Dentomaxillofacial Radiology, Sydney Dental School, University of Sydney, Sydney, Australia.
Sydney Dental School, Institute of Dental Research, Westmead Centre for Oral Health, University of Sydney, Sydney, Australia.
Clin Exp Dent Res. 2024 Dec;10(6):e70027. doi: 10.1002/cre2.70027.
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.
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.
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.
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.
牙医拍摄的牙科 X 光片对于诊断和有效治疗计划至关重要。由于视觉和认知过程的失败，牙科 X 光片中的解读错误会影响患者和临床医生。本调查旨在评估牙科医生对这些错误后果的看法，以及潜在的减少这些错误的措施。
本在线匿名调查使用排名、李克特量表和开放式问题评估澳大利亚牙科医生对这些错误后果的看法和潜在的缓解措施。使用描述性统计和双变量分析对数据进行分析。
参与者认为治疗不足（72%）和法律影响（82%）是解读错误的最严重后果，而对患者造成严重伤害则被认为最不可能。牙科医生更注重保持高水平的能力和患者的福祉。使用高质量的图像（63.9%）和适当的 X 光片（59.7%）被认为是最大限度减少解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持犹豫态度。
该调查为减少解读错误的后果和针对性措施提供了有价值的实践见解。努力减少解读错误应关注患者安全以及医生对专业声誉和业务可行性的担忧。该研究还表明，需要进一步研究机器学习算法在减少牙科解读错误中的作用。
