scholarly journals Work-Related Injury Surveillance in Vietnam: A National Reporting System Model

2013 ◽  
Vol 103 (11) ◽  
pp. 1989-1996 ◽  
Author(s):  
Helen Marucci-Wellman ◽  
David H. Wegman ◽  
Tom B. Leamon ◽  
Ta Thi Tuyet Binh ◽  
Nguyen Bich Diep ◽  
...  
Author(s):  
Gary S. Sorock ◽  
Gordon S. Smith ◽  
Gordon R. Reeve ◽  
John Dement ◽  
Nancy Stout ◽  
...  

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i3-i8
Author(s):  
Ashley M Bush ◽  
Terry L Bunn ◽  
Madison Liford

IntroductionEmergency department (ED) visit discharge data are a less explored population-based data source used to identify work-related injuries. When using discharge data, work-relatedness is often determined by the expected payer of workers’ compensation (WC). In October 2015, healthcare discharge data coding systems transitioned to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). ICD-10-CM’s structure offers potential new work-related codes to enhance work-related injury surveillance. This study identified work-related ED visits using relevant ICD-10-CM work-related injury codes. Cases identified using this method were compared with those identified using the WC expected payer approach.MethodsState ED visit discharge data (2016–2019) were analysed using the CDC’s discharge data surveillance definition. Injuries were identified using a diagnosis code or an external cause-of-injury code in any field. Injuries were assessed by mechanism and expected payer. Literature searches and manual review of ICD-10-CM codes were conducted to identify possible work-related injury codes. Descriptive statistics were performed and assessed by expected payer.ResultsWC was billed for 87 361 injury ED visits from 2016 to 2019. Falls were the most frequent injury mechanism. The 246 ICD-10-CM work-related codes identified 36% more work-related ED injury visits than using WC as the expected payer alone.ConclusionThis study identified potential ICD-10-CM codes to expand occupational injury surveillance using discharge data beyond the traditional WC expected payer approach. Further studies are needed to validate the work-related injury codes and support the development of a work-related injury surveillance case definition.


Author(s):  
Caroline Gillespie ◽  
Kirsten Vallmuur ◽  
Narelle Haworth ◽  
Darren Wishart

1998 ◽  
Vol 3 (4) ◽  
pp. 6-6
Author(s):  
Marc T. Taylor

Abstract This article discusses two important cases that involve the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides). First, in Vargas v Industrial Com’n of Arizona, a claimant had a pre-existing non–work-related injury to his right knee as well as a work-related injury, and the issue was apportionment of the pre-existing injury. The court held that, under Arizona's statute, the impairment from the pre-existing injury should be subtracted from the current work-related impairment. In the second case, Colorado courts addressed the issue of apportionment in a workers’ compensation claim in which the pre-existing injury was asymptomatic at the time of the work-related injury (Askey v Industrial Claim Appeals Office). In this case, the court held that the worker's benefits should not be reduced to account for an asymptomatic pre-existing condition that could not be rated accurately using the AMA Guides. The AMA Guides bases impairment ratings on anatomic or physiologic loss of function, and if an examinee presents with two or more sequential injuries and calculable impairments, the AMA Guides can be used to apportion between pre-existing and subsequent impairments. Courts often use the AMA Guides to decide statutorily determined benefits and are subject to interpretation by courts and administrative bodies whose interpretations may vary from state to state.


2011 ◽  
Vol 1 (2) ◽  
pp. 13-17
Author(s):  
Sanjith S ◽  
◽  
Ramesh Kumar P ◽  

2017 ◽  
Vol 53 (3) ◽  
pp. 325-325
Author(s):  
Wan-Ju Cheng ◽  
Ming-Chyi Huang ◽  
Yawen Cheng ◽  
Chun-Hsin Chen ◽  
Chiou-Jung Chen

Work ◽  
2019 ◽  
Vol 61 (4) ◽  
pp. 537-549 ◽  
Author(s):  
Rebecca E. Gewurtz ◽  
Stephanie Premji ◽  
D. Linn Holness

Sign in / Sign up

Export Citation Format

Share Document