Injury Trends, Costs, and Lost Time in an Australian Meat Processing Facility: A Retrospective Analysis

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This study investigated workplace injury trends, compensation costs, and time lost in an Australian red-meat processing facility over seven years and considered the potential influence of pre-employment assessments (PEAs) and physiotherapy-led early intervention programmes. Methods A retrospective descriptive analysis was conducted using organisational injury, compensation, and workforce data from 2018 to 2024. Injuries were categorised as burns, critical injury, foreign body, laceration, musculoskeletal disorder, or soft tissue. Descriptive statistics summarised injury frequency, claim costs, and time lost, and temporal patterns were visualised. Costs were reported in 2024 Australian dollars. Results A total of 273 workplace injuries were recorded. Lacerations (48.6%) and musculoskeletal disorders (27.7%) were most common. Cumulative compensation costs exceeded AUD $ 3.1 million and total time lost surpassed 3.6 million hours. Cost increases during 2020–2021 aligned with COVID-19-related operational disruptions. Injury frequency decreased from 73 cases in 2023 to 44 cases in 2024 following the introduction of PEAs and physiotherapy-led early intervention; however, causal inference is limited due to study design. Conclusions Workplace injuries in meat processing impose substantial operational and economic impacts, driven largely by high-frequency laceration and musculoskeletal-related claims. Findings suggest that proactive screening and ergonomic interventions may help to reduce injury burden and improve workforce sustainability. Prospective studies are needed to evaluate the effectiveness and scalability of PEAs and early intervention strategies in high-risk industrial settings. Occupational health Meat processing Injury epidemiology Workers’ compensation Workplace safety Pre-employment assessments Musculoskeletal disorders Ergonomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The Australian meat processing industry is among the nation’s highest-risk occupational sectors, characterised by repetitive manual handling, cold environments, sharp-tools, and high production demands ( 1 ). Nationally, approximately 3.5 per cent of employed Australians reported a work-related injury or illness in the 12 months to 2021–22, with 66 per cent requiring time away from work ( 2 ). However, these averages mask the disproportionate burden within meat processing, which records serious injury claim rates several times higher than manufacturing. General manufacturing reports approximately 9.6 serious injury claims per million hours worked, while meat processing facilities report rates between 19 and 29 claims per million hours ( 2 , 3 ). Workers are exposed to hazards such as continuous knife use, low-temperature environments, carcass lifting, and labour-intensive manual processes. Comparatively, other high-risk sectors such as agriculture (11.1), construction (up to 16.9), and healthcare (10.2) also report high injury rates, although none exhibit the persistent and elevated rates characteristic of meat processing ( 2 , 4 ). Within red-meat operations, lacerations and musculoskeletal disorders (MSDs) dominate incident reports, together accounting for more than 70% of injuries. Manual handling tasks such as lifting carcasses, shifting heavy product, and stacking boxes contribute to around 45% of claims, while knife-related activities, including cutting, boning, and trimming, account for approximately half of all incidents ( 2 ). National data further indicate that traumatic joint, ligament, and muscle or tendon injuries represent about 50% of claims and 36% of total costs, whereas lacerations account for 29% of claims and 21% of costs ( 4 ). These figures highlight the need for targeted safety interventions and policy attention. Pre-employment assessments (PEAs) and early intervention programs are increasingly employed as preventive strategies to address the industry’s high injury rates. PEAs evaluate an individual’s physical capacity, mobility, and overall suitability for physically demanding roles, supporting the principle of “person–job fit” and reducing the likelihood of early-tenure injuries ( 5 ). In the meat processing, PEAs, follow a two-stage process. Stage one involves a self-report questionnaire covering lifestyle factors, medical and injury history, immunisation status, and potential exposure to communicable diseases. It also includes questions about previous injuries, surgeries, or medical conditions that may affect work capacity or increase injury risk. Stage two consists of a one-on-one physiotherapy assessment, including = grip strength, rotator cuff strength, spinal flexion, squatting, lifting (from ground and overhead), pushing strength, range of motion, and hearing via audiometry. The assessment determines whether the individual has sufficient physical capacity for the intended role and identifies any pre-existing conditions that may increase injury risk. Physiotherapy led functional assessments are particularly effective in identifying workers at higher risk of musculoskeletal strain, outperforming traditional medical-only screening models. These assessments typically evaluate strength, flexibility, endurance, and task-specific capabilities such as lifting, carrying, repetitive cutting, and prolonged standing, providing a more accurate prediction of injury susceptibility in physically demanding environments. ( 6 , 7 ). Complementary early-intervention programs such as physiotherapy triage, ergonomic risk modification, and task-readiness training can further reduce injury risk and accelerate recovery where injuries occur ( 8 – 10 ). Evidence suggests that employees who undergo functional screening experience approximately 33 per cent fewer injury claims than unscreened cohorts, while non-screened employees show higher rates of compensation and lost-time claims ( 3 ). This study explores workplace injury patterns, associated costs, and time lost within an Australian meat processing facility over a seven-year period (2018–2024). Drawing on longitudinal operational and demographic data, it considers trends in injury frequency, severity, and economic impact, with particular attention to musculoskeletal disorders (MSDs) and lacerations the two most common injury categories. The research also considers the introduction of a pre-employment assessment (PEA) program and a physiotherapy-based early intervention strategy implemented from 2018, examining their role in shaping injury outcomes over time. Methods Study Design This study used a retrospective descriptive design to analyse injury and workforce data from a large Australian meat-processing facility over a seven-year period (2018 to 2024). The aim was to identify patterns in injury frequency, severity, associated costs, and time lost due to injury-related absences. A secondary aim was to evaluate the potential influence of pre-employment assessments (PEAs) and early intervention programmes implemented during the study period. Descriptive statistical methods were used to summarise injury counts, claim costs, and hours lost. Temporal trends were visualised using line and bar charts, and scatterplots were used to explore the relationship between claim costs and time lost. No inferential statistical tests were conducted, as the study was designed to describe observed patterns rather than to establish causal relationships. Data Sources Data were extracted from multiple organisational sources including, occupational health and safety (OHS) logs, human resources reports, and financial records. The OHS logs provided detailed information on incident type, date of occurrence, severity, and associated claim costs. Human resource reports supplied workforce demographic data, including total employee numbers, new hires by year, and site-specific employment figures. Financial records included compensation costs and wage liabilities related to injury claims. Documentation on the implementation and scope of PEAs and physiotherapy led early intervention strategies was reviewed to contextualise observed injury trends. Variables Injury events were classified into six categories: burns, critical injuries, foreign body incidents, lacerations, musculoskeletal disorders, and soft tissue injuries. Burns typically involved thermal exposure during processing tasks. Critical injuries represented severe cases such as traumatic head injuries or amputations, foreign body incidents resulted from embedded particles requiring medical removal. Lacerations were primarily knife-related cuts and puncture wounds, while musculoskeletal disorders included strains, sprains, and overuse injuries associated with repetitive manual handling. Soft tissue injuries encompassed bruises and minor trauma without structural damage. The workforce was predominantly male (approximately 95%), with female representation around 5%. The average age of employees was approximately 35 years. The primary variables analysed included injury frequency, cost metrics, time lost, and workforce demographics. Injury frequency was assessed by tallying the number of recorded incidents annually, stratified by injury category. Cost metrics included both total and mean claim costs, disaggregated by year and injury type to identify financial trends. Time lost was measured by summing the aggregate hours of absence attributed to injury-related leave. Workforce demographics, including employee counts and turnover, were used to contextualise injury rates and assess organisational stability. Data Analysis Descriptive statistics summarised injury counts, category distribution, claim costs, and time lost. Event counts were aggregated annually and stratified by injury type. Cost analysis involved calculating total and mean claim costs per injury category and year. Measures of variability, including standard deviation, minimum, and maximum values, were computed to identify high-cost outliers. Time lost was assessed by summing hours of absence per injury category and year, enabling evaluation of productivity impacts. Temporal trends were visualised using bar and line plots, while scatterplots explored the relationship between claim costs and time lost. A heatmap was also developed to illustrate the average cost per injury category across the study years. Injury incidence rates were calculated by dividing the number of injury events by the corresponding employee-year exposure and multiplying by 100 to express the rate per 100 employee-years. Employee exposure was calculated using the formula: $$\:\text{Employee-Year\:Exposure}=\text{Total\:Employees}\times\:\left(\frac{\text{Months\:Monitored}}{12}\right)$$ Exact 95% confidence intervals for these rates were estimated using the Poisson distribution, following the method described by Garwood (1936). All analyses were conducted using Microsoft Excel. Results were validated through cross-checking with original organisational records to ensure accuracy and consistency. Ethical Considerations All data were anonymised prior to analysis. Injury records did not include individual level identifiers such as ethnicity, age, or sex. The study relied exclusively on existing organisational records and did not involve direct interaction with employees, thereby minimising ethical risk. Ethics approval was granted by the University of Newcastle Human Research Ethics Committee (H-2024-0321). Written informed consent was gained prior to data analysis. The research was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and aligned with the National Health and Medical Research Council (NHMRC) National Statement on Ethical Conduct in Human Research ( 11 ). Results 3.1 Event Trends A total of 273 injuries were recorded between 2018 and 2024. Injury frequency increased markedly over the study period, rising from 7 cases in 2018 to 35 in 2019, and peaking at 73 cases in 2023. This escalation likely reflects heightened operational pressures and workforce instability during the mid study years. A subsequent decline to 44 cases in 2024 coincided with the implementation of PEAs and physiotherapy led early intervention programs. Temporal analysis revealed notable spikes in injury frequency and associated costs during the COVID 19 pandemic years (2020–2021). These increases reflect labour shortages, workforce turnover, and operational disruptions ( 4 ). These trends are illustrated in Fig. 1 , which shows annual injury counts alongside total claim costs. Figure 1 Annual Injury Event Counts and Total Claim Costs (2018–2024) 3.2 Cost Analysis The cumulative financial burden of workplace injuries exceeded $ 3.1 million across the study period. Musculoskeletal disorders and lacerations were the costliest injuries, together accounting for more than $ 1.63 million over half of total compensation costs. Musculoskeletal injuries were particularly expensive due to extended recovery times, physiotherapy requirements, and wage liabilities during prolonged absences. Lacerations, although generally less severe, imposed significant costs due to their high frequency and occasional need for surgical intervention. Cost spikes in 2020 and 2021 aligned with the pandemic period, reflecting the combined effects of operational strain, reduced access to rehabilitation services, and increased reliance on less experienced workers. Critical injuries, including traumatic head injuries and amputations, represented extreme outliers, with individual claims exceeding $ 685,000 dollars in 2021. In contrast, soft tissue injuries and burns, while less frequent, showed cost variability when complications or extended recovery occurred. These patterns highlight the need for targeted prevention strategies and early intervention, particularly for high-cost injury types. These trends are shown in Fig. 2 , which depicts average event cost by injury category and year, and in Table 1 , which provides summary statistics for claim costs. Table 1 Summary Statistics of Event Costs by Year and Category Year Category n Mean (AUD) SD (AUD) Median (AUD) Min (AUD) Max (AUD) 2018 Critical Injury 1 1,051 1,051 1,051 1,051 2018 Foreign body 1 2,116 2,116 2,116 2,116 2018 Laceration 1 1,765 1,765 1,765 1,765 2018 Musculoskeletal Disorder 3 44,158 73,225 2,313 1,451 128,709 2018 Soft tissue 1 1,475 1,474 1,474 1,474 2018 Total 7 19,840 48,009 1,765 1,051 128,709 2019 Critical Injury 2 1,749 1,260 1,749 858 2,640 2019 Laceration 9 1,587 1,352 1,060 281 4,037 2019 Musculoskeletal Disorder 18 6,187 13,893 2,001 605 59,977 2019 Soft tissue 6 7,265 13,777 1,660 1,011 35,353 2019 Total 35 4,935 11,412 1,733 281 59,977 2020 Burns 2 1,170 5 1,169 1,166 1,173 2020 Foreign body 1 528 527 527 527 2020 Laceration 6 533 374 421 214 1,241 2020 Musculoskeletal Disorder 7 75,126 171,233 10,716 281 462,618 2020 Soft tissue 5 4,720 7,067 741 83 16,751 2020 Total 21 26,455 100,263 741 83 462,618 2021 Critical Injury 8 87,158 241,899 1,333 0 685,806 2021 Laceration 16 28,433 81,407 864 0 329,693 2021 Musculoskeletal Disorder 4 5,785 5,298 5,327 880 11,602 2021 Soft tissue 8 9,682 16,854 510 0 48,399 2021 Total 36 34,800 124,451 1,057 0 685,806 2022 Burns 2 95 134 94 0 189 2022 Critical Injury 7 11,205 28,406 794 0 75,614 2022 Foreign body 2 350 495 349 0 699 2022 Laceration 20 3,579 8,117 598 0 32,551 2022 Musculoskeletal Disorder 13 3,437 7,579 1,053 0 28,164 2022 Soft tissue 13 2,688 2,989 1,328 423 9,985 2022 Total 57 4,044 11,449 677 0 75,614 2023 Burns 1 67 66 66 66 2023 Critical Injury 10 27,844 60,635 979 0 181,197 2023 Foreign body 2 1,896 1,313 1,896 967 2,824 2023 Laceration 32 3,193 6,913 1,125 0 36,446 2023 Musculoskeletal Disorder 7 6,027 5,506 8,200 154 14,497 2023 Soft tissue 21 4,353 10,150 908 0 42,350 2023 Total 73 7,097 24,117 1,082 0 181,197 2024 Burns 2 4,981 4,933 4,981 1,493 8,468 2024 Critical Injury 2 1,032 1,021 1,032 310 1,754 2024 Foreign body 1 923 922 922 922 2024 Laceration 23 3,518 4,700 1,371 0 15,200 2024 Musculoskeletal Disorder 9 2,942 4,283 775 0 11,834 2024 Soft tissue 7 16,590 25,654 1,855 97 66,707 2024 Total 44 5,374 11,491 1,379 0 66,707 Total All 273 11,374 55,861 1,094 0 685,806 SD = Standard Deviation. SD = Standard Deviation. Mean, median, minimum, and maximum values are expressed in Australian dollars (AUD). 3.3 Time Lost Total time lost due to injury surpassed 3.63 million hours over the study period, reflecting both direct absenteeism and indirect productivity losses from restricted duties and workforce reallocation. Musculoskeletal disorders accounted for approximately 1.3 million hours the largest share consistent with their severity and prolonged recovery requirements. These injuries often necessitated extended rehabilitation and gradual return-to-work programs. Lacerations contributed around 935,000 hours, while typically resulting in shorter absences, complex cases requiring surgery drove occasional spikes in lost time. Critical injuries, though rare (30 cases), were highly disruptive, with individual incidents exceeding 500,000 hours lost due to long-term incapacity. The highest cumulative time lost occurred during 2020 and 2021, coinciding with the pandemic. This period was marked by limited access to physiotherapy, increased physical strain, and workforce instability, all of which likely contributed to delayed recovery. In contrast, the reduction in lost time observed in 2024 suggests that the introduction of pre-employment assessments and early physiotherapy may have supported more efficient recovery and return to work. The relationship between claim cost and time lost is illustrated in Fig. 3 , and category-specific trends are shown in Fig. 4 . 3.4 Injury Profile Analysis of injury types revealed that lacerations (n = 107, 48.6 percent) and musculoskeletal disorders (n = 61, 27.7 percent) were the most common, together comprising over two thirds of all recorded incidents. Soft tissue injuries were the third most frequent (n = 34, 15.5 percent), followed by burns (n = 8, 3.6 percent), foreign body incidents (n = 6, 2.7 percent), and critical injuries (n = 4, 1.8 percent). Although infrequent, critical injuries such as amputations and traumatic head injuries contributed disproportionately to total costs and time lost due to their severity and prolonged recovery. These distributions are summarised in Table 1 and visualised in the heatmap of average cost per injury category across study years (Fig. 4 ). Cost trends highlighted the financial burden of both high-frequency and severe injuries. In 2021. critical injuries had the highest mean claim cost, exceeding AUD $ 87,000 per case. Lacerations, although more frequent, averaged over AUD $ 28,000 per claim, demonstrating that routine injuries can still be costly. Musculoskeletal disorders showed a sharp increase in mean cost in 2020, reaching AUD $ 75,126, likely due to pandemic related delays in treatment and rehabilitation. Soft tissue injuries, while less frequent, also demonstrated cost variability, with mean expenses rising to AUD $ 16,590 in 2024, reflecting the impact of complications on recovery and claims. These findings reinforce the importance of targeted prevention strategies addressing both high cost and high frequency injuries. Improvements observed in 2024 suggest that robust screening, ergonomic interventions, and early physiotherapy may contribute to reduce the incidence and severity of workplace injuries, contributing to long term workforce sustainability. Discussion The decline in injuries from 73 cases in 2023 to 44 in 2024 appears temporally associated with the introduction of pre-employment assessments (PEAs) and physiotherapy-led early intervention programs. These strategies aim to improve workforce readiness and align physical capacity with job demands, consistent with evidence that functional capacity evaluations and early physiotherapy reduce musculoskeletal risk and recovery time ( 8 , 12 ). However, causality cannot be inferred due to the retrospective design. Other factors such as improved staffing stability, operational recovery, and reporting practices may have contributed. Regression to the mean following a high-injury year in 2023 is also possible. These findings highlight the need for prospective evaluations to confirm effectiveness. The strong association between claim costs and time lost underscores that prolonged recovery drives financial burden, particularly for severe injuries. Pandemic-related spikes in 2020–2021 illustrate the vulnerability of occupational health systems to external disruptions and emphasize the importance of resilience planning. Musculoskeletal disorders and lacerations remain dominant injury types, indicating that screening alone is insufficient. Integrating ergonomic redesign, knife-handling training, and task-specific conditioning into onboarding and ongoing programs may offer additional benefit. From a policy perspective, these findings reinforce the importance of embedding preventive strategies within industry-wide safety frameworks. Systematic reviews show that interventions targeting musculoskeletal disorders and absenteeism often yield positive return on investment, supporting their inclusion in occupational health standards. For high-risk sectors such as meat processing, combining functional screening with ergonomic and training interventions could reduce injury burden and improve workforce sustainability ( 10 , 13 ). This study relied on retrospective data from a single facility, which may limit generalizability. The absence of inferential statistical analysis and potential confounding factors such as workforce turnover and management changes restrict causal interpretation. Additionally, injury reporting practices may have varied over time, influencing observed trends. Future research should address these limitations through multi-site, prospective designs and incorporate qualitative insights into implementation challenges. Preventive strategies have demonstrated economic and health benefits, but feasibility and scalability require validation through controlled trials. Long-term monitoring will be essential to ensure adaptability during operational stressors such as pandemics or supply chain disruptions. By investing in evidence-based interventions, employers can enhance worker safety, reduce financial burden, and strengthen resilience in physically demanding industries. Conclusion This study highlights the significant burden of workplace injuries in the Australian meat processing industry, with musculoskeletal disorders and lacerations emerging as the most frequent and costly categories. These injuries accounted for the majority of compensation costs and productivity losses, underscoring the need for targeted prevention strategies. The cumulative impact over AUD $ 3.1 million in costs and 3.6 million hours lost reinforces the economic and operational importance of proactive occupational health measures. The observed decline in injuries in 2024 coincided with the introduction of pre-employment assessments and physiotherapy-led early intervention programs, suggesting their potential value in improving workforce readiness and mitigating risk. However, causality cannot be confirmed, and other factors such as staffing stability and operational recovery likely contributed. These findings support a multifaceted approach that combines screening, ergonomic design, and ongoing training to address persistent injury types. Future research should focus on prospective, controlled evaluations to determine the effectiveness and cost efficiency of these interventions. Exploring scalability across diverse industrial settings will be critical for informing policy and ensuring sustainable implementation. By investing in evidence-based preventive strategies, employers can enhance worker safety, reduce financial burden, and strengthen resilience in physically demanding sectors Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the University of Newcastle Human Research Ethics Committee (H-2024-0321). The study analysed routinely collected organisational injury and compensation data without identifiable personal information; therefore, consent to participate was not required. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work. Author Contribution BR conceptualised the study, conducted the analysis, and drafted the manuscript. AH, JR, and MS contributed to critical revision of the manuscript and provided supervision and methodological guidance. All authors reviewed and approved the final manuscript. Acknowledgement The authors acknowledge Michael Fitzgerald for his assistance with statistical analysis and data interpretation. We also acknowledge EC Throsby Pty Ltd and the University of Newcastle for providing in-kind access to organisational injury and compensation data that made this work possible. Data Availability The datasets generated and analysed during the current study are not publicly available due to commercial and confidentiality agreements with the participating organisation. Data may be made available from the corresponding author on reasonable request and with permission from the organisation. References Safe Work Australia. Manual handling in the workplace 2023 [Available from: https://www.safeworkaustralia.gov.au/manual-handling Australian Bureau of Statistics. Work-related injuries in Australia: 2022 2023 [Available from: https://www.abs.gov.au/statistics/industry/workplace-safety/work-related-injuries/latest-release Safe Work Australia. Key work health and safety statistics, Australia 2024 [Available from: https://data.safeworkaustralia.gov.au/insights/key-whs-statistics-australia/latest-release Australian Meat Industry Council. Report on the Australian meat processing industry's health and safety practices 2020 [Available from: https://amic.org.au/wp-content/uploads/2020/10/2020-2021-Annual-Operating-Plan.pdf Fenner P, RACGP) RACoGP. (. Pre-employment medicals: Addressing the challenges 2011 [Available from: https://www.racgp.org.au/getattachment/36f11d49-6663-4953-bace-0445fe339656/The-pre-employment-medical.aspx Frederieke G, Schaafsma NM, Reneman MF, Fassier JB, Jungbauer FHW. Pre-employment examinations for preventing injury, disease and sick leave in workers. Cochrane Database Syst Reviews. 2016;1. Pachman J. Evidence base for pre-employment medical screening. Bull World Health Organ. 2009;87(8):529–34. Nicholas MK, Costa DSJ, Linton SJ, Main CJ, Shaw WS, Pearce G, Gleeson M, Pinto RZ, Blyth FM, McAuley JH, Smeets RJEM, McGarity A. Implementation of Early Intervention Protocol in Australia for ‘High Risk’ Injured Workers is Associated with Fewer Lost Work Days Over 2 Years Than Usual (Stepped) Care. J Occup Rehabil. 2020;30:93–104. Renfrew B, Reis J, Hutton A, Stubbs M. Effectiveness of pre-employment assessments in improving worker health in the meat processing industry: a scoping review. J Public Health. 2025. Schaafsma F, Hulshof C, Verbeek J, Bos J, Dyserinck H, van Dijk F. Pre-employment examinations for preventing injury, disease, and sick leave in workers. Cochrane Database Syst Reviews. 2016;1. World Medical Association. WMA Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Participants 2005 [Available from: https://www.wma.net/policies-post/wma-declaration-of-helsinki/ Legge J, Burgess-Limerick R, Peeters G. A new pre-employment functional capacity evaluation predicts longer-term risk of musculoskeletal injury in healthy workers: a prospective cohort study Spine 2013;38(25). Esmaeili RS, Esmaeili M, Jalali SV, Babaei Pouya M, Karimi A. A. A multicomponent quasi-experimental ergonomic interventional study: long-term parallel four-groups interventions. BMC Musculoskelet Disord. 2023;24(107). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8586512","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580594589,"identity":"64cd19c8-05a7-4956-92f6-1627abe140e5","order_by":0,"name":"Bree Renfrew","email":"data:image/png;base64,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","orcid":"","institution":"University of Newcastle Australia","correspondingAuthor":true,"prefix":"","firstName":"Bree","middleName":"","lastName":"Renfrew","suffix":""},{"id":580594590,"identity":"72f8e392-9a31-4195-8c30-f0f5db2b8575","order_by":1,"name":"Alison Hutton","email":"","orcid":"","institution":"Western Sydney University","correspondingAuthor":false,"prefix":"","firstName":"Alison","middleName":"","lastName":"Hutton","suffix":""},{"id":580594591,"identity":"58ae0313-6496-4aae-b3ac-427122faef14","order_by":2,"name":"Julie Reis","email":"","orcid":"","institution":"La Trobe University","correspondingAuthor":false,"prefix":"","firstName":"Julie","middleName":"","lastName":"Reis","suffix":""},{"id":580594592,"identity":"f6af45df-1e45-4804-8d9a-c030b9d8ebfc","order_by":3,"name":"Michelle Stubbs","email":"","orcid":"","institution":"University of Newcastle Australia","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"","lastName":"Stubbs","suffix":""}],"badges":[],"createdAt":"2026-01-13 02:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8586512/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8586512/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101269094,"identity":"05e8a479-7cc3-462a-9f94-eb67fc0640ca","added_by":"auto","created_at":"2026-01-28 01:27:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":227538,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnnual workplace injury counts and total compensation costs (2018–2024)\u003c/strong\u003e\u003cbr\u003e\nLine graph showing the annual number of recorded injury events alongside cumulative compensation costs in Australian dollars. Injuries peaked in 2023, while compensation costs showed marked increases during 2020–2021.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8586512/v1/d81b4d98476494a4103f379a.jpg"},{"id":101298009,"identity":"94f6658d-1202-4511-8f68-7de8b9cdc958","added_by":"auto","created_at":"2026-01-28 09:29:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":257919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMean compensation cost per injury by category (2018–2024)\u003c/strong\u003e\u003cbr\u003e\nBar chart displaying mean claim cost for each injury category across the study period. Musculoskeletal disorders had the highest mean cost per event.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8586512/v1/e2edd1829f5187cda387b4e9.jpg"},{"id":101269092,"identity":"20ddf9c3-d76c-428d-92f8-8bae075ebf3e","added_by":"auto","created_at":"2026-01-28 01:27:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":206548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between compensation cost and time lost across injury categories\u003c/strong\u003e\u003cbr\u003e\nScatter plot illustrating the association between total claim costs and cumulative time lost (hours) by injury category. Higher cost categories corresponded with greater time lost.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8586512/v1/ae5500a0d287b7f67197211a.jpg"},{"id":101297940,"identity":"28c0f01c-873c-4760-8bcf-e4728914488d","added_by":"auto","created_at":"2026-01-28 09:29:24","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":183965,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInjury type distribution by year (2018–2024)\u003c/strong\u003e\u003cbr\u003e\nStacked bar chart showing the annual distribution of injury categories. Lacerations and musculoskeletal disorders consistently accounted for the majority of reported injuries.\u003c/p\u003e","description":"","filename":"14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8586512/v1/1c94846a2b18a90875ed7d81.jpg"},{"id":101299419,"identity":"1d3a7e63-8324-438c-92cd-01e7b837d9bf","added_by":"auto","created_at":"2026-01-28 09:41:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1851193,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8586512/v1/1e9a1127-4135-41b7-ab20-cea152823e26.pdf"},{"id":101269090,"identity":"889d4ccd-5b83-4caa-9e2a-d6b1e37935ac","added_by":"auto","created_at":"2026-01-28 01:27:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":29055,"visible":true,"origin":"","legend":"","description":"","filename":"BMCSTROBEChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-8586512/v1/de716ca069453923a3906e1e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Injury Trends, Costs, and Lost Time in an Australian Meat Processing Facility: A Retrospective Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Australian meat processing industry is among the nation\u0026rsquo;s highest-risk occupational sectors, characterised by repetitive manual handling, cold environments, sharp-tools, and high production demands (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Nationally, approximately 3.5 per cent of employed Australians reported a work-related injury or illness in the 12 months to 2021\u0026ndash;22, with 66 per cent requiring time away from work (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). However, these averages mask the disproportionate burden within meat processing, which records serious injury claim rates several times higher than manufacturing.\u003c/p\u003e \u003cp\u003eGeneral manufacturing reports approximately 9.6 serious injury claims per million hours worked, while meat processing facilities report rates between 19 and 29 claims per million hours (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Workers are exposed to hazards such as continuous knife use, low-temperature environments, carcass lifting, and labour-intensive manual processes. Comparatively, other high-risk sectors such as agriculture (11.1), construction (up to 16.9), and healthcare (10.2) also report high injury rates, although none exhibit the persistent and elevated rates characteristic of meat processing (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWithin red-meat operations, lacerations and musculoskeletal disorders (MSDs) dominate incident reports, together accounting for more than 70% of injuries. Manual handling tasks such as lifting carcasses, shifting heavy product, and stacking boxes contribute to around 45% of claims, while knife-related activities, including cutting, boning, and trimming, account for approximately half of all incidents (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). National data further indicate that traumatic joint, ligament, and muscle or tendon injuries represent about 50% of claims and 36% of total costs, whereas lacerations account for 29% of claims and 21% of costs (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). These figures highlight the need for targeted safety interventions and policy attention.\u003c/p\u003e \u003cp\u003ePre-employment assessments (PEAs) and early intervention programs are increasingly employed as preventive strategies to address the industry\u0026rsquo;s high injury rates. PEAs evaluate an individual\u0026rsquo;s physical capacity, mobility, and overall suitability for physically demanding roles, supporting the principle of \u0026ldquo;person\u0026ndash;job fit\u0026rdquo; and reducing the likelihood of early-tenure injuries (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In the meat processing, PEAs, follow a two-stage process. Stage one involves a self-report questionnaire covering lifestyle factors, medical and injury history, immunisation status, and potential exposure to communicable diseases. It also includes questions about previous injuries, surgeries, or medical conditions that may affect work capacity or increase injury risk. Stage two consists of a one-on-one physiotherapy assessment, including\u0026thinsp;=\u0026thinsp;grip strength, rotator cuff strength, spinal flexion, squatting, lifting (from ground and overhead), pushing strength, range of motion, and hearing via audiometry. The assessment determines whether the individual has sufficient physical capacity for the intended role and identifies any pre-existing conditions that may increase injury risk. Physiotherapy led functional assessments are particularly effective in identifying workers at higher risk of musculoskeletal strain, outperforming traditional medical-only screening models. These assessments typically evaluate strength, flexibility, endurance, and task-specific capabilities such as lifting, carrying, repetitive cutting, and prolonged standing, providing a more accurate prediction of injury susceptibility in physically demanding environments. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eComplementary early-intervention programs such as physiotherapy triage, ergonomic risk modification, and task-readiness training can further reduce injury risk and accelerate recovery where injuries occur (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Evidence suggests that employees who undergo functional screening experience approximately 33 per cent fewer injury claims than unscreened cohorts, while non-screened employees show higher rates of compensation and lost-time claims (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study explores workplace injury patterns, associated costs, and time lost within an Australian meat processing facility over a seven-year period (2018\u0026ndash;2024). Drawing on longitudinal operational and demographic data, it considers trends in injury frequency, severity, and economic impact, with particular attention to musculoskeletal disorders (MSDs) and lacerations the two most common injury categories. The research also considers the introduction of a pre-employment assessment (PEA) program and a physiotherapy-based early intervention strategy implemented from 2018, examining their role in shaping injury outcomes over time.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis study used a retrospective descriptive design to analyse injury and workforce data from a large Australian meat-processing facility over a seven-year period (2018 to 2024). The aim was to identify patterns in injury frequency, severity, associated costs, and time lost due to injury-related absences. A secondary aim was to evaluate the potential influence of pre-employment assessments (PEAs) and early intervention programmes implemented during the study period. Descriptive statistical methods were used to summarise injury counts, claim costs, and hours lost. Temporal trends were visualised using line and bar charts, and scatterplots were used to explore the relationship between claim costs and time lost. No inferential statistical tests were conducted, as the study was designed to describe observed patterns rather than to establish causal relationships.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Sources\u003c/h3\u003e\n\u003cp\u003eData were extracted from multiple organisational sources including, occupational health and safety (OHS) logs, human resources reports, and financial records. The OHS logs provided detailed information on incident type, date of occurrence, severity, and associated claim costs. Human resource reports supplied workforce demographic data, including total employee numbers, new hires by year, and site-specific employment figures. Financial records included compensation costs and wage liabilities related to injury claims. Documentation on the implementation and scope of PEAs and physiotherapy led early intervention strategies was reviewed to contextualise observed injury trends.\u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eInjury events were classified into six categories: burns, critical injuries, foreign body incidents, lacerations, musculoskeletal disorders, and soft tissue injuries. Burns typically involved thermal exposure during processing tasks. Critical injuries represented severe cases such as traumatic head injuries or amputations, foreign body incidents resulted from embedded particles requiring medical removal. Lacerations were primarily knife-related cuts and puncture wounds, while musculoskeletal disorders included strains, sprains, and overuse injuries associated with repetitive manual handling. Soft tissue injuries encompassed bruises and minor trauma without structural damage. The workforce was predominantly male (approximately 95%), with female representation around 5%. The average age of employees was approximately 35 years.\u003c/p\u003e \u003cp\u003eThe primary variables analysed included injury frequency, cost metrics, time lost, and workforce demographics. Injury frequency was assessed by tallying the number of recorded incidents annually, stratified by injury category. Cost metrics included both total and mean claim costs, disaggregated by year and injury type to identify financial trends. Time lost was measured by summing the aggregate hours of absence attributed to injury-related leave. Workforce demographics, including employee counts and turnover, were used to contextualise injury rates and assess organisational stability.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics summarised injury counts, category distribution, claim costs, and time lost. Event counts were aggregated annually and stratified by injury type. Cost analysis involved calculating total and mean claim costs per injury category and year. Measures of variability, including standard deviation, minimum, and maximum values, were computed to identify high-cost outliers. Time lost was assessed by summing hours of absence per injury category and year, enabling evaluation of productivity impacts. Temporal trends were visualised using bar and line plots, while scatterplots explored the relationship between claim costs and time lost. A heatmap was also developed to illustrate the average cost per injury category across the study years. Injury incidence rates were calculated by dividing the number of injury events by the corresponding employee-year exposure and multiplying by 100 to express the rate per 100 employee-years. Employee exposure was calculated using the formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{Employee-Year\\:Exposure}=\\text{Total\\:Employees}\\times\\:\\left(\\frac{\\text{Months\\:Monitored}}{12}\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eExact 95% confidence intervals for these rates were estimated using the Poisson distribution, following the method described by Garwood (1936). All analyses were conducted using Microsoft Excel. Results were validated through cross-checking with original organisational records to ensure accuracy and consistency.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eAll data were anonymised prior to analysis. Injury records did not include individual level identifiers such as ethnicity, age, or sex. The study relied exclusively on existing organisational records and did not involve direct interaction with employees, thereby minimising ethical risk. Ethics approval was granted by the University of Newcastle Human Research Ethics Committee (H-2024-0321). Written informed consent was gained prior to data analysis. The research was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and aligned with the National Health and Medical Research Council (NHMRC) National Statement on Ethical Conduct in Human Research (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003e \u003cb\u003e3.1 Event Trends\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eA total of 273 injuries were recorded between 2018 and 2024. Injury frequency increased markedly over the study period, rising from 7 cases in 2018 to 35 in 2019, and peaking at 73 cases in 2023. This escalation likely reflects heightened operational pressures and workforce instability during the mid study years. A subsequent decline to 44 cases in 2024 coincided with the implementation of PEAs and physiotherapy led early intervention programs. Temporal analysis revealed notable spikes in injury frequency and associated costs during the COVID 19 pandemic years (2020\u0026ndash;2021). These increases reflect labour shortages, workforce turnover, and operational disruptions (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). These trends are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, which shows annual injury counts alongside total claim costs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cem\u003eAnnual Injury Event Counts and Total Claim Costs (2018\u0026ndash;2024)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2 Cost Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe cumulative financial burden of workplace injuries exceeded \u003cspan\u003e$\u003c/span\u003e3.1\u0026nbsp;million across the study period. Musculoskeletal disorders and lacerations were the costliest injuries, together accounting for more than \u003cspan\u003e$\u003c/span\u003e1.63\u0026nbsp;million over half of total compensation costs. Musculoskeletal injuries were particularly expensive due to extended recovery times, physiotherapy requirements, and wage liabilities during prolonged absences. Lacerations, although generally less severe, imposed significant costs due to their high frequency and occasional need for surgical intervention.\u003c/p\u003e \u003cp\u003eCost spikes in 2020 and 2021 aligned with the pandemic period, reflecting the combined effects of operational strain, reduced access to rehabilitation services, and increased reliance on less experienced workers. Critical injuries, including traumatic head injuries and amputations, represented extreme outliers, with individual claims exceeding \u003cspan\u003e$\u003c/span\u003e685,000 dollars in 2021. In contrast, soft tissue injuries and burns, while less frequent, showed cost variability when complications or extended recovery occurred. These patterns highlight the need for targeted prevention strategies and early intervention, particularly for high-cost injury types. These trends are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, which depicts average event cost by injury category and year, and in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, which provides summary statistics for claim costs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary Statistics of Event Costs by Year and Category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (AUD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD (AUD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian (AUD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMin (AUD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMax (AUD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritical Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForeign body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1,765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44,158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73,225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e128,709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1,474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e19,840\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e48,009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,765\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1,051\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e128,709\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritical Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2,640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13,893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59,977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13,777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e35,353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4,935\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11,412\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,733\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e281\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e59,977\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBurns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1,173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForeign body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1,241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75,126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10,716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e462,618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16,751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e26,455\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e100,263\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e741\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e462,618\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritical Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87,158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e241,899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e685,806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28,433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81,407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e329,693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5,327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11,602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16,854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e48,399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e34,800\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e124,451\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,057\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e685,806\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBurns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritical Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28,406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e75,614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForeign body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8,117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e32,551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e28,164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9,985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4,044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11,449\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e677\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e75,614\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBurns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritical Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27,844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60,635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e181,197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForeign body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2,824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6,913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36,446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6,027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8,200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14,497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e42,350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e73\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7,097\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e24,117\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,082\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e181,197\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBurns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4,933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4,981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1,493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8,468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritical Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1,754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForeign body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaceration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4,700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15,200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMusculoskeletal Disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4,283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11,834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16,590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25,654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e66,707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5,374\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11,491\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,379\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e66,707\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAll\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e273\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11,374\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e55,861\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,094\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e685,806\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eSD\u0026thinsp;=\u0026thinsp;Standard Deviation. SD\u0026thinsp;=\u0026thinsp;Standard Deviation. Mean, median, minimum, and maximum values are expressed in Australian dollars (AUD).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.3 Time Lost\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTotal time lost due to injury surpassed 3.63\u0026nbsp;million hours over the study period, reflecting both direct absenteeism and indirect productivity losses from restricted duties and workforce reallocation. Musculoskeletal disorders accounted for approximately 1.3\u0026nbsp;million hours the largest share consistent with their severity and prolonged recovery requirements. These injuries often necessitated extended rehabilitation and gradual return-to-work programs.\u003c/p\u003e \u003cp\u003eLacerations contributed around 935,000 hours, while typically resulting in shorter absences, complex cases requiring surgery drove occasional spikes in lost time. Critical injuries, though rare (30 cases), were highly disruptive, with individual incidents exceeding 500,000 hours lost due to long-term incapacity. The highest cumulative time lost occurred during 2020 and 2021, coinciding with the pandemic. This period was marked by limited access to physiotherapy, increased physical strain, and workforce instability, all of which likely contributed to delayed recovery. In contrast, the reduction in lost time observed in 2024 suggests that the introduction of pre-employment assessments and early physiotherapy may have supported more efficient recovery and return to work. The relationship between claim cost and time lost is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and category-specific trends are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.4 Injury Profile\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAnalysis of injury types revealed that lacerations (n\u0026thinsp;=\u0026thinsp;107, 48.6 percent) and musculoskeletal disorders (n\u0026thinsp;=\u0026thinsp;61, 27.7 percent) were the most common, together comprising over two thirds of all recorded incidents. Soft tissue injuries were the third most frequent (n\u0026thinsp;=\u0026thinsp;34, 15.5 percent), followed by burns (n\u0026thinsp;=\u0026thinsp;8, 3.6 percent), foreign body incidents (n\u0026thinsp;=\u0026thinsp;6, 2.7 percent), and critical injuries (n\u0026thinsp;=\u0026thinsp;4, 1.8 percent). Although infrequent, critical injuries such as amputations and traumatic head injuries contributed disproportionately to total costs and time lost due to their severity and prolonged recovery. These distributions are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and visualised in the heatmap of average cost per injury category across study years (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCost trends highlighted the financial burden of both high-frequency and severe injuries. In 2021. critical injuries had the highest mean claim cost, exceeding AUD \u003cspan\u003e$\u003c/span\u003e87,000 per case. Lacerations, although more frequent, averaged over AUD \u003cspan\u003e$\u003c/span\u003e28,000 per claim, demonstrating that routine injuries can still be costly. Musculoskeletal disorders showed a sharp increase in mean cost in 2020, reaching AUD \u003cspan\u003e$\u003c/span\u003e75,126, likely due to pandemic related delays in treatment and rehabilitation. Soft tissue injuries, while less frequent, also demonstrated cost variability, with mean expenses rising to AUD \u003cspan\u003e$\u003c/span\u003e16,590 in 2024, reflecting the impact of complications on recovery and claims.\u003c/p\u003e \u003cp\u003eThese findings reinforce the importance of targeted prevention strategies addressing both high cost and high frequency injuries. Improvements observed in 2024 suggest that robust screening, ergonomic interventions, and early physiotherapy may contribute to reduce the incidence and severity of workplace injuries, contributing to long term workforce sustainability.\u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eThe decline in injuries from 73 cases in 2023 to 44 in 2024 appears temporally associated with the introduction of pre-employment assessments (PEAs) and physiotherapy-led early intervention programs. These strategies aim to improve workforce readiness and align physical capacity with job demands, consistent with evidence that functional capacity evaluations and early physiotherapy reduce musculoskeletal risk and recovery time (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, causality cannot be inferred due to the retrospective design. Other factors such as improved staffing stability, operational recovery, and reporting practices may have contributed. Regression to the mean following a high-injury year in 2023 is also possible. These findings highlight the need for prospective evaluations to confirm effectiveness.\u003c/p\u003e \u003cp\u003eThe strong association between claim costs and time lost underscores that prolonged recovery drives financial burden, particularly for severe injuries. Pandemic-related spikes in 2020\u0026ndash;2021 illustrate the vulnerability of occupational health systems to external disruptions and emphasize the importance of resilience planning. Musculoskeletal disorders and lacerations remain dominant injury types, indicating that screening alone is insufficient. Integrating ergonomic redesign, knife-handling training, and task-specific conditioning into onboarding and ongoing programs may offer additional benefit.\u003c/p\u003e \u003cp\u003eFrom a policy perspective, these findings reinforce the importance of embedding preventive strategies within industry-wide safety frameworks. Systematic reviews show that interventions targeting musculoskeletal disorders and absenteeism often yield positive return on investment, supporting their inclusion in occupational health standards. For high-risk sectors such as meat processing, combining functional screening with ergonomic and training interventions could reduce injury burden and improve workforce sustainability (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study relied on retrospective data from a single facility, which may limit generalizability. The absence of inferential statistical analysis and potential confounding factors such as workforce turnover and management changes restrict causal interpretation. Additionally, injury reporting practices may have varied over time, influencing observed trends. Future research should address these limitations through multi-site, prospective designs and incorporate qualitative insights into implementation challenges.\u003c/p\u003e \u003cp\u003ePreventive strategies have demonstrated economic and health benefits, but feasibility and scalability require validation through controlled trials. Long-term monitoring will be essential to ensure adaptability during operational stressors such as pandemics or supply chain disruptions. By investing in evidence-based interventions, employers can enhance worker safety, reduce financial burden, and strengthen resilience in physically demanding industries.\u003c/p\u003e "},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the significant burden of workplace injuries in the Australian meat processing industry, with musculoskeletal disorders and lacerations emerging as the most frequent and costly categories. These injuries accounted for the majority of compensation costs and productivity losses, underscoring the need for targeted prevention strategies. The cumulative impact over AUD \u003cspan\u003e$\u003c/span\u003e3.1\u0026nbsp;million in costs and 3.6\u0026nbsp;million hours lost reinforces the economic and operational importance of proactive occupational health measures.\u003c/p\u003e \u003cp\u003eThe observed decline in injuries in 2024 coincided with the introduction of pre-employment assessments and physiotherapy-led early intervention programs, suggesting their potential value in improving workforce readiness and mitigating risk. However, causality cannot be confirmed, and other factors such as staffing stability and operational recovery likely contributed. These findings support a multifaceted approach that combines screening, ergonomic design, and ongoing training to address persistent injury types.\u003c/p\u003e \u003cp\u003eFuture research should focus on prospective, controlled evaluations to determine the effectiveness and cost efficiency of these interventions. Exploring scalability across diverse industrial settings will be critical for informing policy and ensuring sustainable implementation. By investing in evidence-based preventive strategies, employers can enhance worker safety, reduce financial burden, and strengthen resilience in physically demanding sectors\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e Ethical approval for this study was obtained from the University of Newcastle Human Research Ethics Committee (H-2024-0321). The study analysed routinely collected organisational injury and compensation data without identifiable personal information; therefore, consent to participate was not required.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eBR conceptualised the study, conducted the analysis, and drafted the manuscript. AH, JR, and MS contributed to critical revision of the manuscript and provided supervision and methodological guidance. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors acknowledge Michael Fitzgerald for his assistance with statistical analysis and data interpretation. We also acknowledge EC Throsby Pty Ltd and the University of Newcastle for providing in-kind access to organisational injury and compensation data that made this work possible.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analysed during the current study are not publicly available due to commercial and confidentiality agreements with the participating organisation. Data may be made available from the corresponding author on reasonable request and with permission from the organisation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSafe Work Australia. Manual handling in the workplace 2023 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.safeworkaustralia.gov.au/manual-handling\u003c/span\u003e\u003cspan address=\"https://www.safeworkaustralia.gov.au/manual-handling\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Bureau of Statistics. Work-related injuries in Australia: 2022 2023 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.abs.gov.au/statistics/industry/workplace-safety/work-related-injuries/latest-release\u003c/span\u003e\u003cspan address=\"https://www.abs.gov.au/statistics/industry/workplace-safety/work-related-injuries/latest-release\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSafe Work Australia. Key work health and safety statistics, Australia 2024 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.safeworkaustralia.gov.au/insights/key-whs-statistics-australia/latest-release\u003c/span\u003e\u003cspan address=\"https://data.safeworkaustralia.gov.au/insights/key-whs-statistics-australia/latest-release\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Meat Industry Council. Report on the Australian meat processing industry's health and safety practices 2020 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://amic.org.au/wp-content/uploads/2020/10/2020-2021-Annual-Operating-Plan.pdf\u003c/span\u003e\u003cspan address=\"https://amic.org.au/wp-content/uploads/2020/10/2020-2021-Annual-Operating-Plan.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFenner P, RACGP) RACoGP. (. Pre-employment medicals: Addressing the challenges 2011 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.racgp.org.au/getattachment/36f11d49-6663-4953-bace-0445fe339656/The-pre-employment-medical.aspx\u003c/span\u003e\u003cspan address=\"https://www.racgp.org.au/getattachment/36f11d49-6663-4953-bace-0445fe339656/The-pre-employment-medical.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrederieke G, Schaafsma NM, Reneman MF, Fassier JB, Jungbauer FHW. Pre-employment examinations for preventing injury, disease and sick leave in workers. Cochrane Database Syst Reviews. 2016;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePachman J. Evidence base for pre-employment medical screening. Bull World Health Organ. 2009;87(8):529\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNicholas MK, Costa DSJ, Linton SJ, Main CJ, Shaw WS, Pearce G, Gleeson M, Pinto RZ, Blyth FM, McAuley JH, Smeets RJEM, McGarity A. Implementation of Early Intervention Protocol in Australia for \u0026lsquo;High Risk\u0026rsquo; Injured Workers is Associated with Fewer Lost Work Days Over 2 Years Than Usual (Stepped) Care. J Occup Rehabil. 2020;30:93\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRenfrew B, Reis J, Hutton A, Stubbs M. Effectiveness of pre-employment assessments in improving worker health in the meat processing industry: a scoping review. J Public Health. 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaafsma F, Hulshof C, Verbeek J, Bos J, Dyserinck H, van Dijk F. Pre-employment examinations for preventing injury, disease, and sick leave in workers. Cochrane Database Syst Reviews. 2016;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Medical Association. WMA Declaration of Helsinki \u0026ndash; Ethical Principles for Medical Research Involving Human Participants 2005 [Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wma.net/policies-post/wma-declaration-of-helsinki/\u003c/span\u003e\u003cspan address=\"https://www.wma.net/policies-post/wma-declaration-of-helsinki/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegge J, Burgess-Limerick R, Peeters G. A new pre-employment functional capacity evaluation predicts longer-term risk of musculoskeletal injury in healthy workers: a prospective cohort study Spine 2013;38(25).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEsmaeili RS, Esmaeili M, Jalali SV, Babaei Pouya M, Karimi A. A. A multicomponent quasi-experimental ergonomic interventional study: long-term parallel four-groups interventions. BMC Musculoskelet Disord. 2023;24(107).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Occupational health, Meat processing, Injury epidemiology, Workers’ compensation, Workplace safety, Pre-employment assessments, Musculoskeletal disorders, Ergonomics","lastPublishedDoi":"10.21203/rs.3.rs-8586512/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8586512/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMeat processing is one of Australia\u0026rsquo;s highest-risk industrial sectors, yet contemporary epidemiological data describing workplace injury patterns and associated economic burden are limited. This study investigated workplace injury trends, compensation costs, and time lost in an Australian red-meat processing facility over seven years and considered the potential influence of pre-employment assessments (PEAs) and physiotherapy-led early intervention programmes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective descriptive analysis was conducted using organisational injury, compensation, and workforce data from 2018 to 2024. Injuries were categorised as burns, critical injury, foreign body, laceration, musculoskeletal disorder, or soft tissue. Descriptive statistics summarised injury frequency, claim costs, and time lost, and temporal patterns were visualised. Costs were reported in 2024 Australian dollars.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 273 workplace injuries were recorded. Lacerations (48.6%) and musculoskeletal disorders (27.7%) were most common. Cumulative compensation costs exceeded AUD \u003cspan\u003e$\u003c/span\u003e3.1\u0026nbsp;million and total time lost surpassed 3.6\u0026nbsp;million hours. Cost increases during 2020\u0026ndash;2021 aligned with COVID-19-related operational disruptions. Injury frequency decreased from 73 cases in 2023 to 44 cases in 2024 following the introduction of PEAs and physiotherapy-led early intervention; however, causal inference is limited due to study design.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eWorkplace injuries in meat processing impose substantial operational and economic impacts, driven largely by high-frequency laceration and musculoskeletal-related claims. Findings suggest that proactive screening and ergonomic interventions may help to reduce injury burden and improve workforce sustainability. Prospective studies are needed to evaluate the effectiveness and scalability of PEAs and early intervention strategies in high-risk industrial settings.\u003c/p\u003e","manuscriptTitle":"Injury Trends, Costs, and Lost Time in an Australian Meat Processing Facility: A Retrospective Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-28 01:27:43","doi":"10.21203/rs.3.rs-8586512/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-19T05:45:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T04:35:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T05:23:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"232099533776907148543373823941525470784","date":"2026-01-25T13:21:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19593755388113299099809304824987568670","date":"2026-01-22T09:10:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-22T07:58:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-22T07:44:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-22T06:35:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-22T03:06:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-01-22T03:01:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f3a2e42-1505-4fea-b041-7c946381eb06","owner":[],"postedDate":"January 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T11:53:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-28 01:27:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8586512","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8586512","identity":"rs-8586512","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}