Evaluating the effectiveness of a logger safety training program

INTRODUCTION: Logger safety training programs are rarely, if ever, evaluated as to their effectiveness in reducing injuries. METHOD: Workers' compensation claim rates were used to evaluate the effectiveness of a logger safety training program, the West Virginia Loggers' Safety Initiative (LSI). RESULTS: There was no claim rate decline detected in the majority (67%) of companies that participated in all 4 years of the LSI. Furthermore, their rate did not differ from the rest of the WV logging industry that did not participate in the LSI. Worker turnover was significantly related to claim rates; companies with higher turnover of employees had higher claim rates. Companies using feller bunchers to harvest trees at least part of the time had a significantly lower claim rate than companies not using them. Companies that had more inspections per year had lower claim rates. CONCLUSIONS: High injury rates persist even in companies that receive safety training; high employee turnover may affect the efficacy of training programs. The logging industry should be encouraged to facilitate the mechanization of logging tasks, to address barriers to employee retention, and to increase the number of in-the-field performance monitoring inspections. Impact on industry There are many states whose logger safety programs include only about 4-8 hours of safe work practices training. These states may look to West Virginia's expanded training program (the LSI) as a model for their own programs. However, the LSI training may not be reaching loggers due to the delay in administering training to new employees and high levels of employee turnover. Regardless of training status, loggers' claim rates decline significantly the longer they work for a company. It may be that high injury rates in the state of West Virginia would be best addressed by finding ways to encourage and facilitate companies to become more mechanized in their harvesting practices, and to increase employee tenure. Increasing the number of yearly performance inspections may also be a venue to reduce claim rates. Future research could investigate in better detail the working conditions of West Virginia loggers and identify barriers to job tenure, particularly for workers whose primary job task is chainsaw operation. A larger-scale study of the effect of performance monitoring inspections on claim rates is also warranted.     

Assessment of perceived injury risks and priorities among truck drivers and trucking companies in Washington State

Problem

The trucking industry experiences one of the highest work-related injury rates. Little work has been conducted previously in the United States to assess the hazards, needs, and injury prevention priorities in trucking. Method: Two separate industry-wide surveys of 359 trucking companies and 397 commercial truck drivers were conducted in Washington State. Results: Trucking companies and drivers both ranked musculoskeletal and slip, trip, fall injuries as the top two priorities. Controlling heavy lifting, using appropriate equipment, and addressing slippery surfaces were frequently listed as solutions. There appears to be a gap in safety climate perception between workers and employers. However, driver and company priorities agreed with industry workers' compensation claims. There is room for safety program management improvement in the industry. The study findings detail opportunities for prioritizing and reducing injuries. Impact on Industry: This information can be used to focus and design interventions for the prevention of work-related injuries while improving industry competitiveness.     

Evaluation of a safety training program in three food service companies

Problem: Outcome measures for safety training effectiveness research often do not include measures such as occupational injury experience. Effectiveness mediators also receive sparse attention. Method: A new safety training curriculum was delivered to workers in a stratified random sample of food service facilities across three companies. A similar group of facilities received usual training. We collected post-test measures of demographic variables, safety knowledge, perceptions of transfer of training climate, and workers' compensation claim data for one year after the initial training activities. Results: Knowledge test scores were apparently higher in the new-training units than in the usual-training units. Some demographic variables were inconsistently associated with these differences. Evidence for reduction of the injury rate associated with the new training was observed from two companies but only approached significance for one company. A second company revealed a similar but non-significant trend. Knowledge scores were not significantly associated with lower injury rates. Discussion: We found evidence that safety training increases knowledge and reduces injuries. We found almost no evidence of effects of training effectiveness mediators, including no relationship between safety knowledge and injury experience. Methodological issues related to conducting a large study may have influenced these results. Impact on Industry: Although safety training leads to greater knowledge and, in some cases, reduced occupational injuries, the influence of mediating variables remains to be fully explained.     

Assessing disabling and non-disabling injuries and illnesses using accepted workers compensation claims data to prioritize industries of high risk for Oregon young workers

Introduction: Young workers are especially vulnerable to occupational injuries and illnesses. There is a continued need to investigate injury burden among young workers across demographics and industry to inform targeted interventions. Workers compensation (WC) claims are important for quantifying work-related injuries and illnesses, however published studies have focused on disabling claims. This study extended previous research on Oregon young workers by including the most recent WC claims data to identify patterns of injury and high risk industries. Methods: We obtained all accepted disabling claims (N = 13,360) and a significant portion of non-disabling claims (N = 24,660) on workers aged 24 years and under from 2013 to 2018. Claim count, rate and cost were calculated by year, age, gender, industry, and injury type. A prevention index (PI) method was used to rank industries in order to inform prevention efforts. Results: Average annual disabling and non-disabling claim rates were 111.6 and 401.3 per 10,000 young workers. Workers aged 19–21 (disabling: 119.0 per 10,000 and non-disabling: 429.3) and 22–24 years (115.7 and 396.4) and male workers (145.3 and 509.0) had higher claim rates than workers aged 14–18 (80.6 and 297.0) and female workers (79.8 and 282.9). The most frequent injury types were “struck by/against” (35.6%) and “work-related musculoskeletal disorders (WMSDs)” (19.5%). High risk industries included agriculture, construction, and manufacturing for both genders combined. For female young workers, the highest risk industry was healthcare. Conclusions: This study demonstrated the added value of non-disabling WC claims data. Using both disabling and non-disabling data and PI method, agriculture, construction, manufacturing and healthcare industries were identified as priority workplaces to prevent common and costly injuries among Oregon young workers. Practical Applications: While the industries identified are considered hazardous for all workers, findings in this study can guide targeted research and prevention efforts specific to young workers.     

Injuries among electric power industry workers, 1995–2013

IntroductionWorkers in the electric power industry face many risks of injury due to the high diversity of work tasks performed in potentially hazardous and unpredictable work environments.MethodWe calculated injury rates by age, sex, occupational group, and injury type among workers in the Electric Power Research Institute’s (EPRI) Occupational Health and Safety Database (OHSD), which contains recordable injury, medical claims, and personnel data from 18 participating electric power companies from 1995 to 2013.ResultsThe OHSD includes a total of 63,193 injuries over 1,977,436 employee-years of follow-up, for an overall injury rate of 3.20 injuries per 100 employee-years. Annual injury rates steadily decreased from 1995 to 2000, increased sharply in 2001, and subsequently decreased to their lowest rate of 1.31 injuries per 100 employee-years in 2013. Occupations with the highest injury rates were welders (13.56 per 100 employee-years, 95% CI 12.74–14.37), meter readers (12.04 per 100 employee-years, 95% CI 11.77–12.31), and line workers (10.37 per 100 employee-years, 95% CI 10.19–10.56). Males had an overall higher injury rate compared to females (2.74 vs. 1.61 per 100 employee-years) although some occupations, such as meter reader, had higher injury rates for females. For all workers, injury rates were highest for those in the 21 to 30 age group (3.70 per 100 employee-years) and decreased with age. Welders and machinists did not follow this trend and had higher injury rates in the 65 + age group. There were 63 fatalities over the 1995 to 2013 period, with 21 fatalities (33.3%) occurring among line workers.ConclusionsAlthough injury rates have decreased over time, certain high-risk groups remain (i.e., line workers, mechanics, young males, older welders and machinists, and female meter readers).Practical applicationsProtective measures and targeted safety programs may be warranted to ensure the safety of electric power workers.     

Hand tool injuries at work: A surveillance perspective

This paper reports results of a surveillance study of work injuries caused by power and nonpower hand tools. Analyzing 129,399 case reports of hand tool injury compensation claims from the 1983 Supplementary Data System of the Bureau of Labor Statistics, the authors determined that nonpower hand tool injury rates were highest in agriculture, followed by construction, mining, and retail trades. For power hand tool injury rates, the order was: construction, agriculture, manufacturing, and mining. Among nonpower hand tools, hand knives were prominent, causing large proportions of injuries to workers in the food preparation occupations and farm laborers. Power hand tool injuries were most often associated with saws, which accounted for large proportions of injuries to lumbermen, carpenters, and miscellaneous laborers. Most injuries could be described as acute trauma involving upper extremities, but musculoskeletal injuries were also documented in substantial numbers. The authors provide suggestions for focused investigations to follow the surveillance effort reported here.     

Development and evaluation of a Naïve Bayesian model for coding causation of workers’ compensation claims

IntroductionTracking and trending rates of injuries and illnesses classified as musculoskeletal disorders caused by ergonomic risk factors such as overexertion and repetitive motion (MSDs) and slips, trips, or falls (STFs) in different industry sectors is of high interest to many researchers. Unfortunately, identifying the cause of injuries and illnesses in large datasets such as workers’ compensation systems often requires reading and coding the free form accident text narrative for potentially millions of records.MethodTo alleviate the need for manual coding, this paper describes and evaluates a computer auto-coding algorithm that demonstrated the ability to code millions of claims quickly and accurately by learning from a set of previously manually coded claims.ConclusionsThe auto-coding program was able to code claims as a musculoskeletal disorders, STF or other with approximately 90% accuracy.Impact on industryThe program developed and discussed in this paper provides an accurate and efficient method for identifying the causation of workers' compensation claims as a STF or MSD in a large database based on the unstructured text narrative and resulting injury diagnoses. The program coded thousands of claims in minutes. The method described in this paper can be used by researchers and practitioners to relieve the manual burden of reading and identifying the causation of claims as a STF or MSD. Furthermore, the method can be easily generalized to code/classify other unstructured text narratives.     

Vibration and jarring as a cause of back injury in the NSW coal mining industry

Head neck and back injury represents 32% of injuries in the NSW coal mining industry. There is considerable hearsay evidence that rough rides in vehicles are a significant cause of such injuries but no objective studies have been carried out.Analysis of workers compensation data showed that overexertion and slips and falls were the most significant causes of head neck and back injuries but approximately 11% of all head neck and back injuries were reported to be due to vehicle jarring. Two types of underground vehicles accounted for 53% of all injuries. These were Shuttlecars and Underground Transporters.There was no evidence from the compensation data that whole body vibration was a significant factor in head neck and back injuries.     

Logging injuries for a 10-year period in Jilin Province of the People's Republic of China

PROBLEM: Logging continues to be a major source of injuries in northeast China. This paper describes logging-related injuries in the Jilin Province of the People's Republic of China. METHODS: Logging fatalities and nonfatal injuries were summarized from 1981 to 1990 in Jilin. Injury data from 1991 for the entire forestry sector in China were also analyzed. RESULTS: Fatalities were mainly from of head injuries and were caused by being struck by an object. Nonfatal injuries were most often to the lower extremities and the head and were normally caused by being struck by an object or a fall or slip. The majority of both fatal and nonfatal logging injuries occurred to workers with less than 1 year of employment and those under 35 years old. Most injuries occurred November through March in Jilin. IMPACT ON INDUSTRY: Patterns of logging injury in Jilin of China were similar, but not identical, to those described in other studies of logging injuries worldwide. Methods found to be effective in reducing logging-related injuries in other parts of the world might be used in China to reduce the injuries associated with logging.     

Fewer workers' compensation claims and lower claim costs if employers with high injury rates achieved the rates of their safer peers

Introduction: Employers engaged in similar business activities demonstrate a range of workers' compensation claim rates. Workplace injuries and illnesses could be prevented if employers with high claim rates achieved the claim rates of their safer peers. Methods: We used Washington workers' compensation claims data for years 2013–2015 to calculate rates of compensable claims (eligible for disability or time loss benefits, if unable to work four days after injury) and total accepted claims (compensable plus medical-aid only claims) for each employer. We estimated the number and cost of claims to occur if employers with high claim rates reduced them to the rates of employers at the 25th percentile, adjusted for insurance risk class, employer size, and injury type. To evaluate the impact of setting more or less ambitious goals, we also estimated reductions based on claim rates at the 10th and 50th percentiles. Results: Over 43% of claims and claim costs would be prevented if employers with higher claim rates lowered them to the 25th percentile using either total accepted or compensable claim rates as the benchmark outcome. The estimated claim cost savings from benchmarking to compensable claims was nearly as great as the estimate based on benchmarking to total accepted claims ($308.5 mil annually based on compensable claims vs. $332.4 mil based on total accepted claims). Restaurants and Taverns had the greatest number of potentially prevented compensable claims. Colleges and Universities and Wood Frame and Building Construction had the greatest potential reduction in compensable claim costs among larger and smaller employers, respectively. Conclusion: Substantial reductions in workers' compensation claims and costs are possible if employers achieve the injury rates experienced by their safer peers. Practical application: Evaluating the range of workplace injury rates among employers within industry groups identifies opportunities for injury prevention and offers another approach to resource allocation.     

Work-related injuries among commercial janitors in Washington State,comparisons by gender

IntroductionWe analyzed workers' compensation (WC) data to identify characteristics related to workers' compensation claim outcomes among janitorial service workers in Washington State.MethodWe analyzed WC data from the Washington State Department of Labor & Industries (L&I) State Fund (SF) from January 1, 2003 through December 31, 2013, for janitorial service workers employed in the National Occupational Research Agenda (NORA) Services Sector. We constructed multivariable models to identify factors associated with higher medical costs and increased time lost from work.ResultsThere were 2,390 janitorial service compensable claims available for analysis. There were significant differences in injury type and other factors by gender, age, and language preference. Linguistic minority status was associated with longer time loss and higher median medical costs. Women were estimated to account for 35% of janitorial service workers but made up 55% of the compensable claims in this study.ConclusionsJanitorial service workers comprise a large vulnerable occupational group in the U.S. workforce. Identifying differences by injury type and potential inequitable outcomes by gender and language is important to ensuring equal treatment in the workers' compensation process.Practical applicationsThere were significant differences in injury and individual characteristics between men and women in this study. Women had twice the estimated rate of injury to men, and were more likely to require Spanish language materials. Improving communication for training and knowledge about the workers' compensation system appear to be high priorities in this population of injured janitorial service workers.     

Rate of occupational accidents in the mining industry since 1950--a successful approach to prevention policy

This paper deals with the decrease in the rate of accident insurance claims in the German mining industry over the last five decades. It intends to show that this process is above all the result of a prevention policy where companies and the body responsible for the legal accident insurance in the mining industry, the Bergbau-Berufsgenossenschaft (BBG), work hand in hand. A system like the German accident insurance scheme, combining prevention, rehabilitation, and compensation, enables successful and modern safety and health measures.     

The use of state workers' compensation administrative data to identify injury scenarios and quantify costs of work-related traumatic brain injuries

PROBLEM: Traumatic brain injury (TBI) is a public health problem but little is known about the nature of that problem in the working population. METHOD: The author used a national definition to identify cases in Washington State from workers' compensation (WC) hospital billing data, quantified the cost of WC insurance benefits using actuarial cost estimates, and identified high risk industries using ANSI Z16.2 typology. RESULTS: There were 928 cases of TBI with a lifetime claim cost of $159 million from the Washington State Fund (1994-2001). Sixty percent of injuries resulted in death or disability. The highest risks of TBI are concentrated in 16 industrial insurance risk classes and the highest costs in 19 North American Industry Classification codes. Injury scenarios were identified for nine industrial insurance risk classes. CONCLUSIONS: TBI is a disabling and costly workplace injury in the state of Washington, affecting even teenagers and seniors who are not generally considered to be part of the workforce. Injury typology codes provide useful information for improving workplace safety. IMPACT ON INDUSTRY: This research provides industry with quantitative information regarding the cost of work-related traumatic brain injury and the usefulness of using workers' compensation claims data to reduce the burden of workplace injury.     

Prioritizing prevention opportunities in the Washington State construction industry, 2003-2007

Objective

This study compares construction industry groups in Washington State by injury severity and cost, and ranks industry groups according to potential for prevention.

Methods

All Washington State workers' compensation compensable claims with date of injury between 2003 and 2007 were classified into North American Industrial Classification System (NAICS) industry groups. Claims were then aggregated by injury type and industry groups were ranked according to a prevention index (PI). The PI is the average of the rank orders of the claim count and the claim incidence rate. A lower PI indicates a higher need for prevention activities. The severity rate was calculated as the number of days of time loss per 10,000 full-time equivalents (FTEs).

Results

For all injury types, construction industry groups occupy 7 of the top 15 PI ranks in Washington State. The severity rate among construction industry groups was twice that for non-construction groups for all injury types. Foundation, structure, and building exterior contractors (NAICS 2381) ranked highest in prevention potential and severity among construction industry groups for most common injury types including falls from elevation, fall on same level, struck by/against, and musculo-skeletal disorders of the neck, back, and upper extremity (WMSDs). Median claim costs by injury type were generally higher among construction industry groups.

Conclusions

The construction industry in Washington State has a high severity rate and potential for prevention. The methods used for characterizing these industry groups can be adapted for comparison within and between other industries and states.

Impact on Industry

These data can be used by industry groups and employers to identify higher cost and higher severity injury types. Knowledge about the relative frequencies and costs associated with different injury types will help employers and construction industry associations make better informed decisions about where prevention efforts are most needed and may have the greatest impact. The results of this study can also be used by industry stakeholders to cooperatively focus on high cost and high severity injuries and explore best practices, interventions, and solutions as demonstrated by efforts to prevent musculoskeletal disorders in masonry (Entzel, Albers, & Welch, 2007). Initiating construction industry groups to focus on high cost and high severity injuries may also help prevent other types of injuries.     

Work environment risk factors for injuries in wood processing

Problem

The reported injury rate for wood product manufacturing in Maine, 1987-2004, was almost twice the state-wide average for all jobs. Method: A case-control study was conducted in wood processing plants to determine preventable risk factors for injury. A total of 157 cases with injuries reported to workers' compensation and 251 controls were interviewed. Results: In multivariable analyses, variables associated with injury risk were high physical workload, machine-paced work or inability to take a break, lack of training, absence of a lockout/tagout program, low seniority, and male gender. Different subsets of these variables were significant when acute incidents and overexertions were analyzed separately and when all injuries were stratified by industry sub-sector. Impact on industry: Generalizability may be limited somewhat by non-representative participation of workplaces and individuals. Nevertheless, these findings provide evidence that many workplace injuries occurring in wood processing could be prevented by application of ergonomics principles and improved work organization.     

Workers’ compensation claim counts and rates by injury event/exposure among state-insured private employers in Ohio, 2007–2017

Introduction: This study analyzed workers’ compensation (WC) claims among private employers insured by the Ohio state-based WC carrier to identify high-risk industries by detailed cause of injury. Methods: A machine learning algorithm was used to code each claim by U.S. Bureau of Labor Statistics (BLS) event/exposure. The codes assigned to lost-time (LT) claims with lower algorithm probabilities of accurate classification or those LT claims with high costs were manually reviewed. WC data were linked with the state’s unemployment insurance (UI) data to identify the employer’s industry and number of employees. BLS data on hours worked per employee were used to estimate full-time equivalents (FTE) and calculate rates of WC claims per 100 FTE. Results: 140,780 LT claims and 633,373 medical-only claims were analyzed. Although counts and rates of LT WC claims declined from 2007 to 2017, the shares of leading LT injury event/exposures remained largely unchanged. LT claims due to Overexertion and Bodily Reaction (33.0%) were most common, followed by Falls, Slips, and Trips (31.4%), Contact with Objects and Equipment (22.5%), Transportation Incidents (7.0%), Exposure to Harmful Substances or Environments (2.8%), Violence and Other Injuries by Persons or Animals (2.5%), and Fires and Explosions (0.4%). These findings are consistent with other reported data. The proportions of injury event/exposures varied by industry, and high-risk industries were identified. Conclusions: Injuries have been reduced, but prevention challenges remain in certain industries. Available evidence on intervention effectiveness was summarized and mapped to the analysis results to demonstrate how the results can guide prevention efforts. Practical Applications: Employers, safety/health practitioners, researchers, WC insurers, and bureaus can use these data and machine learning methods to understand industry differences in the level and mix of risks, as well as industry trends, and to tailor safety, health, and disability prevention services and research.     

An analysis of injury claims from low-seam coal mines

Introduction

The restricted workspace present in low-seam coal mines forces workers to adopt awkward working postures (kneeling and stooping), which place high physical demands on the knee and lower back.

Method

This article provides an analysis of injury claims for eight mining companies operating low-seam coal mines during calendar years 1996-2008. All cost data were normalized using data on the cost of medical care (MPI) as provided by the U.S. Bureau of Labor Statistics.

Results

Results of the analysis indicate that the knee was the body part that led in terms of claim cost ($4.2 million), followed by injuries to the lower back ($2.7 million). While the average cost per injury for these body parts was $13,100 and $14,400, respectively (close to the average cost of an injury overall), the high frequency of these injuries resulted in their pre-eminence in terms of cost. Analysis of data from individual mining companies suggest that knee and lower back injuries were a consistent problem across companies, as these injuries were each among the top five most costly part of body for seven out of eight companies studied.

Application/Impact

Results of this investigation suggest that efforts to reduce the frequency of knee and low back injuries in low-seam mines have the potential to create substantial cost savings.     

Reporting occupational injuries: The first step

Attempts to evaluate occupational injury surveillance systems have centered on employer compliance. Surveillance systems also rely on employees reporting injuries, and the reliability of such reporting is unknown. In this study of hospital environmental service workers, 29.2% (108 of 372) recalled having been injured in the previous year, and of these, 38.9% (42 of 108) had not reported one or more injuries. Among those injured, older workers (mean age 40.6 years vs. 36.2 years; p = 0.024) and those having worked longer at the same job (mean duration 6.7 years vs. 4.3 years; p = 0.032) were more likely to not report an injury. The most frequently cited reason for not reporting was that the injury had seemed too minor, though 64.4% of unreported injuries required medical care and 44.1% resulted in lost work time.