Managing Occupational Health and Safety in SMEs: An Evolutionary Webbased Tool Even though several guidelines have been proposed by public organizations about how to design an Occupational Health and Safety management system (OHSMS) customized to Small and Mediumsize Enterprises (SMEs), an approach integrating and OHSMS with the risk assessment under a unified and shared logic still misses. This paper presents an evolutionary OHS tool for SMEs that combines the advantages of a simplified procedure to develop a risk analysis and outline a set of risk prevention and protection measures at workplace, such as the one proposed by the Italian legislation, with the advantages of a simplified OHS management model. It is assumed that a software tool could be the preferential way to allow a wide diffusion and an effective application of this model. The online structure also enables distributing OHSrelated information directly from institutional databases. This information, provided within the same software tool used for risk assessment and OHS management, can significantly support in particular SMEs with a poor experience.

A Rulebased Framework for Risk Assessment in the Health Domain Abstract   Risk assessment is an important decision support task in many domains, including health, engineering, process management, and economy. There is a growing interest in automated methods for risk assessment. These methods should be able to process information efficiently and with little user involvement. Currently, from the scientific literature in the health domain, there is availability of evidencebased knowledge about specific risk factors. On the other hand, there is no automatic procedure to exploit this available knowledge in order to create a general risk assessment tool which can combine the available quantitative data about risk factors and their impact on the corresponding risk. We present a Framework for the Assessment of Risk of adverse Events (FARE) and its first concrete applications FRATup and DRATup, which were used for fall and depression risk assessment in older persons and validated on four and three European epidemiological datasets, respectively. FARE consists of i) a novel formal ontology called On2Risk; and ii) a logical and probabilistic rulebased model. The ontology was designed to represent qualitative and quantitative data about risks in a general, structured and machinereadable manner so that this data may be concretely exploited by risk assessment algorithms. We describe the structure of the FARE model in the form of logic and probabilistic rules. We show how when starting from machinereadable data about risk factors, like the data contained in On2Risk, an instance of the algorithm can be automatically constructed and used to estimate the risk of an adverse event.