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Background: Agricultural employment is one of the most dangerous occupations in the United States. Workers' compensation coverage requirements for agricultural work vary from state to state, and experience modifier rates (E-mods) affecting insurance premiums sometimes vary drastically across state lines and according to claim severities and farm sizes. We proposed to develop an interactive software application that would educate farmers on the impact of employee time loss on annual E-mod factor change specific to their geographic location and farm size. Methods: We conducted a comparative analysis of workers' compensation formulations, including E-mods among Upper Midwestern states. We performed sensitivity analysis of the formulas to claim amount and payroll to highlight differences related to claim severity and to farm size. Results: The state to state variation and remarkable complexity of these formulas was confirmed. E-Mod factors are shown to increase substantially across states with both claim size and payroll, though are found to be similar across Wisconsin and Minnesota which were examined in detail. Conclusions: The findings confirm that creating a nationally applicable interactive educational software tool for farmers and ranchers to view hypothetical rate changes by inputting on-farm injury scenarios represents a significant challenge and that educational outreach coupled with the use of commercial software, especially as less costly options become available, may serve the role of minimizing misunderstandings by current producers as may other informational sources. [ABSTRACT FROM AUTHOR]

Background: Agricultural safety and health researchers have used a variety of classification and coding schemes to identify and categorize injury, illness, and disease associated with agricultural hazards. This paper demonstrates how the Farm and Agricultural Injury Classification (FAIC) and Occupational Injury and Illness Classification System (OIICS) coding schemes can be used in tandem for all agricultural injuries. Methods: Specific cases from the AgInjuryNews.org database were selected to illustrate how the FAIC and OIICS codes can be applied to agricultural injury, and to illustrate limitations that still exist with each coding scheme. Results: Using the FAIC and OIICS together provided a clearer picture of an injury incident by combining more explicit occupational and non‐occupational exposures with incident type details in a single table. Conclusions: Both FAIC and OIICS coding schemes depend on sufficient information being available from injury reports. This paper concluded with suggestions for improving coding of agricultural injury. [ABSTRACT FROM AUTHOR]

Background: Injury data and reports provide valuable information for both public and private organizations to guide programming, policy, and prevention, but in the increasingly complex and dangerous industry of US agriculture, the injury surveillance needed to produce this data is lacking. To address the gap, AgInjuryNews was established in 2015. The system includes fatal and nonfatal injury cases derived from publicly available reports, including occupational and nonoccupational injuries, occurring in the agricultural, forestry, and fishing (AFF) industry. Objective: The study aimed to develop a stakeholder-engaged redesign of the interactive, up-to-date, and publicly available dataset of US AFF injury and fatality reports. Methods: Instructor-led heuristic evaluations within a 15-student undergraduate course, data from 8 student participants of laboratory-based usability testing and 2016 and 2017 AgInjuryNews-registered user surveys, coupled with input from the National Steering Committee informed the development priorities for 2018. An interdisciplinary team employed an agile methodology of 2-week sprints developing in ASP.NET and Structured Query Language to deliver an intuitive frontend and a flexible, yet structured, backend, including a case report input form for capturing more than 50 data points on each injury report. Results: AgInjuryNews produced 17,714 page views from 43 countries in 2018 captured via Google Analytics, whereas 623 injury reports were coded and loaded, totaling more than 31,000 data points. Newly designed features include customizable email alerts, an interactive map, and expanded search and filter options. User groups such as the Bureau of Labor Statistics and the Agricultural Safety and Health Council of America have endorsed the system within their networks. News media have cited or referenced the system in national outlets such as the New York Times, Politico, and the Washington Post. Conclusions: The new system's features, functions, and improved data granularity have sparked innovative lines of research and increased collaborative interest domestically and abroad. It is anticipated that this nontraditional sentinel surveillance system and its dataset will continue to serve many purposes for public and private agricultural safety and health stakeholders in the years to come. [ABSTRACT FROM AUTHOR]

Background: Physicians and patient-facing caregivers have increasingly used mobile health (mHealth) technologies in the past several years, accelerating during the COVID-19 pandemic. However, barriers and feedback surrounding adoption remain relatively understudied and varied across health systems, particularly in rural areas., Objective: This study aims to identify provider adoption, attitudes, and barriers toward mHealth in a large, multisite, rural US health care system. We investigated (1) mHealth apps that providers use for their own benefit and (2) mHealth apps that a provider uses in conjunction with a patient., Methods: We surveyed all patient-seeing providers within the Marshfield Clinic Health System with a brief, 16-item, web-based survey assessing attitudes toward mHealth, adoption of these technologies, and perceived barriers faced by providers, their peers, and the institution. Survey results were summarized via descriptive statistics, with log-binomial regression and accompanying pairwise analyses, using Kruskal-Wallis and Jonckheere-Terpstra tests for significance, respectively. Respondents were grouped by reported clinical role and specialty., Results: We received a 38% (n/N=916/2410) response rate, with 60.7% (n=556) of those sufficiently complete for analyses. Roughly 54.1% (n=301) of respondents reported mHealth use, primarily around decision-making and supplemental information, with use differing based on provider role and years of experience. Self-reported barriers to using mHealth included a lack of knowledge and time to study mHealth technologies. Providers also reported concerns about patients' internet access and the complexity of mHealth apps to adequately use mHealth technologies. Providers believed the health system's barriers were largely privacy, confidentiality, and legal review concerns., Conclusions: These findings echo similar studies in other health systems, surrounding providers' lack of time and concerns over privacy and confidentiality of patient data. Providers emphasized concerns over the complexity of these technologies for their patients and concerns over patients' internet access to fully use mHealth in their delivery of care., (©Bryan P Weichelt, Rick Burke, Burney Kieke, Matt Pilz, Neel Shimpi. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 24.06.2024.)

Background: Agriculture, forestry, fishing and hunting industry is the most hazardous occupational sector in the USA. Even with this level of occupational risk, several national and state-level occupational injury surveillance programmes have been eliminated, leaving regional efforts to analyse multiple sources and compile data on agricultural injuries and fatalities. No up-to-date centralised national database for agricultural injuries/fatalities in the USA currently exists., Objective: Using the public data on AgInjuryNews.org, this study considered a wide range of variables to examine fatalities and injuries of the industry in 2015 and 2016. The results reported in this paper sought to explore and understand common data elements of US news reports., Methods: As of 5 April 2017, more than 3000 articles across 36 years were contained in the dataset. We selected 2 years to review, 2015 and 2016, which represented the most complete years to date; 2015 was the first year in which systematic collection was initiated by the AgInjuryNews.org team. Data were coded based on the Occupational Injury and Illness Classification System source and event/exposure types., Results: A total of 1345 victims were involved in 1044 incidents. Leading sources of injuries were vehicles and machinery, and the most common event/exposure type was transportation., Conclusions: This study demonstrated that data from AgInjuryNew.org is consistent with previous literature, and it can supply up-to-date data as an open-source surveillance supplement, disseminated for health and safety stakeholders., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)