Occupational injury and illness rates are used by employers and regulatory agencies to monitor the health and safety of workers. Changes in the rates are interpreted to reflect actions taken or not taken by the employer. The purpose of this study was to delineate external factors, those factors outside the control of employers, which influence occupational injury and illness rates. The results of this study are useful in interpreting changes in the occupational injury and illness rates as a function of changes in the external factors. A review of the literature provided information on the type of external forces which would be expected to influence occupational injury/illness rates. The factors selected for the data analysis included economic indicators, regulatory budget and performance measures, firm size, and leniency in workers' compensation claim determination as measured by the proportion of denied claims. Data were collected on the injury/illness incidence, lost workday case incidence, and lost workday rates for the state of Oregon for 1978 through 1987. Multiple linear regression models were constructed for each of the injury/illness rates using a step-down variable selection process to determine the predictor variables for each model. Separate models were constructed for each dependent variable using the values of the predictor variables for the same year and for the preceding year. The results supported the hypotheses that the unemployment rate, gross state product, number of serious violations cited by OSHA, and percentage of claims denied by the Workers' Compensation Board influence occupational injury and illness rates. Total OSHA expenditures and the number of inspections conducted by OSHA in a given year demonstrated positive relationships with lost workday cases incidence and injury/illness incidence rates, respectively; the positive associations were contrary to the hypothesized relationships. Models can be constructed using data on external factors to predict injury/illness incidence, lost workday case incidence, and lost workday rates. The unemployment rate was the most useful variable in predicting occupational injury and illness rates. / Graduation date: 1991

The purpose of this study was to examine the total direct costs of occupational injuries as they relate to workers compensation allocations within a self-insured firm. Through the use of a model, this study provides financial impact information for safety professionals by defining the total direct costs of occupational injuries. The investigator constructed a model which traced actual workers compensation allocations over a five year period at a division of Hewlett-Packard in Corvallis, Oregon. The objective of this model was to compare actual workers compensation cost history with that of adjusted workers compensation cost data to determine the total direct costs that occupational injuries have on the division's workers compensation cost allocations. This study indicated that injuries produce cost impacts to divisions well beyond the injury compensation costs reported by insurance carrier payment summaries. The study at this specific Hewlett-Packard division in Oregon indicated total costs at 1.7 to 1.9 times the actual cost of workers compensation reimbursements. This study supports the need to continue research efforts that will further refine the identification of total injury costs and the impact these losses have on the business performance of a company. / Graduation date: 1993

Univ., Diss.--Paris 1, 2006.

published_or_final_version / Public Administration / Master / Master of Public Administration

The challenges in human resource allocation drive the present project. Conducted at an office of the Workers' Compensation Board of British Columbia (the WCB), the project aims at developing a simulation model of claim management operations to facilitate decision-making in resource allocation. In this context, resource allocation refers to the alignment of staff to claims. The components of the problem include the number of staff required and the types of staff required, given targeted system performance. The volume of claims, the profile of claims, the Workers Compensation Act, the board's business guidelines and the board's operational targets all influence staffing requirement. It is far from straightforward to answer the following questions: what is the optimal level of staffing? What is the right mix of skills? And what is the proper alignment of staff with claims? How will the system perform given a certain staffing level? How will change in the profile of incoming claims influence staffing requirement? A discrete-event simulation model was developed as a decision support tool in this project. The model was used to evaluate several resource allocation scenarios. Simulation showed that timeliness measures such as time to decision and time to closure would improve with additional resources, but the improvement was not drastic. At the staffing level of 14, compared to the current level of 12, time to decision for unadjudicated claims would reduce by 6%. Simulation further showed that specialization of staff by claim type might have a negative impact on system performance measures, because economics of scale were compromised. Finally, simulation showed that if Site Visits, a required procedure for adjudicating claims related to Activity-Related Soft Tissue Diseases, could be conducted by dedicated personnel, time to decision for these claims might reduce by as high as 60%.

Doctor of Philosophy (PhD) / Injuries to people living and working on farms in New South Wales continue to be a significant burden on the health system, Workers’ Compensation system, agricultural industries and farming families. Strategies to reduce the number and severity of injuries suffered by farmers and people working on farms rely on accurate information. Unfortunately there is no one dataset available to describe the circumstances surrounding farm injuries and the size of this burden in Australia. Hence, a number of different data sources are required to provide a picture of farm injuries. To date, there has been very little critical examination of what value each of these datasets provides to describing farm injuries. This Thesis aimed to: • Undertake surveillance of injuries occurring to people on farms or during agricultural production in NSW using data from an Emergency Department, NSW Hospital Separations information, NSW Workers’ Compensation Claims, and ABS Deaths data. • Critically examine the utility of Emergency Department, Hospital, Workers’ Compensation, and ABS Deaths Data for the surveillance of farm injuries in NSW. • Critically examine data classification systems used in Emergency Department, Hospital, Workers’ Compensation, and ABS Deaths data collections to describe the breadth of farm injuries in NSW. • Define the priority areas for farm injury prevention initiatives in NSW based on the information obtained from the examination of the data from Emergency Department, Hospital, Workers’ Compensation, and ABS Deaths. • Evaluate the effectiveness of the NSW Rollover Protective Structure (ROPS) rebate scheme and examine the utility of the data currently available in NSW to measure the performance of the program. Four datasets, Tamworth Emergency Department, Hospital Separations, Workers’ Compensation and the Australian Bureau of Statistics (ABS) Deaths data were used to provide information on the surveillance of farm injuries, describe the breadth of classifications used to describe farm injuries, and define priorities for the prevention of farm injuries. There were 384 farm-related injuries which presented to the Emergency Department at the Tamworth Base Hospital between 1 September 1997 and 31 August 1998. Emergency Department data collected in this study used the Farm Injury Optimal Dataset (FIOD) for classification, which allowed for a comprehensive picture of the circumstances surrounding the injury event. The three most common external causes of injury were related to horses, motorcycles, and animals. Commonly people were working at the time of injury. Children represented 21% of the people injured. The average number of injuries per 100 farms per annum was 34.7. An examination of hospital discharge data for NSW was undertaken for the period 1 July 1992 to 30 June 2000 where the location of the injury was a farm. Classification of cases in this dataset conformed to the International Classification of Disease (ICD) versions 9 and 10. There were 14,490 people who were injured on a farm during the study period. The three most common external causes of injury were motorcycles, animals being ridden and agricultural machinery. Children represented 17% of all farm injury cases. The rate per 1,000 farms ranged from 19 to 42 per annum. An examination of Workers’ Compensation claims for agricultural industries in NSW between 1 July 1992 and 30 June 2001 was undertaken. The ‘Type of Occurrence’ classification system was used to code the claims. There were 24,332 claims of which the majority were males (82%). The incidence of injury / disease in agriculture per annum varied from 37 per 1,000 workers to 73 per 1,000 workers. The rate per 1,000 agricultural establishments varied from 54 to 76. The average cost of a claim was $10,880 and the average time lost per claims was 9.2 weeks. There were 81 deaths and 3,158 permanent disabilities. The three most common agents were sheep / goats (5%), ferrous and non-ferrous metals (5%), crates / cartons / boxes / etc (5%). Using ABS deaths data to examine the deaths of people working and living on farms was limited to males whose occupation was recorded as ‘farmer and farm manager’ and ‘agricultural labourer and related worker’. There were 952 deaths over the period 1 January 1991 and 31 December 2000. The information provided a consistent series of cases over time. Areas where prevention should be directed included motor vehicle accidents; falls; agricultural machinery; other machinery; firearms; poisoning; and drowning. Using any one of the datasets alone to examine people injured on farms not only underestimates the number of people injured, but also misses particular types of agents involved in farm injuries. Each of the datasets used in this Thesis provides a different perspective of farm injury in NSW. By examining the information together, there are a number of areas which are consistently represented in each dataset such as falls and agricultural machinery. While no one dataset provided all the information that would be useful for the prevention of injuries, the available information does provide direction for the development of prevention strategies. The overall weakness of the information provided is that it misses a number of risk factors that contribute to farm injuries such as fatigue and training. The lack of appropriate denominator information also makes it difficult to directly compare the datasets and estimate the size of the problem. There are a number of additional coding categories that could be included in each dataset that would provide a better understanding of the different groups at risk of sustaining an injury on a farm or during agricultural work. These coding categories include activity at time of injury, admission to hospital, and occupation. An example of the use of data to determine the effectiveness of a farm injury prevention program is the ‘NSW Rollover Protective Structure (ROPS) Rebate Scheme’ evaluation. Tractor rollover deaths have been identified as an issue for prevention by Farmsafe Australia; however, such deaths were not identified in any of the datasets used in this Thesis due to coding limitations in the ABS data. In this Thesis information about the evaluation of the ‘NSW ROPS Rebate Scheme’ is presented. The scheme was successful in fitting 10,449 ROPS to tractors and the following lessons were learnt: when providing a rebate, the administration (i.e. sending the cheque) needs to be done well; advertising is important and should be co-ordinated, increase the awareness of the risk(s) the intervention is aiming to prevent and effectiveness of subsequent solution (s); the program should ensure there is an increased awareness of the outcome the intervention is aiming to prevent; if regulation is part of the program, enforcement needs to undertaken; and should address any barriers to uptake. The information provided in this Thesis highlights the substantial burden that farm injury places on the agricultural and rural sector of NSW. While there is no one data source that can describe the circumstances and the burden of farm injuries, the currently available datasets do provide an insight into the circumstances of farm injuries and the burden these injuries place on health, Workers’ Compensation, agricultural industries and farming families.

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (leaves 88-109).

Univ., Diss.--Frankfurt (Main), 2005. / Literaturverz. S. 317 - 349.

Thesis (Ph. D.)--University of California, San Diego, 2008. / Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 330-339).

Published also as Thesis (Ph. D.)--Columbia University. / Bibliography: p. 254-266.