Developing Surveillance Methodology for Agricultural and Logging Injury in New Hampshire Using Electronic Administrative Data Sets

Scott, Erika; Hirabayashi, Liane; Krupa, Nicole; Sorensen, Julie A.; Jenkins, Paul

doi:10.1097/jom.0000000000000482

Cited by 8 publications

(8 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Future iterations of the WINS platform will begin integrating other data sources from the state of Wisconsin [e.g., ambulance runs based on models outlined by Scott et al ( 24 , 25 )] to capture more injuries that may have been treated outside of MCHS or not covered by SHP insurance. In addition, chart reviews will be conducted on a sample of farm-related injuries in the out-farm group, and the WINS source population will be expanded by including other healthcare systems that serve children and adolescents beyond north-central regions of Wisconsin.…”

Section: Discussionmentioning

confidence: 99%

“…Efforts were also made to identify recreational activities that took place in the farm location (e.g., riding horses or ATVs). Medically-attended farm-related injuries were ascertained based on adaptations of injury surveillance models outlined by Landsteiner et al ( 23 ) and Scott et al ( 24 , 25 ). Injury details were extracted from medical diagnoses observed during emergency, inpatient, urgent care, or outpatient encounters in the MCHS electronic data repository.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Regional surveillance of medically-attended farm-related injuries in children and adolescents

VanWormer

Berg

Burke

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

PurposeDue to numerous environmental hazards such as heavy machinery and large livestock, youth who live and work on farms are at high risk of injury, disability, and death. This study described a regional surveillance system for monitoring farm-related injuries in children and adolescents. As the risk of farm-related injuries are not exclusive to farm residents, trends in farm-related injuries over the previous 5 years were reported and compared between children/adolescents who did and did not live on farms in north-central Wisconsin.MethodsA retrospective cohort of child and adolescent patients of the Marshfield Clinic Health System was assembled. Incident farm-related injuries, including from agricultural work or other activities in a farm environment, were extracted from medical records from 2017 through 2021. Generalized linear models were created to compare age- and sex-adjusted farm-related injury rates by year.ResultsThere were 4,730 (5%) in-farm and 93,420 (95%) out-farm children and adolescents in the cohort. There were 65 incident farm-related injury cases in the in-farm group and 412 in the out-farm group. The annual incidence rate of farm-related injuries was higher in the in-farm group, but changes during the 5-year timeframe were not significant in either group. In the in-farm group, rates ranged from a high of 61.8 [95% confidence interval (CI): 38.3, 94.5] incident farm-related injuries per 10,000 children/adolescents in 2017 to a low of 28.2 (13.5, 51.9) injuries per 10,000 children/adolescents in 2018. In the out-farm group, rates ranged from 10.7 (8.3, 13.6) to 16.8 (13.7, 20.5) incident farm-related injuries per 10,000 children/adolescents per year between 2017 and 2021. The in-farm group had a higher proportion of injured males and heavy machinery injuries, while the out-farm group had more all-terrain vehicle injuries and pesticide poisonings.ConclusionFarm residency remains hazardous for children and adolescents, as injury rates were three times higher in the in-farm group and remained stable over 5 years. All-terrain vehicle injuries were high in both groups, and should be a priority in rural safety interventions. With additional adaptations to other states, this surveillance model could be scaled across other healthcare systems.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Regional surveillance of medically-attended farm-related injuries in children and adolescents

VanWormer

Berg

Burke

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…Unstructured data analysis is reported as challenging in EHR datasets [31] and claims databases [34], which is due to processing textual data [34] and coding the data to recognised coding formats such as the ICD, leading to potentially lower quality analysis or the need to exclude records [31,35,39]. A study found that many variables that were available for analysis, such as medication lists, education and income that were excluded from the study due to inabilities to process unstructured data [31].…”

Section: Sources Of Data For Predicting Outcomes To Wmsdsmentioning

confidence: 99%

“…A study found that many variables that were available for analysis, such as medication lists, education and income that were excluded from the study due to inabilities to process unstructured data [31]. Unstructured data also has its benefits, such as being able to capture sequence of events that can be missed from structured data [35].…”

Section: Sources Of Data For Predicting Outcomes To Wmsdsmentioning

confidence: 99%

Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review

Wassell,

Vitiello,

Butler-Henderson

et al. 2024

J Occup Rehabil

View full text Add to dashboard Cite

Purpose Through electronic health records (EHRs), musculoskeletal (MSK) therapists such as chiropractors and physical therapists, as well as occupational medicine physicians could collect data on many variables that can be traditionally challenging to collect in managing work-related musculoskeletal disorders (WMSDs). The review’s objectives were to explore the extent of research using EHRs in predicting outcomes of WMSDs by MSK therapists. Method A systematic search was conducted in Medline, PubMed, CINAHL, and Embase. Grey literature was searched. 2156 unique papers were retrieved, of which 38 were included. Three themes were explored, the use of EHRs to predict outcomes to WMSDs, data sources for predicting outcomes to WMSDs, and adoption of standardised information for managing WMSDs. Results Predicting outcomes of all MSK disorders using EHRs has been researched in 6 studies, with only 3 focusing on MSK therapists and 4 addressing WMSDs. Similar to all secondary data source research, the challenges include data quality, missing data and unstructured data. There is not yet a standardised or minimum set of data that has been defined for MSK therapists to collect when managing WMSD. Further work based on existing frameworks is required to reduce the documentation burden and increase usability. Conclusion The review outlines the limited research on using EHRs to predict outcomes of WMSDs. It highlights the need for EHR design to address data quality issues and develop a standardised data set in occupational healthcare that includes known factors that potentially predict outcomes to help regulators, research efforts, and practitioners make better informed clinical decisions.

show abstract

“…National surveillance systems that apply uniform definitions and coding schemes provide value to stakeholders and facilitate collaborations between researchers nationally and internationally. 12,[14][15][16][17] Yet, gaps remain in national statistics, and support is needed to supplement current national surveillance to be more inclusive and comprehensive, recognizing the whole spectrum of agriculturerelated injury and fatality cases.…”

Section: Implications and Recommendationsmentioning

confidence: 99%

What about the Rest of Them? Fatal Injuries Related to Production Agriculture Not Captured by the Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries (CFOI)

Weichelt

Scott

Burke

et al. 2021

Journal of Agromedicine

View full text Add to dashboard Cite

Surveillance of injuries in production agriculture is necessary to inform stakeholders about workplace hazards and risks in order to improve and advance injury prevention policies and practices for this dangerous industry. The most comprehensive fatal injury surveillance effort currently in the United States is the Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries (CFOI), which covers occupational fatalities in all U.S. industries, including production agriculture. However, this surveillance does not include many categories of fatalities that occur during agricultural work or on production agriculture worksites. To better capture the human cost of production agriculture, the authors of this paper call for the collection of additional data with a broader scope that supplements, not replaces, the current CFOI. This paper describes challenges in surveillance, highlights key procedural gaps, and offers recommendations for advancing national surveillance of fatal traumatic injuries associated with production agriculture.

show abstract

Developing Surveillance Methodology for Agricultural and Logging Injury in New Hampshire Using Electronic Administrative Data Sets

Cited by 8 publications

References 31 publications

Regional surveillance of medically-attended farm-related injuries in children and adolescents

Regional surveillance of medically-attended farm-related injuries in children and adolescents

Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review

What about the Rest of Them? Fatal Injuries Related to Production Agriculture Not Captured by the Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries (CFOI)

Contact Info

Product

Resources

About