The epidemiology of life‐threatening work‐related injury—A demonstration paper

Cryer, Colin; Samaranayaka, Ari; Langley, John Desmond; Davie, Gabrielle

doi:10.1002/ajim.22301

Cited by 8 publications

(7 citation statements)

References 31 publications

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“…Outcomes of injury included length of hospital stay and injury severity. Injury severity was calculated using the ICD-based Injury Severity Score (ICISS) (Osler et al, 1996), a serious injury was considered to be one with an ICISS less than 0.941 (survival probability of 94.1% or less) (Cryer et al, 2008). Computation of the ICISS was based on injury diagnosis, a survival risk ratio (SRR) (proportion of survivors among all patients with that particular ICD-10-AM diagnosis) using the worst injury method (Henley and Harrison, 2009).…”

Section: Variables and Data Measurementsmentioning

confidence: 99%

Intentional self-harm in culturally and linguistically diverse communities: A study of hospital admissions in Victoria, Australia

Pham

O’Brien

Berecki‐Gisolf

et al. 2021

Aust N Z J Psychiatry

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Purpose: To examine the rates and profiles of intentional self-harm hospital admissions among people from culturally and linguistically diverse and non-culturally and linguistically diverse backgrounds. Methods: A retrospective analysis of 29,213 hospital admissions for self-harm among people aged 15 years or older in Victoria, Australia, was conducted using data from the Victorian Admitted Episodes Dataset between 2014/2015 and 2018/2019. The Victorian Admitted Episodes Dataset records all hospital admissions in public and private hospitals in Victoria (population 6.5 million). Population-based incidence of self-harm, logistic regression and percentages (95% confidence intervals) were calculated to compare between culturally and linguistically diverse groups by birthplaces and the non-culturally and linguistically diverse groups of self-harm admissions. Results: When grouped together culturally and linguistically diverse individuals had lower rates of (hospital-treated) self-harm compared with the non-culturally and linguistically diverse individuals. However, some culturally and linguistically diverse groups such as those originating from Sudan and Iran had higher rates than non-culturally and linguistically diverse groups. Among self-harm hospitalised patients, those in the culturally and linguistically diverse group (vs non-culturally and linguistically diverse group) were more likely to be older, Metropolitan Victorian residents, from the lowest socioeconomic status, and being ever or currently married. Self-harm admissions by persons born in Southern and Eastern Europe were the oldest of all groups; in all other groups number of admissions tended to decrease as age increased whereas in this group the number of admissions increased as age increased. Conclusion: There was considerable heterogeneity in rates of hospital-treated self-harm in culturally and linguistically diverse communities, with some countries of origin (e.g. Sudan, Iran) having significantly higher rates. Some of this variation may be due to factors relating to the mode of entry into Australia (refugee vs planned migration), and future research needs to examine this possibility and others, to better plan for support needs in the culturally and linguistically diverse communities most affected by self-harm. Combining all culturally and linguistically diverse people into one group may obscure important differences in self-harm. Different self-harm prevention strategies are likely to be needed for different culturally and linguistically diverse populations.

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Section: Variables and Data Measurementsmentioning

confidence: 99%

Intentional self-harm in culturally and linguistically diverse communities: A study of hospital admissions in Victoria, Australia

Pham

O’Brien

Berecki‐Gisolf

et al. 2021

Aust N Z J Psychiatry

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“…Mortality is often not fully captured in WC data, making the use of predictive injury severity models, such as the ICD-based Injury Severity Score (ICISS) [28], more challenging.…”

Section: Introductionmentioning

confidence: 99%

A New Method to Classify Injury Severity by Diagnosis: Validation Using Workers’ Compensation and Trauma Registry Data

Sears

Bowman

Rotert³

et al. 2015

J Occup Rehabil

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Purpose Acute work-related trauma is a leading cause of death and disability among U.S. workers. Existing methods to estimate injury severity have important limitations. This study assessed a severe injury indicator constructed from a list of severe traumatic injury diagnosis codes previously developed for surveillance purposes. Study objectives were to: (1) describe the degree to which the severe injury indicator predicts work disability and medical cost outcomes; (2) assess whether this indicator adequately substitutes for estimating Abbreviated Injury Scale (AIS)-based injury severity from workers' compensation (WC) billing data; and (3) assess concordance between indicators constructed from Washington State Trauma Registry (WTR) and WC data. Methods WC claims for workers injured in Washington State from 1998-2008 were linked to WTR records. Competing risks survival analysis was used to model work disability outcomes. Adjusted total medical costs were modeled using linear regression. Information content of the severe injury indicator and AIS-based injury severity measures were compared using Akaike Information Criterion and R2. Results Of 208,522 eligible WC claims, 5% were classified as severe. Among WC claims linked to the WTR, there was substantial agreement between WC-based and WTR-based indicators (kappa=0.75). Information content of the severe injury indicator was similar to some AIS-based measures. The severe injury indicator was a significant predictor of WTR inclusion, early hospitalization, compensated time loss, total permanent disability, and total medical costs. Conclusions Severe traumatic injuries can be directly identified when diagnosis codes are available. This method provides a simple and transparent alternative to AIS-based injury severity estimation.

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“…With the worst-injury method, 22 a serious injury was considered to be one with an ICD-based Injury Severity Score less than or equal to 0.941 (survival probability of 94.1%). 23 Geographic regions were classified as metropolitan and regional, using the local government area of residence in both states. Socio Economic Indexes for Areas-Index of Relative Socio-Economic Advantage and Disadvantage expressed as state-deciles 24 was used to classify the socioeconomic status.…”

Section: Methodsmentioning

confidence: 99%

The Australian Injury Comorbidity Index to Predict Mortality

Fernando

Berecki‐Gisolf

Newstead

et al. 2020

Annals of Emergency Medicine

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Study objective: Existing comorbidity indices such as the Charlson comorbidity index are dated yet still widely used. This study derives and validates up-to-date comorbidity indices for hospital-admitted injury patients, specific to mortality outcomes. Methods: Injury-related hospital admissions data for 2 cohorts of patients in the Australian state of Victoria were linked to mortality data: July 2012 to June 2014 (161,334 patients) and July 2006 to June 2015 (614,762 patients). Logistic regression models were fitted, and results were used to derive binary and weighted comorbidity indices to predict mortality outcomes. The indices were validated with data from New South Wales (Australia). Results: There were 11 comorbidity groups identified as associated with inhospital death (cohort 1), 13 with 30-day mortality, and 19 with 1-year mortality (cohort 2). The newly derived weights for comorbidities were very different from the Charlson comorbidity index weights for some conditions. The area under the curve statistics for inhospital death, 30-day mortality, and 1-year mortality were similar for the newly derived binary comorbidity indices (0.920, 0.923, and 0.910, respectively), the Charlson comorbidity index (0.915, 0.919, and 0.906, respectively), and the Elixhauser comorbidity measure (0.924, 0.923, and 0.908, respectively). The false-negative rates for the new binary indices (15.8%, 15.8%, and 16.3%, respectively) were statistically equal to those of the Charlson comorbidity index (17.4%, 16.3%, and 16.5%, respectively) and the Elixhauser comorbidity measure (15.2%, 14.8%, and 16.3%, respectively). Conclusion: The newly derived Australian Injury Comorbidity Indices, which are a binary representation of individual conditions associated with the outcome of interest, are useful in quantifying the effect of comorbidity among injury patients. They include a shorter list of conditions than existing indices such as the Charlson comorbidity index and Elixhauser comorbidity measure, are up to date, and consider the individual association of each condition over a summed score such as the Charlson comorbidity index. Indices that quantify the effect of comorbidities should consider the population, disease prevalence, and outcome of interest and require periodic updating. [

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The epidemiology of life‐threatening work‐related injury—A demonstration paper

Abstract: The method presented provides the opportunity for government agencies to produce a national description of the epidemiology of serious TTL work-related injuries.

Cited by 8 publications

References 31 publications

Intentional self-harm in culturally and linguistically diverse communities: A study of hospital admissions in Victoria, Australia

Intentional self-harm in culturally and linguistically diverse communities: A study of hospital admissions in Victoria, Australia

A New Method to Classify Injury Severity by Diagnosis: Validation Using Workers’ Compensation and Trauma Registry Data

The Australian Injury Comorbidity Index to Predict Mortality

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