Shwetha Hegde, Shanika Nanayakkara, Stephen Cox, Rajesh Vasa, Jinlong Gao
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The data were analyzed using descriptive statistics and bivariate analysis.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Participants identified undertreatment (72%) and legal implications (82%) as the most significant consequences of interpretive errors, whereas severe harm to patients was deemed the least likely. Dental practitioners placed a greater emphasis on maintaining a high level of competence and the well-being of their patients. Utilizing high-quality images (63.9%) and appropriate radiographs (59.7%) were identified as the most effective measures to minimize interpretive errors. Participants showed hesitancy regarding the reliance on machine learning as a clinical decision-making tool.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The survey provides valuable practical insights into the consequences and targeted measures to minimize the occurrence of interpretive errors. Efforts to minimize interpretive errors should address patient safety and practitioners' concerns about professional reputation and business viability. The study also suggests further research into the role of machine learning algorithms in reducing interpretive errors in dentistry.</p>\n </section>\n </div>","PeriodicalId":10203,"journal":{"name":"Clinical and Experimental Dental Research","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cre2.70027","citationCount":"0","resultStr":"{\"title\":\"Australian Dentists' Knowledge of the Consequences of Interpretive Errors in Dental Radiographs and Potential Mitigation Measures\",\"authors\":\"Shwetha Hegde, Shanika Nanayakkara, Stephen Cox, Rajesh Vasa, Jinlong Gao\",\"doi\":\"10.1002/cre2.70027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objectives</h3>\\n \\n <p>Dental radiographs, typically taken and interpreted by dentists, are essential for diagnosis and effective treatment planning. 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引用次数: 0
摘要
目的 牙科 X 光片通常由牙科医生拍摄和判读,对于诊断和有效的治疗计划至关重要。由于视觉和认知过程的失误而导致的牙科 X 光片判读错误会对患者和临床医生造成影响。本调查旨在评估牙科医生对这些错误后果的看法以及减少这些错误的潜在措施。 材料与方法 该在线匿名调查采用排序、李克特量表和开放式问题的方式,评估了澳大利亚牙科医生对这些错误的后果和潜在缓解措施的看法。采用描述性统计和双变量分析法对数据进行了分析。 结果 参与者认为治疗不足(72%)和法律影响(82%)是解释性错误最主要的后果,而对患者造成严重伤害的可能性最小。牙科医生更重视保持高水平的能力和患者的健康。使用高质量的图像(63.9%)和适当的射线照片(59.7%)被认为是减少判读错误的最有效措施。参与者对依赖机器学习作为临床决策工具表示犹豫。 结论 该调查提供了宝贵的实用见解,帮助人们了解最大限度减少判读错误发生的后果和有针对性的措施。尽量减少解释性错误的努力应解决患者安全问题以及从业人员对专业声誉和商业可行性的担忧。这项研究还建议进一步研究机器学习算法在减少牙科口译错误中的作用。
Australian Dentists' Knowledge of the Consequences of Interpretive Errors in Dental Radiographs and Potential Mitigation Measures
Objectives
Dental radiographs, typically taken and interpreted by dentists, are essential for diagnosis and effective treatment planning. Interpretive errors in dental radiographs, stemming from failures of visual and cognitive processes, can affect both patients and clinicians. This survey aimed to assess the dental practitioners' perceptions of the consequences of these errors and potential measures to minimize them.
Materials and Methods
This online anonymized survey assessed Australian dental practitioners' perceptions of the consequences of these errors and potential mitigation measures using ranking, Likert scale, and open-ended questions. The data were analyzed using descriptive statistics and bivariate analysis.
Results
Participants identified undertreatment (72%) and legal implications (82%) as the most significant consequences of interpretive errors, whereas severe harm to patients was deemed the least likely. Dental practitioners placed a greater emphasis on maintaining a high level of competence and the well-being of their patients. Utilizing high-quality images (63.9%) and appropriate radiographs (59.7%) were identified as the most effective measures to minimize interpretive errors. Participants showed hesitancy regarding the reliance on machine learning as a clinical decision-making tool.
Conclusions
The survey provides valuable practical insights into the consequences and targeted measures to minimize the occurrence of interpretive errors. Efforts to minimize interpretive errors should address patient safety and practitioners' concerns about professional reputation and business viability. The study also suggests further research into the role of machine learning algorithms in reducing interpretive errors in dentistry.
期刊介绍:
Clinical and Experimental Dental Research aims to provide open access peer-reviewed publications of high scientific quality representing original clinical, diagnostic or experimental work within all disciplines and fields of oral medicine and dentistry. The scope of Clinical and Experimental Dental Research comprises original research material on the anatomy, physiology and pathology of oro-facial, oro-pharyngeal and maxillofacial tissues, and functions and dysfunctions within the stomatognathic system, and the epidemiology, aetiology, prevention, diagnosis, prognosis and therapy of diseases and conditions that have an effect on the homeostasis of the mouth, jaws, and closely associated structures, as well as the healing and regeneration and the clinical aspects of replacement of hard and soft tissues with biomaterials, and the rehabilitation of stomatognathic functions. Studies that bring new knowledge on how to advance health on the individual or public health levels, including interactions between oral and general health and ill-health are welcome.