Improving agricultural injury surveillance: a comparison of incidence and type of injury event among three data sources

Medicolegal Implications of Fatalities Because of Entanglement in the Augers of Feed Mixer Wagons

ABSTRACT

Feed mixer or total mixed ration mixer wagons are powerful agricultural machines used to shred and mix silage with other ingredients and deliver it direct to the feeding troughs on livestock farms. Fatalities involving these feed mixers may occur when operators become trapped in the augers or, less frequently, are crushed by moving wagons. Death can occur very rapidly because of dismemberment, multiple lesions, or crushing. The aim of this review is to focus on the diagnostic evaluations that need to be performed to confirm that the death was accidental and to exclude a hypothesis of murder or suicide. Forensic investigations in such cases must involve the detailed analysis of the death scene and the mechanical characteristics of the machinery with an accurate postmortem and toxicological examination.

Using hospitalization data for injury surveillance in agriculture, forestry and fishing: a crosswalk between ICD10CM external cause of injury coding and The Occupational Injury and Illness Classification System

BACKGROUND

While statistics related to occupational injuries exist at state and national levels, there are notable difficulties with using these to understand non-fatal injuries trends in agriculture, forestry, and commercial fishing. This paper describes the development and testing of a crosswalk between ICD-10-CM external cause of injury codes (E-codes) for agriculture, forestry, and fishing (AFF) and the Occupational Injury and Illness Classification System (OIICS). By using this crosswalk, researchers can efficiently process hospitalization data and quickly assemble relevant cases of AFF injuries useful for epidemiological tracking.

METHODS

All 6810 ICD-10-CM E- codes were double-reviewed and tagged for AFF- relatedness. Those related to AFF were then coded into a crosswalk to OIICS. The crosswalk was tested on hospital data (inpatient, outpatient, and emergency department) from New York, Massachusetts, and Vermont using SAS9.3. Injury records were characterized by type of event, source of injury, and by general demographics using descriptive epidemiology.

RESULTS

Of the 6810 E-codes available in the ICD-10-CM scheme, 263 different E-codes were ultimately classified as 1 = true case, 2 = traumatic/acute and suspected AFF, or 3 = AFF and suspected traumatic/acute. The crosswalk mapping identified 9969 patient records either confirmed to be or suspected to be an AFF injury out of a total of 38,412,241 records in the datasets, combined. Of these, 963 were true cases of agricultural injury. The remaining 9006 were suspected AFF cases, where the E-code was not specific enough to assign certainty to the record's work-relatedness. For the true agricultural cases, the most frequent combinations presented were contact with agricultural/garden equipment (301), non-roadway incident involving off-road vehicle (222), and struck by cow or other bovine (150). For suspected agricultural cases, the majority (68.2%) represent animal-related injuries.

CONCLUSIONS

The crosswalk provides a reproducible, low-cost, rapid means to identify and code AFF injuries from hospital data. The use of this crosswalk is best suited to identifying true agricultural cases; however, capturing suspected cases of agriculture, forestry, and fishing injury also provides valuable data.

Agro-industrial accidents linked to length of service, operation site and confidence in employer adherence to safety rules

Background

The agriculture sector consistently ranks among the most hazardous occupational industries globally with high risk of job-related injuries, illnesses, disability, and death. In 2015, the agricultural fatal work injury rate in the United States was 22.8 per 100,000 full-time equivalent workers; seven times the all-worker fatal injury rate of 3.4 per 100,000 full-time equivalent workers. In this study we identified the factors that are associated with workplace accident and injuries at the Goldtree (SL) Limited Company - a private international agro-industrial palm kernel oil company operating in eastern Sierra Leone.

Methods

This is a descriptive research that made use of both qualitative and quantitative research techniques to collect and analyse agro-industrial occupation-related accident and injuries of workers attached to the Goldtree (SL) Limited Company, an international palm kernel oil producing and marketing company in Sierra Leone. We analyzed the responses of 100 workers at the Goldtree (SL) Limited Company that are related to their work safety, adherence to work safety guidelines as well as working habit.

Results

Thirty nine (39.0%) of the workers interviewed in this study said they had been involved in some forms of occupational accident; (33.3%) of those involved in some form of occupational-related accidents have been working in the company for 3–5 years, 22.0% have been working at the company for at least 2 years; 7.7% have been working for 6–8 years (X² = 9.88, p-value = 0.02).

Conclusion

Workers who have spent few years in the job, and those workers who have confidence that management is committed to addressing health and safety issues, believed that their working tools were in excellent condition, or agreed that they have the rights and responsibilities for an effective workplace health and safety system have decreased odds of experiencing occupational-related accidents or injury at the study site.

Characteristics of Agriculture Related Motor Vehicle Crashes in Rural New York State

Objective: The Centers for Disease Control and Prevention (CDC) data have shown that agriculture, forestry, and fishing as an occupational group have the third highest rate of work-related roadway crashes. Agriculture-related crashes have been explored in the Midwest and South; however, we know little about agriculture-related crashes in the Northeast, especially in New York.Methods: To better understand this, researchers obtained motor vehicle crash data from 2010 to 2012 from the New York State Department of Motor Vehicles (NYSDMV). These data were then filtered to agriculture-related cases by both vehicle registration type and vehicle body type.Results: We identified 203 agriculture-related vehicle crashes, involving 381 vehicles and 482 people. Of the agriculture incidents, 91.6% caused property damage, while 36.0% caused injury. The case fatality rate for roadway vehicle crashes was nearly five times as great (2.0/0.4 = 5.00) for agriculture versus non-agriculture crashes (p = 0.0003).Conclusion: Using these data as a supplement to the New York Center for Agricultural Medicine and Health's existing surveillance system provided information useful in setting priorities involving roadway safety.

Using multiple coding schemes for classification and coding of agricultural injury

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.

Establishing a publicly available national database of US news articles reporting agriculture-related injuries and fatalities

BACKGROUND

The AgInjuryNews system and dataset are a news report repository and information source for agricultural safety professionals, policymakers, journalists, and law enforcement officials.

METHODS

AgInjuryNews was designed as a primary storage and retrieval system that allows users to: identify agricultural injury/fatality events; identify injury agents and emerging issues; provide safety messages for media in anticipation of trends; and raise awareness and knowledge of agricultural injuries and prevention strategies. Data are primarily collected through Google Alerts and a digital media subscription service. Articles are screened, reviewed, coded, and entered into the system.

RESULTS

As of January 1, 2018, the system contained 3028 unique incidents. Of those, 650 involved youth, and 1807 were fatalities. The system also had registered 329 users from 39 countries.

CONCLUSIONS

AgInjuryNews combines injury reports into one dataset and may be the most current and comprehensive publicly available collection of news reports on agricultural injuries and deaths.

Supplemental surveillance: a review of 2015 and 2016 agricultural injury data from news reports on AgInjuryNews.org

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.

Data processing and case identification in an agricultural and logging morbidity surveillance study: Trends over time

BACKGROUND

Agriculture and logging are dangerous industries, and though data on fatal injury exists, less is known about non-fatal injury. Establishing a non-fatal injury surveillance system is a top priority. Pre-hospital care reports and hospitalization data were explored as a low-cost option for ongoing surveillance of occupational injury.

METHODS

Using pre-hospital care report free-text and location codes, along with hospital ICD-9-CM external cause of injury codes, we created a surveillance system that tracked farm and logging injuries.

RESULTS

In Maine and New Hampshire, 1585 injury events were identified (2008-2010). The incidence of injuries was 12.4/1000 for agricultural workers, compared to 10.4/1000 to 12.2/1000 for logging workers.

CONCLUSIONS

These estimates are consistent with other recent estimates. This system is limited to traumatic injury for which medical treatment is administered, and is limited by the accuracy of coding and spelling. This system has the potential to be both sustainable and low cost.

Non-fatal agricultural injury surveillance in the United States: A review of national-level survey-based systems

BACKGROUND

Currently, surveillance of non-fatal agricultural injuries in the U.S. mainly relies on national surveys, and to date, none of these surveys were formally reviewed. Our objective was to review and evaluate these survey-based systems, to identify critical gaps in them and provide recommendations to improve them.

METHODS

We used the updated Center for Disease Control and Prevention guidelines to describe each system and evaluate each system's attributes like simplicity, flexibility, data quality, timeliness, representativeness, etc.

RESULTS

Four adult and two youth national surveys collected data for non-fatal agricultural injuries in the U.S. The evaluation identified three major gaps: 1) insufficient data quality attributed to non-response, measurement errors, and underreporting; 2) untimeliness of data; and 3) lack of flexibility to integrate with other existing systems.

CONCLUSION

Improving data quality, timeliness and flexibility will provide reliable and valid injury estimates, and increase the usefulness of these surveys for surveillance and prevention of farm injuries.

Socio-environmental risk factors for medically-attended agricultural injuries in Wisconsin dairy farmers

BACKGROUND

Accidents are common in the agricultural industry, particularly among dairy farmers. How said farmers get hurt is well established, but far less is known about how distal, socio-environmental factors influence injuries. This study examined associations between medically-attended agricultural injuries and: (1) personal sociodemographic characteristics, and (2) farm environment features and general safety practices.

METHODS

A cross-sectional survey was implemented with linked data from electronic health records on prior agricultural injuries that occurred between 01/01/2002-12/31/2015. The sample included adult dairy producers who resided in north-central Wisconsin (USA) and were medically-homed to the Marshfield Clinic Health System. Multiple logistic regression was used to analyze associations between socio-environmental characteristics and agricultural injuries.

RESULTS

There were 620 dairy farmers in the analytical sample, with 50 medically-attended agricultural injuries observed during the 14-year study time period (5.7 injuries per 1000 dairy farmers per year). In the multivariable model, the odds of agricultural injury were significantly greater among farmers who have private individually-purchased health insurance (OR=4.25; 95% CI: 1.31, 13.84), do not live at their dairy operation (OR=2.91; CI: 1.27, 6.67), and do not provide safety training to their workers (OR=4.27; CI: 1.00, 18.21).

CONCLUSIONS

Dairy farmers in this analysis who did not live at their dairy operation, did not provide safety training to all their workers, or had individually-purchased health insurance were more apt to get injured, but more research is needed to confirm these findings in prospectively designed studies. How these factors can be directly addressed or otherwise used to better focus farm injury prevention initiatives should also be explored.

Work related injury among Saudi Star Agro Industry workers in Gambella region, Ethiopia; a cross-sectional study

Background

Work injury is an important cause of morbidity and mortality, much of these work injuries burden can be found in industry required heavy manual work such as, agriculture and fishers. Hence; agriculture is consistently cited as one of the most hazardous industry in the world. The objective of this study isto assess the magnitude and associated factors of work related injury among Saudi Star Agro Industry workers in Gambella region, South West Ethiopia.

Methods

An institutional based cross-sectional study design was conducted on Saudi Star Agro Industry located in Gambella region, from February - June 2014 on 449 randomly selected workers who arestratifiedby working department. Anobservation checklist, factory clinical records and a structured interview questioner were used as a data collection tools.

Result

The prevalence of work related injury was 36.7%. Marital status [AOR;1.69, 95%; CI;(1.1–2.7)], service year [AOR;1.9,95%; CI;(1.17–3.1)], working more than 48 h per week [AOR;9.87, 95%; CI;(5.95–16.28)],safety training [AOR;3.38, 95%;CI;1.14–9.98)], regular health checkup [AOR; 12.29, 95%; CI (9–51.35)] and usage of personal protective equipment [AOR; 2.36, 95%; CI; (1.06–5.25)] were significant factors for the occurrence of work related injury.

Conclusion

The prevalence of work related injury was high. Working hours, safety training and regular health checkup increases the risk of work related injury.

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

OBJECTIVE

Agriculture and logging rank among industries with the highest rates of occupational fatality and injury. Establishing a nonfatal injury surveillance system is a top priority in the National Occupational Research Agenda. Sources of data such as patient care reports (PCRs) and hospitalization data have recently transitioned to electronic databases.

METHODS

Using narrative and location codes from PCRs, along with International Classification of Diseases, 9th Revision, external cause of injury codes (E-codes) in hospital data, researchers are designing a surveillance system to track farm and logging injury.

RESULTS

A total of 357 true agricultural or logging cases were identified.

CONCLUSIONS

These data indicate that it is possible to identify agricultural and logging injury events in PCR and hospital data. Multiple data sources increase catchment; nevertheless, limitations in methods of identification of agricultural and logging injury contribute to the likely undercount of injury events.

Hospitalized head and spine injuries on Saskatchewan farms

INTRODUCTION

With over 44,000 individual farms, farm dwellers account for 11% of the population of Saskatchewan. There is limited data on brain and spine injuries acquired on farms. The objective of this study was to evaluate the epidemiology of head and spine injuries on Saskatchewan farms to assist the development of injury prevention initiatives.

METHODS

Using the Canadian Centre for Agricultural Health and Safety's Saskatchewan Farm Injury Surveillance Database, farm-related head and spine injuries hospitalized > 24 hours were examined (1990-2007). We collected information regarding the type and mechanism of injury as well as the geographic location of both the injury and treatment.

RESULTS

The database captured 390 brain injuries and 228 spine injuries, including 16 spinal cord injuries. The majority of patients were male (73.3% of head injuries and 84.2% of spine injuries). The highest risk age groups were 50-59 years, with 24.1% of the spine injuries, and 40-49 years, with 19.2% of the head injuries. The most common causes of injury were falls and/or machinery-related. The average annual incidence of farm-related spine and head injury were 10.8 and 17.6 per 100,000 farm population, respectively. All patients included in this study were hospitalized for over 24 hours, with 44.7% of spine injuries spending over one week in hospital, and 20% of head injuries spending over three days in hospital.

CONCLUSIONS

Injury prevention initiatives should be targeted towards males aged 40-59 years residing in the southern areas of the province, with increased awareness towards the dangers of falls and operating tractors.

Exploring the feasibility of using electronic health records in the surveillance of fetal alcohol syndrome

BACKGROUND

Explore the use of electronic health records (EHRs) in fetal alcohol syndrome (FAS) surveillance systems.

METHODS

Using EHRs we identified diagnoses and anthropometric measurements related to the FAS criteria developed by the Fetal Alcohol Syndrome Surveillance Network (FASSNet) among children aged 0 to 12 years.

RESULTS

There were 143,393 distinct children aged between 0 and 12 years enrolled in Kaiser Permanente, Georgia, during the study period. Based on diagnoses and anthropometric measurements, 20,101 children met at least one criterion of interest, and when grouped into combinations of different criteria there were 2285 who met GROWTH+CNS criteria, 76 children who met GROWTH+FACE criteria, 107 children who met CNS+FACE criteria, and 93 children who met GROWTH+CNS+FACE criteria. The prevalence of FAS as defined by FASSNet is 1.92 per 1000 children. We linked 17,084 (85.0%) children to their mothers in the health plan; only 3% of mothers of children in the GROWTH+CNS+FACE group had an indication of alcohol or drugs use, but they had the highest rate of depression (39%).

CONCLUSION

Data of utility in identification of FAS are readily available in EHRs and may serve as a basis for intervention with at-risk children and in planning of future FAS surveillance programs.

Overview of immigrant worker occupational health and safety for the agriculture, forestry, and fishing (AgFF) sector in the southeastern United States

BACKGROUND

Manual labor in the Agriculture, Forestry, and Fishing (AgFF) Sector is provided primarily by immigrant workers. Limited information is available that documents the demographic characteristics of these manual workers, the occupational illnesses, injuries and fatalities they experience; or the risk factors to which they are exposed.

METHODS

A working conference of experts on occupational health in the AgFF Sector was held to address information limitations. This paper provides an overview of the conference. Other reports address organization of work, health outcomes, healthcare access, and safety policy.

CONTENTS

This report addresses how best to define the population and the AgFF Sector, occupational exposures for the sector, data limitations, characteristics of immigrant workers, reasons for concern for immigrant workers in the AgFF Sector, regulations, a conceptual model for occupational health, and directions for research and intervention.

Female farmworkers' health during pregnancy: health care providers' perspectives

Pregnant farmworkers and their fetuses are at increased risk of negative health outcomes due to environmental and occupational factors at their workplaces. Health care providers who serve farm communities can positively affect workers' health through the informed care they deliver. Yet, interviews with rural health care providers reveal limited knowledge about agricultural work or occupational and environmental health risks during pregnancy. Professional associations, government organizations, academic institutions, and practice settings must renew their efforts to ensure that environmental and occupational health education, especially as it relates to women and their children, is incorporated into academic and practice environments.

A correction factor for estimating statewide agricultural injuries from ambulance reports

PURPOSE

Agriculture ranks as one of the most hazardous industries in the nation. Agricultural injury surveillance is critical to identifying and reducing major injury hazards. Currently, there is no comprehensive system of identifying and characterizing fatal and serious non-fatal agricultural injuries. Researchers sought to calculate a multiplier for estimating the number of agricultural injury cases based on the number of times the farm box indicator was checked on the ambulance report.

METHODS

Farm injuries from 2007 that used ambulance transport were ascertained for 10 New York counties using two methods: (1) ambulance reports including hand-entered free text; and (2) community surveillance. The resulting multiplier that was developed from contrasting these two methods was then applied to the statewide Emergency Medical Services database to estimate the total number of agricultural injuries for New York state.

RESULTS

There were 25,735 unique ambulance runs due to injuries in the 10 counties in 2007. Among these, the farm box was checked a total of 90 times. Of these 90, 63 (70%) were determined to be agricultural. Among injury runs where the farm box was not checked, an additional 59 cases were identified from the free text. Among these 122 cases (63 + 59), four were duplicates. Twenty-four additional unique cases were identified from the community surveillance for a total of 142. This yielded a multiplier of 142/90 = 1.578 for estimating all agricultural injuries from the farm box indicator. Sensitivity and specificity of the ambulance report method were 53.4% and 99.9%, respectively.

CONCLUSIONS

This method provides a cost-effective way to estimate the total number of agricultural injuries for the state. However, it would not eliminate the more labor intensive methods that are required to identify of the actual individual case records. Incorporating an independent source of case ascertainment (community surveillance) increased the multiplier by 17%.