Sample Strategies Industrial Hygiene Modeler (SIHM)-An open-source exposure assessment performance tool

Robust industrial hygiene exposure assessment strategies are used by less than one-third of practitioners in the United States, despite being more effective at identifying unacceptable exposures than following minimum compliance sampling practices. To support initiatives addressing this issue, this paper presents the development and application of the Sample Strategies Industrial Hygiene Modeler (SIHM), a modeling program designed to facilitate direct comparison of the performance between various exposure data collection and judgment approaches. SIHM was developed in the R programming language (version 4.3.2, R Foundation for Statistical Computing, Vienna, Austria), using statistical analysis codes that support the Expostats Toolkit. It is accessed online as an open-source application and includes walkthrough videos on functionality. SIHM generates metrics that show how often a strategy determines the correct result above or below a specified criterion, such as an occupational exposure limit (OEL), when repeatedly sampled from a 250 working day exposure dataset. SIHM can be used in training and program development on exposure assessment strategy design by demonstrating the effectiveness of more robust approaches. Practitioners can make better decisions about exposure data collection and judgment approaches when they can analyze their relative performance, leading to better exposure decisions for workers.