Meta-analysis of the quantitative effectiveness of risk management measures (RMM) in the workplace.

Background and objectives This paper describes an evaluation and analysis of an updated version of ECEL v3.0—an integrated risk management measure (RMM) library developed as part of a CEFIC LRI initiative. The occupational module contains extensive data on the quantitative effectiveness of RMMs to control inhalation and dermal exposure in the workplace. The objective was to investigate the effectiveness and variability in effectiveness of RMM and to explore the difference between optimal and non-optimal RMM applications in the workplace. Methods A new database structure and interface were developed and the content of the database was updated with a systematic literature review and integration with other databases (totalling 3373 records from 548 studies). To analyse the data, Bayesian linear mixed models were constructed with the study as a random effect and various study characteristics and RMM categories as fixed effects individually in separate models. A multivariate mixed model was used on a stratified dataset to test (amongst others) the conditions of RMM use. Results Analyses of the data indicated effectiveness values for each RMM category (for example ~87% for technical emission controls compared with ~60% for technical dispersion controls). Substantial variability in effectiveness was observed within and between different types of RMM. Seven study characteristics (covariables) were included in the analyses, which indicated a pronounced difference in as-built (optimal/experimental) and as-used (workplace) conditions of RMM use (93.3% and 74.6%, respectively). Conclusions This library provides a reliable evidence base to derive base estimates of RMM effectiveness—beneficial for both registrant and downstream users. It stresses the importance of optimal use of RMMs in the workplace (technical design/functioning, use, and maintenance). Various challenges are foreseen to further update ECEL to improve guidance, for deriving improved estimates and ensure user-friendliness of the library. [ABSTRACT FROM AUTHOR]