Errors of interpretation of dental radiographs among dental professionals: A survey
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Open Access
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PresentationAuthor/s
Shwethah, HegdeAbstract
Radiographic interpretations constitute an essential component of information available to dentists when they are formulating a diagnosis. However, interpretation of images is a human endeavour and is subject to the limitations of our ability. Making a correct diagnosis relies on ...
See moreRadiographic interpretations constitute an essential component of information available to dentists when they are formulating a diagnosis. However, interpretation of images is a human endeavour and is subject to the limitations of our ability. Making a correct diagnosis relies on visual detection, pattern recognition, working memory functions and also cognitive reasoning to perceive the meaning of the interpretation. Mistakes may occur in both the visual perception and the cognitive interpretation of images, and this may have serious consequences for the patient. In medical radiology literature, this issue has been recognised for many years, and numerous publications have reported interpretive errors on chest radiographs and mammograms. The rate of interpretation error is in the range of 2-20% and varies depending on the type of radiological investigation. In dentistry, the rate of error of interpretation of dental radiographs is not as well documented. Clinical settings are often hectic with information ambiguous or incomplete, and the dentist is often under pressure to make diagnostic assessments quickly. As radiographic interpretation is reliant on visual perception, errors in interpretation can occur under such constrained conditions. The subjective nature of the interpretation also makes it difficult to establish what is an ‘error’ as opposed to an acceptable variation in opinion. This study explores the occurrence and causes of errors of interpretation of dental radiographs among dental practitioners using an online anonymised questionnaire. With this survey, we aim to evaluate the perceptions of errors, definitions of errors, their contributing factors and strategies to reduce errors. This research will create a benchmark on the incidence and prevalence of errors of interpretation in dentistry and the will be used to improve the diagnostic accuracy of machine learning algorithms.
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See moreRadiographic interpretations constitute an essential component of information available to dentists when they are formulating a diagnosis. However, interpretation of images is a human endeavour and is subject to the limitations of our ability. Making a correct diagnosis relies on visual detection, pattern recognition, working memory functions and also cognitive reasoning to perceive the meaning of the interpretation. Mistakes may occur in both the visual perception and the cognitive interpretation of images, and this may have serious consequences for the patient. In medical radiology literature, this issue has been recognised for many years, and numerous publications have reported interpretive errors on chest radiographs and mammograms. The rate of interpretation error is in the range of 2-20% and varies depending on the type of radiological investigation. In dentistry, the rate of error of interpretation of dental radiographs is not as well documented. Clinical settings are often hectic with information ambiguous or incomplete, and the dentist is often under pressure to make diagnostic assessments quickly. As radiographic interpretation is reliant on visual perception, errors in interpretation can occur under such constrained conditions. The subjective nature of the interpretation also makes it difficult to establish what is an ‘error’ as opposed to an acceptable variation in opinion. This study explores the occurrence and causes of errors of interpretation of dental radiographs among dental practitioners using an online anonymised questionnaire. With this survey, we aim to evaluate the perceptions of errors, definitions of errors, their contributing factors and strategies to reduce errors. This research will create a benchmark on the incidence and prevalence of errors of interpretation in dentistry and the will be used to improve the diagnostic accuracy of machine learning algorithms.
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Date
2020-12-14Source title
SDS Research Seminar SeriesLicence
Copyright All Rights ReservedFaculty/School
Faculty of Medicine and Health, Sydney Dental SchoolShare