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Workers' Compensation Data (workers' + compensation_data)
Selected AbstractsRelationship of work injury severity to family member hospitalizationAMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 5 2010Abay G. Asfaw PhD Abstract Background Working while under stress due to a family health event may result in injuries of greater severity. Work leave might mitigate such consequences. Data and Methods Workers' compensation data for 33,817 injured workers and inpatient medical data for 76,077 members of their families were extracted from the 2002,2005 Thomson Reuters Medstat MarketScan Health and Productivity Management (HPM) and Commercial Claims and Encounter (CCE) datasets. Using a probit model, the impact of family hospitalization on the probability that a subsequent injury would be severe (above average indemnity costs) was estimated, adjusting for age, sex, hourly versus salaried status, industry sector, state, and family size. Results Family hospitalization within 15 days before injury increased the likelihood that the injury would be severe (from 12.5% to 21.5%) and was associated with 40% higher indemnity costs and 50% higher medical costs. Hospitalizations over 30 days before injury had no impact. Conclusion The observed higher severity of work injuries following family hospitalizations suggests additional analyses may find higher injury rates as well, and that timely family leaves might help prevent severe workplace injuries. Am. J. Ind. Med. 53:506,513, 2010. © 2010 Wiley-Liss, Inc. [source] The Pennsylvania certified safety committee program: An evaluation of participation and effects on work injury ratesAMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 8 2010Hangsheng Liu PhD Abstract Background Since 1994, Pennsylvania, like several other states, has provided a 5% discount on workers' compensation insurance premiums for firms with a certified joint labor management safety committee. This study explored the factors affecting program participation and evaluated the effect of this program on work injuries. Methods Using Pennsylvania unemployment insurance data (1996,2006), workers' compensation data (1998,2005), and the safety committee audit data (1999,2007), we conducted propensity score matching and regression analysis on the program's impact on injury rates. Results Larger firms, firms with higher injury rates, firms in high risk industries, and firms without labor unions were more likely to join the safety committee program and less likely to drop out of the program. The injury rates of participants did not decline more than the rates for non-participants; however, rates at participant firms with good compliance dropped more than the rates at participant firms with poor compliance. Conclusions Firm size and prior injury rates are key predictors of program participation. Firms that complied with the requirement to train their safety committee members did experience reductions in injuries, but non-compliance with that and other requirements was so widespread that no overall impact of the program could be detected. Am. J. Ind. Med. 53:780,791, 2010. © 2010 Wiley-Liss, Inc. [source] Work-related amputations in Washington state, 1997,2005AMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 7 2010Naomi J. Anderson MPH Abstract Background Work-related amputations are infrequent but devastating injuries. Attempts to more accurately estimate the burden of amputations and industries at risk have led the Washington State occupational surveillance program to explore new methods for case identification in Washington State workers' compensation data. Methods Two methods were utilized for case identification of work-related amputations. The first method used the ANSI Z16 nature code for amputation. An alternative method utilized medical, hospital, and claim administration coding of medical bills and bill payment systems. After identifying suspected amputation claims, a sample of the medical records associated with different case identification methods were reviewed to verify that an amputation likely occurred. Results From 1997 to 2005, 2,528 amputations were identified using the ANSI Z16 code for amputation (Nature,=,100) and an additional 3,912 amputations were identified using the alternative method. There was an increasing trend of amputation injuries over the time period using the ANSI amputation definition; however, the trend in amputation injuries captured by the alternative method was decreasing. This may indicate a bias in estimating a trend due to misclassification of amputation injuries. The sectors with the highest amputation claims rates were Manufacturing; Construction; Agriculture, Forestry, Fishing and Hunting; Accommodation and Food Services; and Wholesale and Retail Trade. Conclusions Current methods to identify work-related amputations in the workers' compensation data system underestimate the burden of amputations in Washington State. By utilizing alternative case identification methods, we estimate that there were about 150% more amputations in Washington State over the time period. Am. J. Ind. Med. 53:693,705, 2010. © 2010 Wiley-Liss, Inc. [source] Temporary workers in Washington StateAMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 2 2010Caroline K. Smith MPH Abstract Background Evidence regarding the unequal burden of occupational injuries between workers employed by temporary agencies and those in standard employment arrangements is unclear. Studies range from no significant differences in risk to substantial increased risk for temporary workers. The purpose of this study is to compare the workers' compensation experience of a large cohort of temporary agency employed workers with those in standard forms of employment. Methods Washington State Fund workers' compensation data were obtained for claims with injury dates from January 1, 2003 to June 30, 2006, resulting in 342,540 accepted claims. General descriptive statistics, injury rates (per 10,000 FTE), and rate ratios (temp agency/standard employer) were computed by injury type and industry. Results Temporary agency employed workers had higher rates of injury for all injury types, and higher median time loss (40 vs. 27 days) but lower time loss costs (median $1,224 vs. $1,914, P,<,0.001) and lower medical costs ($3,026 vs. $4,087, P,<,0.001) than standard arrangement workers. Temporary agency workers had substantially higher rates for "caught in" and "struck by" injuries in the construction (IRR 4.93; 95% CI 2.80,8.08) and manufacturing (IRR 4.05; 95% CI 3.25, 5.00) industry sectors. Conclusion Temporary agency employed workers have higher claims incidence rates than those in standard employment arrangements. The rate ratios are twofold higher in the construction and manufacturing industry sectors. More research is needed to explore potential reasons for this disparity in occupational injuries. Industry or some measure of job exposure should be included when comparing injury rates in different types of employment in order to better identify areas for prevention. Am. J. Ind. Med. 53:135,145 2010. © 2009 Wiley-Liss, Inc. [source] Livestock-handling injuries in agriculture: An analysis of Colorado workers' compensation data,AMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 5 2009David I. Douphrate PhD Abstract Background Previous studies have reported that livestock-handling injuries are among the most severe of agricultural injuries. This study identifies the costs, characteristics, and contributing factors associated with livestock-handling injuries among Colorado dairy farmers, cattle/livestock raisers, and cattle dealers. Methods A 10-year (1997,2006) history of Colorado's workers' compensation claims data was used for analysis. Descriptive analyses of livestock-handling injury claims were performed. Claim cost analysis was also conducted. The agent,host,environment epidemiological model was used to analyze injury event descriptions. Results A total of 1,114 livestock-handling claims were analyzed. Claims associated with milking parlor tasks represented nearly 50% of injuries among dairy workers. Claims associated with riding horseback, sorting/penning cattle, and livestock-handling equipment represented high proportions of livestock-handling injuries among cattle/livestock raisers and cattle dealers. Claims associated with livestock-handling represented the highest percentage of high-cost and high-severity injuries in all three sectors. Conclusions Livestock-handling injuries are a significant problem, more costly, and result in more time off work than other causes of agricultural injuries. There is a strong and compelling need to develop cost-effective interventions to reduce the number of livestock-handling injuries in agriculture. Am. J. Ind. Med. 52:391,407, 2009. © 2009 Wiley-Liss, Inc. [source] Estimating fatality rates in occupational light vehicle users using vehicle registration and crash dataAUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, Issue 2 2010Rwth Stuckey Abstract Objective: To estimate occupational light vehicle (OLV) fatality numbers using vehicle registration and crash data and compare these with previous estimates based on workers' compensation data. Method: New South Wales (NSW) Roads and Traffic Authority (RTA) vehicle registration and crash data were obtained for 2004. NSW is the only Australian jurisdiction with mandatory work-use registration, which was used as a proxy for work-relatedness. OLV fatality rates based on registration data as the denominator were calculated and comparisons made with published 2003/04 fatalities based on workers' compensation data. Results: Thirty-four NSW RTA OLV-user fatalities were identified, a rate of 4.5 deaths per 100,000 organisationally registered OLV, whereas the Australian Safety and Compensation Council (ASCC), reported 28 OLV deaths Australia-wide. Conclusions: More OLV user fatalities were identified from vehicle registration-based data than those based on workers' compensation estimates and the data are likely to provide an improved estimate of fatalities specific to OLV use. Implications: OLV-use is an important cause of traumatic fatalities that would be better identified through the use of vehicle-registration data, which provides a stronger evidence base from which to develop policy responses. [source] | ||||||||||