical decision making and its effects on patient outcomes and the process and efficiency of care have not been reported and are unknown. This review sought to explore noise as a feature of medical decision making, as well as explore potential sources of noise in this setting. The search generated 2,082 results. Analysis of 14 studies included in the review (11 PubMed, 3 reference mining) suggests noise is a driver of unhelpful practice variation and may have important effects on care efficiency and reproducibility. 7 of the 14 studies demonstrated pattern noise, 3 demonstrated occasion noise, and 5 demonstrated stable pattern noise. The decision making in 8 studies demonstrated level noise, and lastly the decision making in 4 of the studies demonstrated system noise, a combination of both pattern and level noise. Additional study is required to ascertain how to measure and mitigate noise in medical decision making, as well as better understand the sources of noise present. Clinical trial number not applicable.</p>\",\"PeriodicalId\":9340,\"journal\":{\"name\":\"BMC Medical Informatics and Decision Making\",\"volume\":\"25 1\",\"pages\":\"86\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-02-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11834221/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Informatics and Decision Making\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12911-025-02905-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/s12911-025-02905-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
Noise is an underrecognized problem in medical decision making and is known by other names: a scoping review.
Unwanted random variability in day-to-day decision making referred to as 'noise' is associated with unhelpful variation that affects both the reproducibility and quality of decision making. Although this is described in other fields, the prevalence of noise in medical decision making and its effects on patient outcomes and the process and efficiency of care have not been reported and are unknown. This review sought to explore noise as a feature of medical decision making, as well as explore potential sources of noise in this setting. The search generated 2,082 results. Analysis of 14 studies included in the review (11 PubMed, 3 reference mining) suggests noise is a driver of unhelpful practice variation and may have important effects on care efficiency and reproducibility. 7 of the 14 studies demonstrated pattern noise, 3 demonstrated occasion noise, and 5 demonstrated stable pattern noise. The decision making in 8 studies demonstrated level noise, and lastly the decision making in 4 of the studies demonstrated system noise, a combination of both pattern and level noise. Additional study is required to ascertain how to measure and mitigate noise in medical decision making, as well as better understand the sources of noise present. Clinical trial number not applicable.
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.