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The effectiveness of occupational health and safety management systems (OHSMS) can be understood through analysis of surveys such as the experiences of exposure to occupational hazards by Australian nursing occupations. How effectively OHSMS are implemented in the Australian health industry is unclear as few studies describe current hazard exposure patterns or the impact of OHSMS in the Australian health industry. This paper concludes from the analysis of an Exposure Survey of Australian nursing occupations that nursing occupations perceive themselves to be "at risk" of injury and/or management of OHS risk in work duties is affected by the patterns of hazard exposure, occupation group as well as employee attributes, perceptions, patterns and situations of work. The results highlight the top-rated hazards and imply that the perceptions of hazards in the workplace are different to actual risk experience (e.g. injury patterns). There is an unacceptable level of exposure to diverse hazards in Australian nursing occupations workplaces in regard to regulatory and performance obligations. Stronger strategies to achieve more effective risk treatment, integrate with hospital accreditation and quality programs are discussed to benefit system performance and the welfare of those in nursing occupations.

The relatively large birth cohort between 1946 and 1964, combined with the economic recession in the first decade of the 21st century, have led to an increase in the proportion of older workers in the US workplace. Understanding the health and safety needs of an aging workforce will be critical, especially in the construction industry, where physical job demands are high. This paper reviews the epidemiologic literature on the impact of age on injury among workers in the construction industry in terms of cause, type, and cost. PubMed was searched by using the following terms: older workers, construction, construction industry, injury, and age. The available studies reported that, among the construction industry workforce, older age at injury was related to higher injury costs but not to number of injuries. The higher injury costs associated with worker age are likely due in part to the severity of the injuries sustained by older workers. Identification of injury trends and subsequent analytical research efforts designed to ascertain factors associated with injury among older construction workers are needed for employers to effectively manage a health and safety program that addresses the needs of the aging worker.

Background: Bayesian methods show promise for classifying injury narratives from large administrative datasets into cause groups. This study examined a combined approach where two Bayesian models (Fuzzy and Naïve) were used to either classify a narrative or select it for manual review., Methods: Injury narratives were extracted from claims filed with a worker's compensation insurance provider between January 2002 and December 2004. Narratives were separated into a training set (n=11,000) and prediction set (n=3,000). Expert coders assigned two-digit Bureau of Labor Statistics Occupational Injury and Illness Classification event codes to each narrative. Fuzzy and Naïve Bayesian models were developed using manually classified cases in the training set. Two semi-automatic machine coding strategies were evaluated. The first strategy assigned cases for manual review if the Fuzzy and Naïve models disagreed on the classification. The second strategy selected additional cases for manual review from the Agree dataset using prediction strength to reach a level of 50% computer coding and 50% manual coding., Results: When agreement alone was used as the filtering strategy, the majority were coded by the computer (n=1,928, 64%) leaving 36% for manual review. The overall combined (human plus computer) sensitivity was 0.90 and positive predictive value (PPV) was >0.90 for 11 of 18 2-digit event categories. Implementing the 2nd strategy improved results with an overall sensitivity of 0.95 and PPV >0.90 for 17 of 18 categories., Conclusions: A combined Naïve-Fuzzy Bayesian approach can classify some narratives with high accuracy and identify others most beneficial for manual review, reducing the burden on human coders.

Background: Little is known about the types of injuries and medical problems encountered by fire department personnel during suppression of large campaign-type wildland fires. Such information could help to plan for response to medical incidents during future wildfires., Objective: To describe the injuries and medical problems experienced by firefighters during the 2009 Los Angeles County Station Fire., Methods: This was a retrospective analysis of case records of patients treated during the Los Angeles County Station Fire. Data were abstracted from two sources: the incident command medical tracking sheet and prehospital patient care reports (PCRs)., Results: The sample included 183 patient contacts, of which PCRs were available for 65. For the remaining 118 patients, data were abstracted from the incident command medical tracking sheet. The most common chief complaint was extremity injury, accounting for 44 patient contacts (24% of all patients), with smoke inhalation second, at 32 patient contacts (17%). Of the 65 patients with PCRs, 31 (52%) were treated with oxygen, 26 (40%) had intravenous (IV) lines started, and 15 (23%) received an IV fluid bolus. Half of the patients were transported to an emergency department (ED); the remainder were treated on scene or self-transported to a non-acute care facility., Conclusions: Most firefighter injuries and illnesses encountered during the Los Angeles Station Fire were minor. The prevalence of injuries observed should be taken into consideration in creation of protocols and mandatory equipment lists for fireline paramedics. Furthermore, advanced training for paramedics in the diagnosis and treatment of minor medical conditions may be useful.