Exposing exposure: enhancing patient safety through automated data mining of nuclear medicine reports for quality assurance and organ dose monitoring.

PURPOSE: To develop and validate an open-source informatics toolkit capable of creating a radiation exposure data repository from existing nuclear medicine report archives and to demonstrate potential applications of such data for quality assurance and longitudinal patient-specific radiation dose monitoring.
MATERIALS AND METHODS: This study was institutional review board approved and HIPAA compliant. Informed consent was waived. An open-source toolkit designed to automate the extraction of data on radiopharmaceuticals and administered activities from nuclear medicine reports was developed. After iterative code training, manual validation was performed on 2359 nuclear medicine reports randomly selected from September 17, 1985, to February 28, 2011. Recall (sensitivity) and precision (positive predictive value) were calculated with 95% binomial confidence intervals. From the resultant institutional data repository, examples of usage in quality assurance efforts and patient-specific longitudinal radiation dose monitoring obtained by calculating organ doses from the administered activity and radiopharmaceutical of each examination were provided.
RESULTS: Validation statistics yielded a combined recall of 97.6% ± 0.7 (95% confidence interval) and precision of 98.7% ± 0.5. Histograms of administered activity for fluorine 18 fluorodeoxyglucose and iodine 131 sodium iodide were generated. An organ dose heatmap which displays a sample patient's dose accumulation from multiple nuclear medicine examinations was created.
CONCLUSION: Large-scale repositories of radiation exposure data can be extracted from institutional nuclear medicine report archives with high recall and precision. Such repositories enable new approaches in radiation exposure patient safety initiatives and patient-specific radiation dose monitoring.