Uncertainty quantification of bioassay functions for the internal dosimetry of radioiodine.

Bioassay functions, which are provided by the International Commission on Radiological Protection, are used to estimate the intake activity of radionuclides; however, they include considerable uncertainties in terms of the internal dosimetry for a particular individual. During a practical internal dose assessment, the uncertainty in the bioassay function is generally not introduced because of the difficulty in quantification. Therefore, to clarify the existence of uncertainty in the bioassay function and provide dosimetrists with an insight into this uncertainty, this study attempted to quantify the uncertainty in the thyroid retention function used for radioiodine exposure. The uncertainty was quantified using a probabilistic estimation of the thyroid retention function through the propagation of the distribution of biokinetic parameters by the Monte Carlo simulation technique. The uncertainties in the thyroid retention function, expressed in terms of the scattering factor, were in the ranges of 1.55-1.60 and 1.40-1.50 for within 24 h and after 24 h, respectively. In addition, the thyroid retention function within 24 h was compared with actual measurement data to confirm the uncertainty due to the use of first-order kinetics in the biokinetic model calculation. Significantly higher thyroid uptakes (by a factor of 1.9) were observed in the actual measurements. This study indicates that consideration of the uncertainty in the thyroid retention function can avoid a significant over- and under-estimation of the internal dose, particularly when a high dose is predicted.

Internal Dose Assessment after 131I-Iodide Misadministration in a Patient With Incompletely Blocked Thyroid Uptake: Personalized Internal Dose Assessment by Estimating Individual-Specific Biokinetics.

In July 2017, a medical accident occurred in South Korea, in which I-iodide solution was misadministered to the wrong patient. Although the International Commission on Radiological Protection provided internal dose coefficients for iodine for blocked thyroid, they were not reliable enough for determining the dose to the patient (whose thyroid uptake was incompletely blocked) due to a discrepancy in biokinetics. Therefore, a personalized dose assessment was performed to derive the individual-specific dose coefficients for the patient. Initially, the thyroid biokinetics of the patient were statistically clarified by fitting bioassay monitoring results and the corresponding predicted bioassay values, which were calculated repeatedly for varying iodine transfer rates in an iodine biokinetic model. After determining the transfer rate for the patient, the individual-specific dose coefficients were then calculated in accordance with latest recommendations of the International Commission on Radiological Protection. According to the individual-specific biokinetics, the 24 h thyroid uptake fraction of iodine was estimated as 0.52%. The thyroid absorbed dose of the patient was evaluated as 21.2 Gy, which differed greatly (by about 9 Gy) from the dose evaluated simply using the reference data for blocked thyroid uptake. The personalized dose assessment carried out for the patient not only reduced considerable uncertainties in the internal dose calculation, but also improved the reliability of the calculated internal dose by adopting the latest dosimetric data, including specific absorbed fraction values based on voxel phantoms. Through the dose assessment of the patient, the methodology of personalized dose assessment considering individual-specific biokinetics was developed.

Assessment of hospital processes using a process mining technique: Outpatient process analysis at a tertiary hospital.

INTRODUCTION: Many hospitals are increasing their efforts to improve processes because processes play an important role in enhancing work efficiency and reducing costs. However, to date, a quantitative tool has not been available to examine the before and after effects of processes and environmental changes, other than the use of indirect indicators, such as mortality rate and readmission rate. METHODS: This study used process mining technology to analyze process changes based on changes in the hospital environment, such as the construction of a new building, and to measure the effects of environmental changes in terms of consultation wait time, time spent per task, and outpatient care processes. Using process mining technology, electronic health record (EHR) log data of outpatient care before and after constructing a new building were analyzed, and the effectiveness of the technology in terms of the process was evaluated. RESULTS: Using the process mining technique, we found that the total time spent in outpatient care did not increase significantly compared to that before the construction of a new building, considering that the number of outpatients increased, and the consultation wait time decreased. These results suggest that the operation of the outpatient clinic was effective after changes were implemented in the hospital environment. We further identified improvements in processes using the process mining technique, thereby demonstrating the usefulness of this technique for analyzing complex hospital processes at a low cost. CONCLUSION: This study confirmed the effectiveness of process mining technology at an actual hospital site. In future studies, the use of process mining technology will be expanded by applying this approach to a larger variety of process change situations.