Illness Classification System Research Articles

Orchard Sports Injury and Illness Classification System (OSIICS) Version 15

BackgroundSports medicine (injury and illnesses) requires distinct coding systems because the International Classification of Diseases is insufficient for sports medicine coding. The Orchard Sports Injury and Illness Classification System (OSIICS) is one of two sports medicine coding systems recommended by the International Olympic Committee. Regular updates of coding systems are required. MethodsFor Version 15, updates for mental health conditions in athletes, sports cardiology, concussion sub-types, infectious diseases, and skin and eye conditions were considered particularly important. ResultsRecommended codes were added from a recent International Olympic Committee consensus statement on mental health conditions in athletes. Two landmark sports cardiology papers were used to update a more comprehensive list of sports cardiology codes. Rugby union protocols on head injury assessment were used to create additional concussion codes. ConclusionIt is planned that OSIICS Version 15 will be translated into multiple new languages in a timely fashion to facilitate international accessibility. The large number of recently published sport-specific and discipline-specific consensus statements on athlete surveillance warrant regular updating of OSIICS.

Musculoskeletal injuries profile of patients applying to a sports medicine outpatient clinic

Background/Aim: Sports injuries represent a significant public health concern, and their prevalence is on the rise due to the growing global population and increased participation in amateur and professional sports. Epidemiological studies on sports injuries are crucial in identifying priority areas for injury prevention efforts. While there is a wealth of research on musculoskeletal injuries specific to various sports, there is a scarcity of epidemiological studies focusing on patients seeking care at sports medicine outpatient clinics. This study aims to define and categorize the diagnoses of patients presenting to a sports medicine outpatient clinic for musculoskeletal injuries. Methods: This retrospective cohort study included all patient visits for musculoskeletal injuries at the sports medicine outpatient clinic between 1 July 2022 and 30 June 2023. Patients with complaints other than musculoskeletal injuries and those lacking sufficient data (diagnosis or injury type) in the data recording system were excluded. Data recorded for each participant included age, sex, symptoms, injured body region, and injury type. Diagnoses were categorized using the Orchard Sports Injury and Illness Classification System (OSIICS) v.13. Descriptive analyses provided a detailed overview of reported injuries, including counts and proportions within specific injury categories. Categorical variables are presented as ‘n’ and (%), while continuous variables are expressed as medians with interquartile ranges (IQRs). Results: Data from 1,203 patients (395 females and 808 males) were analyzed, with a mean age of 24 (2.2) years. A total of 1393 injuries were documented, with the knee being the most commonly injured body region (n=398, 30.7%). Among the OSIICS v.13 injury categories, muscle/tendon injuries constituted 33.7% (n=466) of all injuries, followed by cartilage/synovium/bursa injuries (n=432, 31.2%). Conclusion: This study revealed that the knee was the most frequently injured body region among patients seeking care at the sports medicine clinic for musculoskeletal injuries. Muscle/tendon injuries were the predominant type of injury observed.

Incidence, characteristics and cost of head, neck and dental injuries in non-professional football (soccer) using 3 years of sports injury insurance data.

This descriptive epidemiological study aimed to quantify the incidence, characteristics and costs of head, neck and dental injuries in non-professional football players. Injury data were coded (using Orchard Sports Injury and Illness Classification System) from a de-identified insurance database containing three seasons (2018-2020) of data. Cost data included direct and indirect costs presented by type of injury, age group and sex using means ± SD, range of costs ($AU) and total costs ± SE. Chi-squared tests were used to analyse the data (significance level p < .05) with injury incidence rates (IR) calculated per 1000 match hours and per 1000 injury insurance claims. A total of 388 injuries affecting 240 players were sustained. Of these, 43% (n = 102) of players also sustained one or more secondary injuries, mainly to the head or neck area. Dental injuries (n = 143, 39%, IR = 0.008) accounted for the highest number of primary and secondary injuries and the highest mean direct cost per injury ($AU1152), while head and facial injuries accounted for the highest proportion of total costs ($AU434,101). Players who sustained one or more secondary injuries had the highest direct and indirect mean cost per injury. Given the frequency and cost of dental injuries in non-professional football players, injury prevention initiatives warrant further investigation.

Musculoskeletal injury profile in individuals training for the police recruitment exam

BACKGROUND: Each year, exams to become a police officer are held by the Police Academy Directorate in our country and various musculoskeletal injuries are seen during the preparation period. The aim of this study was to determine the musculoskeletal injury profiles of individuals training for police recruitment exams.METHODS: This study was a descriptive and retrospective study. This study was planned to be multicentric and was carried out in the three-sports medicine outpatient clinics. Individuals who trained for police recruitment exams, and applied to sports medicine outpatient clinics due to musculoskeletal injury/injuries were assessed. The participant’s age, gender, symptoms, onset of symptoms, injured body region, and injury types were recorded. Diagnosis were classified according to the Orchard Sports Injury and Illness Classification System (OSIICS) v.13.RESULTS: Data from 137 patients (100 females, 37 males) were analyzed. The mean age was 24±2.2 years. A total of 210 injuries occurred. The annual injury incidence rate was 21.74 per 1000 hours of training. The most frequently injured body region was the lower leg (N.=52, 31%). Almost half of injury-related musculoskeletal disorders (N.=96, 46%) were classified as muscle/tendon injuries, followed by bone injuries (N.=47; 22%) and cartilage/synovium/bursa (N.=32; 15%).CONCLUSIONS: Muscle-tendon injuries are the most common injury type in individuals training for the police recruitment exams.

Traumatic injuries among Alaska’s young workers: Linking cases from four data systems

BackgroundYoung workers (aged 15–24 years) experience higher rates of job-related injury compared with workers aged 25–44 years in the United States. Young workers may have limited or no prior work experience or safety training, which can contribute to their injury risk. In 2018, Alaska had the second highest work-related fatality rate and 14th highest non-fatal injury rate in the United States. This study aimed to characterize nonfatal and fatal occupational injuries among young workers in Alaska.MethodsTo describe injury patterns among Alaska young workers from 2014–2018, we used data from four datasets: Alaska Workers’ Compensation, Alaska Occupational Injury Surveillance System, Alaska Trauma Registry, and Alaska Fishermen’s Fund. The datasets were merged two at a time and filtered by the worker characteristics (e.g., age and sex) and incident characteristics (e.g., date of injury). Duplicates were then manually identified between the datasets using the variables above. The injury narrative and Occupational Injury and Illness Classification System codes were used last to verify true duplicates. Descriptive analyses were performed after the duplicates were merged.ResultsDuring the 5-year study period 2014–2018, young workers experienced 20 fatal and 12,886 nonfatal injuries. Residents of Alaska comprised 85% of nonfatal and 70% of fatal injuries. The top three major occupation groups with the highest number of injuries were production (1,391, 14%), food preparation (1,225, 12%), and transportation/material moving (1,166, 11%). The most common events leading to injuries were struck by object or equipment (2,027, 21%), overexertion involving outside sources (1,385, 14%), and struck against object or equipment (905, 9%). The most common nature of injuries were sprains/strains/tears (3,024, 29%), cuts/lacerations (1,955, 19%), and bruises/contusions (1,592, 15%).ConclusionAlthough progress has been made in reducing worker injuries, Alaskan young workers still experience injuries and fatalities frequently. Based on findings, there is a clear need for employers, researchers, public health professionals, parents, and young workers to prioritize young worker safety through an integrated approach, from education and training to adequate workplace supervision and support.

Incidence Of Injuries Among Us Paralympic Athletes Competing In The Tokyo 2020 Paralympic Games

PURPOSE: To characterize the injuries that occurred amongst the US Paralympic athletes during the 2020 Paralympic games. METHODS: A retrospective review of medical encounters recorded in the electronic medical record of US Paralympic athletes competing in the Tokyo 2020 Paralympic Games (August 14 - September 6, 2021) was conducted. All encounters were reviewed to identify new injuries based on the guidelines outlined by the 2020 International Olympic Committee that occurred during the Paralympic Games. Only new injuries were included in the analysis. Injuries were categorized using the Orchard Sports Injury and Illness Classification System. Details of the athlete (sex) and injury (anatomic location) were examined with incidence rates (IR) and 95% confidence intervals per 1,000 athlete days (AD) were calculated. RESULTS: Of the 241 US athletes (119 male and 122 female) who competed in the Tokyo 2020 Paralympic Games, 46 presented for medical evaluation of a new injury. The IR was 11.7 (95% CI; 8.3, 15.0) per 1,000 AD with a majority (58.7%) occurring in males (IR, 6.8 [4.3, 9.3] per 1,000 AD) compared to females (IR, 4.8 [2.6, 7.0] per 1,000 AD). Injuries to the upper limb (45.7%; IR, 5.3 [3.0, 7.6] per 1,000 AD) accounted for the highest injury rates, followed by injuries to the lower limb (21.7%; IR, 2.5 [1.0, 4.1] per 1,000 AD) and head/face/neck (10.9%; IR, 1.3 [0.2, 2.4] per 1,000 AD). The specific anatomical locations that had the highest rates of injury were the shoulder (15.2%; IR, 1.8 [0.5, 3.1] per 1,000 AD), the wrist/hand (15.2%; IR, 1.8 [0.5, 3.1] per 1,000 AD), and the knee (10.9%; IR, 1.3 [0.2, 2.4] per 1,000 AD). CONCLUSION: Analysis of injuries that occurred among a single Paralympic delegation competing in the Tokyo 2020 Paralympic Games revealed that males sustained more injuries than females with injuries to the upper limb accounting for approximately half (45.7% of all injuries). Continued injury surveillance in elite Paralympic athletes is important to understand injury epidemiology in this population and inform future injury prevention strategies.

Incidence Of Injuries Among Team USA Athletes Competing In Tokyo 2020 Summer Olympic Games

PURPOSE: To describe the incidence of injuries sustained by Team USA athletes during the 2020 Tokyo Summer Olympic Games. METHODS: A retrospective chart review was performed on Team USA athlete electronic medical records from the Tokyo 2020 Summer Olympic Games (July 12 - August 11, 2021). New injuries were defined as any medical concern that was brought to medical attention in accordance with 2020 International Olympic Committee guidelines and classified using the Orchard Sports Injury and Illness Classification System. Details of the athlete (sex) and injury (anatomic location) were examined and incidence rates (IR) with 95% confidence intervals per 1,000 athlete days (AD) were calculated. RESULTS: 158 new injuries were documented among the 626 US athletes (male, n = 341; female, n = 285)) that competed in the Tokyo 2020 Summer Olympic Games, resulting in an IR of 14.1 [95% CI, 11.9, 16.3] per 1,000 AD. Female athletes sustained 60.8% of new injuries (IR, 8.6 [6.9, 10.3] per 1,000 AD) compared to males (IR, 5.5 [4.2, 6.9] per 1,000 AD). Lower limb injuries accounted for 39.9% of all documented injuries (IR, 5.6 [4.2, 7.0] per 1,000 AD); injuries to the knee (n = 22; IR, 2.0 [1.1, 2.8] per 1,000 AD) and ankle/foot (n = 35; IR, 3.1 [2.1, 4.2] per 1,000 AD) made up 90.4% of lower limb injuries. Upper limb injuries (shoulder/arm/elbow, 16.5%, IR, 2.3 [1.4, 3.2] per 1,000 AD; wrist/hand/finger, 8.2%, IR, 1.2 [0.5, 1.8] per 1,000 AD) and spine injuries (lumbar spine, 8.9%, IR, 1.2 [0.6, 1.9] per 1,000 AD; thoracic spine, 3.8%, IR, 0.5 [0.1, 1.0] per 1,000 AD) accounted for 24.7% and 12.7% of all documented injuries, respectively. CONCLUSION: Among Team USA Summer Olympic athletes, lower limb injuries occurred at the highest frequency followed by upper limb and spine injuries. Continued athlete injury surveillance is necessary to prepare for and develop targeted prevention and treatment strategies for future Summer Olympic Games.

Incidence Of Illness Among Team USA Athletes During The Tokyo 2020 Summer Olympic Games

PURPOSE: To describe the incidence and characteristics of illnesses affecting Team USA athletes during the Tokyo 2020 Summer Olympic Games. METHODS: All Olympic athlete medical encounters occurring during the Tokyo 2020 Summer Olympic Games (July 12 - August 11, 2021) were reviewed to identify new illnesses. Illnesses meeting the definition as described by the International Olympic Committee reporting guidelines were included in the analysis. New illnesses were categorized using the Orchard Sports Injury and Illness Classification System. Details of the athletes (sex) and illness (type) were examined and incidence rates (IR) with 95% confidence intervals per 1,000 athlete days (AD) were calculated. RESULTS: Six hundred and twenty-six US athletes (male, n = 341; females, n = 285) competed in the Tokyo 2020 Summer Olympic Games, accounting for 11,204 AD. A total of 51 illnesses (male, n = 18; females, n = 33) were documented resulting in an IR of 4.6 [95% CI; 3.3, 5.8] per 1,000 AD. The most common illnesses diagnosed were infections (23.5%; IR, 1.1 [0.5, 1.7] per 1,000 AD), followed by gastrointestinal (15.7%; IR, 0.7 [0.2, 1.2] per 1,000 AD), dermatologic (13.7%; IR, 0.6 [0.2, 1.1] per 1,000 AD), respiratory (11.8%; IR, 0.5 [0.1, 1.0] per 1,000 AD), ears/nose/throat (11.8%; IR, 0.5 [0.1, 1.0] per 1,000 AD), eye (5.9%; IR, 0.3 [0.0, 0.6] per 1,000 AD), and environmental illnesses (5.9%; IR, 0.3 [0.0, 0.6] per 1,000 AD). Other illnesses included psychological (3.9%; IR, 0.2 [-0.1, 0.4] per 1,000 AD), genitourinary (2.0%; IR, 0.1 [-0.1, 0.3] per 1,000 AD), and cardiovascular (2.0%; IR, 0.1 [-0.1, 0.3] per 1,000 AD). CONCLUSION: Among US Olympic athletes competing in the Tokyo 2020 Summer Olympic Games, infections, gastrointestinal illness, and dermatologic conditions represented over 50% of all documented illnesses. Surveillance and characterization of illness among Olympic athletes is crucial to understanding illness risk factors during the Games period and implementing prevention strategies to keep athletes healthy and at peak performance during future Olympic Games.

World Federation of Athletic Training and Therapy World Congress 2022 Peer-Reviewed Track Abstracts, May 5–7, 2022, Winnipeg, Manitoba, Canada

World Federation of Athletic Training and Therapy World Congress 2022 Peer-Reviewed Track Abstracts, May 5–7, 2022, Winnipeg, Manitoba, Canada

Direct and indirect costs associated with injury in sub-elite football in Australia: a population study using 3 years of sport insurance records

ObjectivesTo determine the direct and indirect costs of injuries in sub-elite footballers in New South Wales (NSW), Australia, stratified by injury location, type, sex and age groups. DesignDescriptive epidemiological study. MethodsA de-identified insurance database containing three seasons (2018–2020) of football injuries in NSW was used to determine injury costs. Injuries were coded using the Orchard Sports Injury and Illness Classification System. Claim costs are presented by age group (Junior = 7–17 years, Senior = 18–34 years, and Veteran = 35+ years), sex and injury location and type. Cost data are reported as means ± standard deviation (SD) with 95 % Confidence Intervals (CI). ResultsThere were 4145 total injury claims, totalling AU$13,716,173, at a mean cost of $3309 (95 % CI 3042–3577) per injury. Joint sprains accrued the largest costs ($6,665,938) with knee injuries accounting for just under half of the total costs of all injuries over the three-season period (49.1 %). ACL injuries accounted for 26.2 % of total costs with a high mean cost per injury ($4564 SD ± 346) alongside lower limb fractures ($4787 SD ± 425) and tendon ruptures ($4659 SD ± 1053). Despite only 22.5 % of injuries accruing indirect costs, these costs accounted for 70.2 % of the total cost ($9,623,665) with the mean indirect cost per injury being ten-times higher than the mean direct cost per injury ($10,337 vs. $987, respectively). ConclusionsKnee injuries (mainly ACL ruptures), joint sprains, fractures and tendon ruptures are the costliest injuries in sub-elite football in NSW. With effective preventative measures available, there is potential to reduce injury rates and subsequent costs.

Is the Course of COVID-19 Different during Pregnancy? A Retrospective Comparative Study.

The COVID-19 pandemic has challenged health systems around the world. Maternal-foetal medicine, which has been particularly affected, must consider scientific data on the physiological processes occurring in the pregnant woman’s body to develop relevant standards of care. Our study retrospectively compared the clinical and laboratory characteristics of 52 COVID-19 pregnant patients with 53 controls. Most of the pregnant patients required medical attention during the third trimester and therefore we propose that vaccination is needed prior to the 30th week of pregnancy. We found no differences between the 2 groups in the course of illness classification system, days of hospital stay, need for oxygen supplementation, need for mechanical ventilation, and ICU admission. Moreover, clinical manifestations and imaging findings were comparable. Pregnant patients needed a greater oxygen flow rate and required high flow oxygen therapy more frequently. Considering pregnancy-related physiological adaptations, we found that COVID-19 infection in pregnant patients is associated with higher levels of inflammatory markers, apart from serum ferritin, than in non-pregnant women, and concluded that biomarkers of cardiac and muscle injury, as well as kidney function, may not be good predictors of COVID-19 clinical course in pregnant patients at the time of admission, but more research needs to be conducted on this topic.

Impact, incidence and prevalence of musculoskeletal injuries in senior amateur male rugby: epidemiological study

ABSTRACT Objectives: Exposure to different types of injuries in rugby union is common. It is important to know about the injury epidemiology for medical teams care in order to optimize players´ performance and the treatment of common injuries, but there is limited specific information related to amateur rugby union. The purpose of this study is to determine the incidence, prevalence, injury burden, severity, nature of injuries sustained by senior amateur male rugby players from three clubs in Argentina during a given season. Methods: An observational, analytical, prospective, multicenter study was developed. Data collection was conducted from 15 March 2019 to 2 November 2019, during a complete season under the applicable standards of the Rugby Injury Consensus Group according to the Orchard Sports Injury and Illness Classification System. Incidence (injuries/1000 player-match-hours), prevalence (%), severity (time loss), injury burden (days lost/1000 player-match-hours), injured location and type of injury (%) were estimated. Results: 250 players and 180 injuries were assessed. Injury prevalence was 52.4%. Incidence rate per match and training was 30.9/1000 player-match-hours, and 0.77/1000 player-training-hours, respectively. The median injury severity score was 23 (IQR 12.7–52) days lost accounting for an injury burden of 97.3/1000 player-hours. Of the total, 113 (62.8%) injuries were contact injuries. The lower limbs were the most commonly affected (58.9%). Hamstring strain injury had the highest incidence and anterior cruciate ligament tear was the most severe injury. Conclusion: The prevalence, incidence, and injury burden reported in this study are unprecedented and would add knowledge for the amateur rugby union community. Trainers, physicians, and physical therapists, should consider it to improve their clinical practice.

Disruptive mood dysregulation disorder

IntroductionFaced with a possible overdiagnosis of bipolar disorder in children and adolescents, a new diagnosis has been created in the mental illness classification system. This new diagnosis is named Disruptive Mood Dysregulation Disorder.ObjectivesWe propose to carry out a bibliographic review on the new diagnostic category of Disruptive Mood Dysregulation Disorder.MethodsWe present the clinical case of a 10-year-old boy showing severe irritability symptoms.ResultsDisruptive Mood Dysregulation Disorder refers to persistent irritability and frequent episodes of extreme behavioral disturbance in children up to 12 years of age. Onset must occur before 10 years of age and the diagnosis should not be applied to children under 6 years of age. The clinical course of these patients in adolescence and adulthood tends towards unipolar depressive disorders or anxiety disorders rather than bipolar disorders.ConclusionsThe new diagnosis of Disruptive Mood Dysregulation Disorder allows us to differentiate between the classic episodic presentations of mania from the non-episodic ones of severe irritability.DisclosureNo significant relationships.

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

BackgroundWhile 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.MethodsAll 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.ResultsOf 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.ConclusionsThe 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.

Resistance-Related Injuries Among Law Enforcement Officers: Addressing the Empirical Gap

Officers can be unintentionally injured during officer-suspect interactions, and these injuries are often not coded as assaults. This article defines and enumerates injuries that officers sustain while chasing, detaining, arresting, or pursuing suspects. These are termed resistance-related injuries. Data on law enforcement officer injuries treated in U.S. emergency departments were obtained from the National Electronic Injury Surveillance System-Occupational Supplement from 2012 to 2017. Resistance-related injuries were defined using the Bureau of Labor Statistics Occupational Injury and Illness Classification System, version 2.01. Injury rates were calculated using denominators from the Current Population Survey. Negative binomial regression was used to analyze temporal trends. Data were analyzed in 2019. Between 2012 and 2017, an estimated 303,500 officers were treated in U.S. emergency departments for nonfatal injuries for an overall injury rate of 568 per 10,000 full-time equivalents. Emergency department-treated injuries significantly decreased by 3.8% annually during this time period (p<0.0001). The leading causes of injury were assaults and violent acts (48%), transportation incidents (11%), and falls (11%). Of the total injuries, more than half were resistance-related (53%). A total of 88% of violence-related injuries, nearly 50% of falls, and 31% of overexertion injuries were considered resistance related. More than half of officers' nonfatal injuries occurred when they were interacting, detaining, or pursuing a suspect. This highlights the need to code nonfatal injuries in a consistent and meaningful way that informs police policy and practice.

Firefighter Overexertion: A Continuing Problem Found in an Analysis of Non-Fatal Injury Among Career Firefighters.

Traditionally, safety-related research on firefighting has focused on fires and fireground smoke as the primary source of non-fatal firefighter injury. However, recent research has found that overexertion and musculoskeletal disorders may be the primary source of firefighter injury. This study aimed to provide an update on injury occurrence among career firefighters. Injury data were collected over a two-year period from two large metropolitan fire departments in the U.S. Injury data were categorized based on the Bureau of Labor Statistics’ Occupational Injury and Illness Classification System. Cross-tabulations and Chi-square tests were used to determine the primary causes of injury, as well as the injury region. Between the two fire departments, there were 914 firefighters included in the analysis. The median age was 40.7 years old with those aged 40–49 as the largest age group for injury cases (38.3%). The most frequently reported cause of injury was ‘overexertion and bodily reaction’ (n = 494; 54.1%). The most reported injury region was in ‘multiple body parts’ (n = 331; 36.3%). To prevent subsequent musculoskeletal disorders that may arise due to overexertion, initiatives that promote enhanced fitness and ergonomics based on an analysis of the physical demands of firefighting are suggested.

Coding agricultural injury: Factors affecting coder agreement

Objectives: To determine coders’ agreement level for the Occupational Injury and Illness Classification System (OIICS) source of injury and injury event codes, and the Farm and Agricultural Injury Classification (FAIC) code in the AgInjuryNews.org and to determine the effects of supplemental information and follow-up discussion in final code assignments. Methods: Two independent researchers initially coded 1304 injury cases from AgInjurynews.org using the OIICS and the FAIC coding schemes. Code agreement levels for injury source, event, and FAIC and the effect of supplemental information and follow-up discussions on final coding was assessed. Results: Coders’ agreement levels were almost perfect for OIICS source and event categories at the 3-digit level, with lower agreement at the 4-digit level. By using supplemental information and follow-up discussion, coders improved the coding accuracy by an average 20% for FAIC. Supplemental information and follow-up discussions had helped finalize the disagreed codes 55% of the time for OIICS source coding assignments and 40% of time for OIICS event coding assignments for most detailed 4-digit levels. Five key themes emerged regarding accurate and consistent coding of the agricultural injuries: inclusion/exclusion based on industry classification system; inconsistent/discrepant reports; incomplete/nonspecific reports; effects of supplemental information on coding; and differing interpretations of code selection rules. Practical applications: Quantifying the level of agreement for agricultural injuries will lead to a better understanding of coding discrepancies and may uncover areas for improvement to coding scheme itself. High level of initial and final agreement with FAIC and OIICS codes suggest that these coding schemes are user-friendly and amenable to widespread use.

JA:2021-25. Increasing Efficiency and Reliability of Agricultural Injury and Fatality Coding with Standard Operating Procedures: Lessons Learned from AgInjuryNews.org

ABSTRACT Purpose: News media reports of agricultural injuries can be useful to better inform safety and health stakeholders and prevention efforts. These data are particularly useful for youth incidents, since the National Institute of Occupational Safety and Health discontinued their survey-based agriculture surveillance program in 2015, leaving a gap in reliable, consistent data on both youth and adult agricultural injuries and fatalities. In this study we describe how coding data derived from news reports, with a detailed Standard Operating Procedure (SOP) and refined inclusion/exclusion criteria, can lead to more efficient workflows to capture and code agricultural injury data. Methods: To capture quality data and improve inter-rater reliability we employ a multi-coder process. The first coder enters primary data into the Case Report Form (CRF), and a second coder reviews these data points for agreement. While reviewing for agreement, the second coder diverges into two other occupational/agricultural injury coding schemas (Occupational Illness and Injury Classification System [OIICS] and Farm and Agricultural Injury Classification [FAIC]) and employs an additional multi-coder and interrater reliability process, adding to the multifaceted workflow and detailed data output. This secondary coding schema and reliability ratings are discussed in a separate manuscript. Any discrepancies from the initial review are then discussed and settled between first and second coders. All CRFs are sent to another team member who reviews >10% and publishes the reports for public use on AgInjuryNews.org. International cases endure a similar process, but without OIICS or FAIC coding. In partnership with the Canadian Agricultural Safety Association, our team began Canadian injury report capture and coding in the fall of 2019. Findings: We developed a structured and detailed SOP for coding agricultural data obtained from news reports. Use of the SOP and refined inclusion/exclusion criteria were crucial when: 1) onboarding additional coders; 2) employing multiple coders; 3) refining search terms in data collection; 4) coding of emerging technologies and trends; and 5) improving the efficiency and quality of the data. Translation: Coders’ ability to reference a thoroughly vetted SOP and inclusion/exclusion criteria may lead to improved data coding for agricultural injuries and fatalities.

Sport Medicine Diagnostic Coding System (SMDCS) and the Orchard Sports Injury and Illness Classification System (OSIICS): revised 2020 consensus versions

Coding in sports medicine generally uses sports-specific coding systems rather than the International Classification of Diseases (ICD), because of superior applicability to the profile of injury and illness presentations in...

Heat related illness among workers in Washington State: A descriptive study using workers' compensation claims, 2006-2017.

Heat related illness (HRI) places a significant burden on the health and safety of working populations and its impacts will likely increase with climate change. The aim of this study was to characterize the demographic and occupational characteristics of Washington workers who suffered from HRI from 2006 to 2017 using workers' compensation claims data. We used Washington workers' compensation data linked to weather station data to identify cases of work-related HRI. We utilized Occupational Injury and Illness Classification System codes, International Classification of Diseases 9/10 codes, and medical review to identify accepted and rejected Washington State (WA) workers' compensation claims for HRI from 2006 to 2017. We estimated rates of HRI by industry and evaluated patterns by ambient temperature. We detected 918 confirmed Washington workers' compensation HRI claims from 2006 to 2017, 654 were accepted and 264 were rejected. Public Administration had the highest third quarter rate (131.3 per 100 000 full time employees [FTE]), followed by Agriculture, Forestry, Fishing, and Hunting (102.6 per 100 000 FTE). The median maximum daytime temperature was below the Washington heat rule threshold for 45% of the accepted HRI claims. Latinos were estimated to be overrepresented in HRI cases. The WA heat rule threshold may not be adequately protecting workers and racial disparities are present in occupational HRI. Employers should take additional precautions to prevent HRI depending on the intensity of heat exposure. States without heat rules and with large industry sectors disproportionately affected by HRI should consider regulations to protect outdoor workers in the face of more frequent and extreme heat waves.