Occupational injuries in Ohio wood product manufacturing: A descriptive analysis with emphasis on saw‐related injuries and associated causes

Beery, Lindsay; Harris, James R.; Collins, James W.; Current, Richard S.; Amendola, Alfred A.; Meyers, Alysha R.; Wurzelbacher, Steven J.; Lampl, Mike; Bertke, Stephen

doi:10.1002/ajim.22360

Cited by 10 publications

(14 citation statements)

References 13 publications

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“…Kickback generally results from the inappropriate use, such as improper operating procedures or conditions, of the power tool. Kickback was the most common trauma mechanism in our study, occurring in 47.1% of cases, which is consistent with the literature 8,13,14,22,23. Table saws have safety regulations requiring safety devices to avoid these accidents; however, they are frequently removed by operators for better visualization 11,24.…”

Section: Discussionsupporting

confidence: 91%

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Circular saw misuse is related to upper limb injuries: a cross-sectional study

Sabongi¹,

Erazo²,

Moraes³

et al. 2019

Clinics

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OBJECTIVES: Machinery injuries account for a substantial share of traumatic upper limb injuries (TULIs) affecting young active individuals. This study is based on the hypothesis that there is an important relationship between the improper use of power saws and TULIs. The aim of the study is to assess the prevalence and epidemiology of TULIs caused by power saws and determine the risks related to power saw use. METHODS: A cross-sectional evaluation of medical records from a two-year period was performed. Patients sustaining TULIs related to power saws were analyzed. Data on the epidemiology, site of injury, mechanism of trauma, technical specifications of the tool, cutting material, personal protective equipment, time lost and return to work were obtained. RESULTS: A database search retrieved 193 TULI records, of which 104 were related to power saws. The majority of patients were male (102/104; 98.1%), right-handed (97/104; 93.3%), and manual workers (46/104; 44.2%), with an average age of 46.8 years. The thumb was the most frequently injured site (32/93; 34.4%). Most of the injuries were caused by manual saws (85/104; 81.7%), and masonry saws accounted for 68.2% (58/85) of the cases. Masonry saws improperly used for woodwork resulted in 86.2% (50/58) of the injuries. TULI caused by masonry saws was 5 times higher in manual workers than in other patients. In addition, masonry saws had a risk of kickback 15 times higher than that of other saws, and the risk of injury increased by 5.25 times when the saws were used improperly for wood cutting. CONCLUSIONS: The profile of TULIs related to power saws was demonstrated and was mainly associated with manual saws operated by manual workers that inappropriately used masonry saws for woodworking.

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Section: Discussionsupporting

confidence: 91%

“…Among them, we highlight the safety devices that aim to avoid blade contact by kickback. After the establishment of regulations that require their use, there was substantial reduction in the incidence of injuries 11,23,24.…”

Section: Discussionmentioning

confidence: 99%

Circular saw misuse is related to upper limb injuries: a cross-sectional study

Sabongi¹,

Erazo²,

Moraes³

et al. 2019

Clinics

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“…The OHBWC database includes information on injured‐worker demographics, industry, occupation, and diagnoses as well as a free‐text narrative description of the injury incident. All claims were assigned single or multiple International Classification of Disease, Ninth Revision, Clinical Modification (ICD‐9‐CM) diagnosis codes, and one code was identified as an optimal return‐to‐work (RTW) code based on an OHBWC algorithm designed to identify the diagnosis most likely to keep the injured worker off for the longest period of disability . This analysis focused solely on the optimal RTW diagnosis codes to emphasize the injuries with the greatest worker and workforce impact.…”

Section: Methodsmentioning

confidence: 99%

Workers' compensation injury claims among workers in the private ambulance services industry—Ohio, 2001–2011

Reichard

Al‐Tarawneh

Konda

et al. 2018

American J Industrial Med

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Background Ambulance service workers frequently transfer and transport patients. These tasks involve occupational injury risks such as heavy lifting, awkward postures, and frequent motor vehicle travel. Methods We examined Ohio workers’ compensation injury claims among state‐insured ambulance service workers working for private employers from 2001 to 2011. Injury claim counts and rates are presented by claim types, diagnoses, and injury events; only counts are available by worker characteristics. Results We analyzed a total of 5882 claims. The majority were medical‐only (<8 days away from work). The overall injury claim rate for medical‐only and lost‐time cases was 12.1 per 100 full‐time equivalents. Sprains and strains accounted for 60% of all injury claims. Overexertion from patient handling was the leading injury event, followed by motor vehicle roadway incidents. Conclusions Study results can guide the development or improvement of injury prevention strategies. Focused efforts related to patient handling and vehicle incidents are needed.

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“…Finally, the 57 resulting injury categories were based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code for the “optimal return to work” (i.e. most severe) diagnosis (Beery et al, 2014) listed on the claim, which OHBWC defines as the injury that most likely will keep the injured worker off of work for the longest period of time and is assigned via a proprietary OHBWC algorithm. Details for the injury category variable have been previously described (Bertke et al, 2012) and inclusion of this additional field previously showed a substantial improvement on the auto-coding performance, namely raising the overall accuracy by about 5%.…”

Section: Methodsmentioning

confidence: 99%

Comparison of methods for auto-coding causation of injury narratives

Bertke

Meyers

Wurzelbacher

et al. 2016

Accident Analysis & Prevention

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Manually reading free-text narratives in large databases to identify the cause of an injury can be very time consuming and recently, there has been much work in automating this process. In particular, the variations of the naïve Bayes model have been used to successfully auto-code free text narratives describing the event/exposure leading to the injury of a workers’ compensation claim. This paper compares the naïve Bayes model with an alternative logistic model and found that this new model outperformed the naïve Bayesian model. Further modest improvements were found through the addition of sequences of keywords in the models as opposed to consideration of only single keywords. The programs and weights used in this paper are available upon request to researchers without a training set wishing to automatically assign event codes to large data-sets of text narratives. The utility of sharing this program was tested on an outside set of injury narratives provided by the Bureau of Labor Statistics with promising results.

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Occupational injuries in Ohio wood product manufacturing: A descriptive analysis with emphasis on saw‐related injuries and associated causes

Cited by 10 publications

References 13 publications

Circular saw misuse is related to upper limb injuries: a cross-sectional study

Circular saw misuse is related to upper limb injuries: a cross-sectional study

Workers' compensation injury claims among workers in the private ambulance services industry—Ohio, 2001–2011

Comparison of methods for auto-coding causation of injury narratives

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