The Snowman: a model of injuries and near-misses for the prevention of sharps injuries
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2010/11/01
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Description:Background: Sharps injuries (SI) and other blood/body fluid exposures (BBFE) present bloodborne pathogen risks for home healthcare (HHC) workers. While SI and BBFE are sufficiently frequent in HHC to be serious public health concerns, even moderately large surveys can still have insufficient power to identify risk factors. In this study, a new conceptual model for using near-misses for SI and BBFE was developed and its utility in statistical analyses of SI and BBFE risk factors was evaluated. Methods: A survey of HHC nurses (n = 787) and aides (n = 282) gathered data on the numbers of SI, BBFE, and near-misses in the past year. Questions focused on the circumstances leading up to the SI, BBFE, and near-misses. After evaluating the hypothesis that near-misses and events lie along the same causal pathway, we combined these outcomes to estimate their association with an important risk factor: employment status. Results: There were similar frequencies of risk factors for the events SI, BBFE, and their near-misses, suggesting that they may share common causal pathways. Combined data on events and near-misses confirmed our hypothesis that part-time and temporary HHC aides were at higher risk than full-timers. Conclusions: Analyses combining injuries and near-misses may be useful in risk factor investigations. [Description provided by NIOSH]
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ISSN:0271-3586
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Volume:53
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Issue:11
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NIOSHTIC Number:nn:20038411
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Citation:Am J Ind Med 2010 Nov; 53(11):1119-1127
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Contact Point Address:Hyun Kim ScD, Department of Community and Preventive Medicine, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box1057, New York, NY 10029
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Email:hyun.kim@mssm.edu
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Federal Fiscal Year:2011
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Performing Organization:University of Massachusetts - Lowell
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Peer Reviewed:True
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Start Date:20040901
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Source Full Name:American Journal of Industrial Medicine
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End Date:20230831
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Main Document Checksum:urn:sha-512:68675fcbb4ec642ee74dc6d2777b1f72d2556c116c43693da568a67dfc225e785cbbbea4221c7fdc2609f71248a2a4e0cb239ba393dcedacd4c2b9d16b8c181c
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