Accuracy and Variation in Transcription of Antemortem Dental Data

Abstract

Comparison of dental features has been used successfully for human identification throughout history. The data from an individual's dental records and identifying dental findings are compared to an unknown postmortem dataset to determine if both datasets belong to the same individual. Currently, a major focus of the forensic science community is on the standardisation and validation of processes. Despite extensive research on the postmortem and reconciliation phases of dental identification, no studies have evaluated antemortem dental data collection, presentation, analysis, and collation. Antemortem information is of paramount importance for definitive identification since without it, comparisons cannot be made. Poor quality data and inaccuracies or errors in transcription could delay identification, or more seriously, lead to a false exclusion or identification. This thesis aims to assess the current antemortem phase process and devise standardised procedures to improve archiving and transmission of antemortem records and increase accuracy and repeatability of dental data transcription. Information contained within dental records, their complexity, and the potential impact this content and its presentation had on antemortem transcription was investigated. Following this, a study requiring transcription of dental data was conducted to identify variation in coding and evaluate the types and causes of errors. Using this information, a standard operating procedure and a computer-aided method to implement it were developed to enhance antemortem transcription quality. This research highlights the large variation in both antemortem data complexity and interpretation and the impact that this can have on transcription. The computer-aided method developed from the knowledge gained showed that analysis and transcription can be further standardised to improve accuracy. Additionally, standardisation will improve calibration between examiners and will enable proficiency testing, which will enhance the scientific basis of dental identification.