The validity of the EASE expert system for inhalation exposures.

Estimation and Assessment of Substance Exposure (EASE) is a computerized expert system developed by the UK Health and Safety Executive to facilitate exposure assessments in the absence of exposure measurements. The system uses a number of rules to predict a range of likely exposures or an 'end-point' for a given work situation. The purpose of this study was to identify a number of inhalation exposure measurements covering a wide range of end-points in the EASE system to compare with the predicted exposures. Occupational exposure data sets were identified from previous research projects or from consultancy work. Available information for each set of measurements was retrieved from archive storage and reviewed to ensure that it was adequate to enable EASE (version 2) predictions to be obtained. Exposure measurements and other relevant contextual data were abstracted and entered into a computer spreadsheet. EASE predictions were then obtained for each task or job and entered into the spreadsheet. In addition, we generated a random exposure range for each data set for comparison with the EASE predictions. Finally, we produced exposure assessments for a subset of the data using a structured subjective assessment method. We were able to identify approximately 4000 inhalation exposure measurements covering 52 different scenarios and 28 EASE end-points. The data included measurements of solvent vapours, non-fibrous dusts and fibres. In 62% of the end-points the EASE predictions were generally greater than the exposure measurements and in 30% of the end-points the EASE estimates were comparable with the measurements. The random allocation of exposure ranges was, as expected, less reliable than EASE, although there were still about one-third of the cases where the randomly generated exposure ranges generally agreed with the measurements. The structured subjective assessments undertaken by a human expert produced exposure estimates in better agreement with the measurements with about two-thirds of the end-points derived from these assessments in good agreement with the data. We argue that the inhalation exposure estimates from EASE could be improved by incorporating some of the parameters included in the structured subjective assessment methodology.