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Analysis of Workers' Compensation Cl...
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Ramaswamy, Sai Kumar.
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Analysis of Workers' Compensation Claims Data for Improving Safety Outcomes in Agribusiness Industries.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Analysis of Workers' Compensation Claims Data for Improving Safety Outcomes in Agribusiness Industries./
作者:
Ramaswamy, Sai Kumar.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:
149 p.
附註:
Source: Dissertations Abstracts International, Volume: 79-01, Section: B.
Contained By:
Dissertations Abstracts International79-01B.
標題:
Occupational health. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10222131
ISBN:
9781369877137
Analysis of Workers' Compensation Claims Data for Improving Safety Outcomes in Agribusiness Industries.
Ramaswamy, Sai Kumar.
Analysis of Workers' Compensation Claims Data for Improving Safety Outcomes in Agribusiness Industries.
- Ann Arbor : ProQuest Dissertations & Theses, 2017 - 149 p.
Source: Dissertations Abstracts International, Volume: 79-01, Section: B.
Thesis (Ph.D.)--Iowa State University, 2017.
This item must not be sold to any third party vendors.
Occupational injuries continue to be a major issue for non-farm agricultural workplaces such as commercial grain elevators and ethanol plants. For preventing these injuries and improving workplace safety outcomes requires learning from past incidents, and identify the most significant causes and implement targeted prevention strategies. However, obtaining detailed records of past incidents is a challenge acknowledged by investigators across several industrial sectors including agribusiness. Previous researchers suggest workers' compensation claims as an excellent data source to address the existing informational gaps about safety incidents and injuries in the workplace. In this study, workers' compensation claims obtained from a leading private insurance company were investigated using statistical techniques such as chi-square tests, regression analysis, and data mining techniques such as decision trees. The study objective was to analyze these claims, identify injury causes, risks, and problem areas so supervisors and safety professionals can make decisions needed to improve safety outcomes in the workplace. The findings of this study are documented in three separate manuscripts. Since safety incidents that cause injuries and fatalities have a widespread impact, therefore mitigating these incidents using a proactive data-driven approach rather than just compliance can benefit the worker, the organization, and society-at-large.
ISBN: 9781369877137Subjects--Topical Terms:
1547694
Occupational health.
Analysis of Workers' Compensation Claims Data for Improving Safety Outcomes in Agribusiness Industries.
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Occupational injuries continue to be a major issue for non-farm agricultural workplaces such as commercial grain elevators and ethanol plants. For preventing these injuries and improving workplace safety outcomes requires learning from past incidents, and identify the most significant causes and implement targeted prevention strategies. However, obtaining detailed records of past incidents is a challenge acknowledged by investigators across several industrial sectors including agribusiness. Previous researchers suggest workers' compensation claims as an excellent data source to address the existing informational gaps about safety incidents and injuries in the workplace. In this study, workers' compensation claims obtained from a leading private insurance company were investigated using statistical techniques such as chi-square tests, regression analysis, and data mining techniques such as decision trees. The study objective was to analyze these claims, identify injury causes, risks, and problem areas so supervisors and safety professionals can make decisions needed to improve safety outcomes in the workplace. The findings of this study are documented in three separate manuscripts. Since safety incidents that cause injuries and fatalities have a widespread impact, therefore mitigating these incidents using a proactive data-driven approach rather than just compliance can benefit the worker, the organization, and society-at-large.
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