Dose estimation from daily and weekly dosimetry data.
Ostrouchov G; Frome EL; Kerr GD
NIOSH 1998 Sep; :1-3
Statistical analyses of data from epidemiologic studies of workers exposed to radiation have been based on recorded annual radiation doses. It is usually assumed that the annual dose values are known exactly, although it is generally recognized that the data contain uncertainty due to measurement error and bias. In our previous work, a probability distribution was used to describe an individual's dose during a specific period of time and statistical methods were developed for estimating it from weekly film dosimetry data. This study showed that there was a systematic underestimation of doses for Oak Ridge National Laboratory (ORNL) workers. This could result in biased estimates of doseresponse coefficients and their standard errors. The result of this evaluation raised serious questions about the validity of the historical personnel dosimetry data that are being used in low-dose studies of nuclear industry workers. Here we develop new methods for using additional information from daily pocket-meter data and combining it with film dosimetry data to improve the distribution estimates. Together, the methods take into account the "measurement error" that is produced by the film and pocket-meter dosimetry systems, the biases introduced by policies that lead to recording left-censored doses as zeros, and other measurement and recording practices. The combined methodology is applied to a sample of dose histories obtained from hard copy dosimetry records at ORNL for the years 1945 to 1955. First, the rigorous addition of pocket-meter information shows that the negative bias is generally more severe than was reported earlier; however, the amount of bias also varies greatly between personyears. Second, the addition of pocket-meter information reduces uncertainty for some, while increasing it for others. Together, these results suggest that detailed pocket-meter and film dosimetry information is required to obtain unbiased and reliable dosimetry data for use in epidemiologic studies of workers at ORNL.
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