Complications, burden and in-hospital death among hospital treated injury patients in Victoria, Australia: a data linkage study

In-hospital complications of work-related musculoskeletal injuries

BACKGROUND, OBJECTIVES

Work-related musculoskeletal (MSK) injuries are a major contributor to morbidity worldwide and frequently result in hospitalisation. Hospital complications are common, costly, and largely preventable, but relevant data is required to address this. This study aimed to identify the incidence and factors associated with in-hospital complications of work-related MSK injuries.

METHODS

This study is based on work-related MSK hospital admission data from Victorian Admitted Episodes Database, 2016-2022. Complications were identified based on ICD-10-AM coding using CHADx (Classification of Hospital Acquired Diagnoses). Negative binomial and logistic regression analyses were performed to identify factors related to in-hospital complications.

RESULTS

In-hospital complications occurred in 6.3 % of work-related MSK injury admissions. In the adjusted models, ages ≥45 years, female sex, and area-level disadvantage were associated with in-hospital complications. Stay at public (vs private) hospitals, comorbidity, emergency admissions, and general anaesthesia were also associated. Complication rates were higher in hospitalised workers with direct head, neck, and trunk injuries and cumulative MSK disorders than those with direct extremities injuries and acute MSK conditions. The most common complications were cardiovascular, gastrointestinal complications and adverse drug events.

CONCLUSION

This study identified patient, injury and hospital-related characteristics associated with in-hospital complications of work-related MSK injuries for informing prevention strategies and risk estimation by hospital staff and workers' compensation schemes. The results demonstrate a sizable rate of complications given the relatively young and healthy study population.

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

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.

International classification of disease based injury severity score (ICISS): A data linkage study of hospital and death data in Victoria, Australia

BACKGROUND

Surveillance of severe injury incidence and prevalence using ICD-based injury severity scores (ICISS) requires valid, locally applicable diagnosis-specific survival probabilities (DSPs). This study aims to derive and validate ICISS in Victoria, Australia, and compare various ICISS methodologies in terms of accuracy and calculated severe injury prevalence.

METHODS

This study used injury admissions (ICD-10-AM coded) from the Victorian Admitted Episodes Database (VAED) linked with death data (Cause of Death - Unit Record Files: CODURF). Using design data (July 2008 - June 2014; n = 720,759), various ICISS scales were derived, based on (i) in-hospital and (ii) three-month mortality. These scales were applied to testing data (July 2014 - December 2016; n = 334,363). Logistic regression modelling was used to determine model discrimination and calibration.

RESULTS

In the design data, there were 6,337(0.9%) hospital deaths and 17,514(2.4%) three-months deaths; in the testing data, there were 2,700(0.8%) hospital deaths and 8,425(2.5%) three-month deaths. Newly developed ICISS scales had acceptable to outstanding discrimination, with Area Under the Curve ranging from 0.758 to 0.910. Age-specific ICISS scales were superior to general ICISS scales in model discrimination but inferior in model calibration. Calculated severe injury (ICISS ≤0.941) prevalence in the testing data ranged from 2% to 24%, depending on which mortality outcomes were used to calculate DRGs.

CONCLUSIONS

This study provides local, validated ICISS scores that can be used in Victoria. It is recommended that age group stratified ICISS based on the worst-injury method is used. From the comparison of various ICISS scores, reflecting the range of ICISS permutations that are currently in use, care should be taken to compare ICISS methodology before comparing severe injury prevalence per population, injury cause, and time trends.

Fatal and Serious Injury Rates for Different Travel Modes in Victoria, Australia

While absolute injury numbers are widely used as a road safety indicator, they do not fully account for the likelihood of an injury given a certain level of exposure. Adjusting crash and injury rates for travel exposure can measure the magnitude of travel activity leading to crash outcomes and provide a more comprehensive indicator of safety. Fatal and serious injury (FSI) numbers were adjusted by three measures of travel exposure to estimate crash and injury rates across nine travel modes in the Australian state of Victoria. While car drivers accounted for the highest number of injuries across the three modes, their likelihood of being killed or seriously injured was substantially lower than that of motorcyclists across all exposure measures. Cyclists accounted for fewer injuries than car passengers and pedestrians but had a higher risk per exposure. The results varied by both injury severity and exposure measure. The results of this study will assist with high level transport planning by allowing for the investigation of the changes in travel-related FSI resulting from proposed travel mode shifts driven by safety, environmental reasons or other reasons as part of the holistic goal of transforming the transport system to full compliance with Safe System principles.

Australian Injury Comorbidity Indices (AICIs) to predict burden and readmission among hospital-admitted injury patients

BACKGROUND

Existing comorbidity measures predict mortality among general patient populations. Due to the lack of outcome specific and patient-group specific measures, the existing indices are also applied to non-mortality outcomes in injury epidemiology. This study derived indices to capture the association between comorbidity, and burden and readmission outcomes for injury populations.

METHODS

Injury-related hospital admissions data from July 2012 to June 2014 (161,334 patients) for the state of Victoria, Australia were analyzed. Various multivariable regression models were run and results used to derive both binary and weighted indices that quantify the association between comorbidities and length of stay (LOS), hospital costs and readmissions. The new and existing indices were validated internally among patient subgroups, and externally using data from the states of New South Wales and Western Australia.

RESULTS

Twenty-four comorbidities were significantly associated with overnight stay, twenty-seven with LOS, twenty-eight with costs, ten with all-cause and eleven with non-planned 30-day readmissions. The number of and types of comorbidities, and their relative impact were different to the associations established with the existing Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Measure (ECM). The new indices performed equally well to the long-listed ECM and in certain instances outperformed the CCI.

CONCLUSIONS

The more parsimonious, up to date, outcome and patient-specific indices presented in this study are better suited for use in present injury epidemiology. Their use can be trialed by hospital administrations in resource allocation models and patient classification models in clinical settings.

Occupational and non-occupational injuries can result in prolonged augmentation of psychiatric disorders

Background

The long-term effects of occupational injury (OI) on psychiatric diseases are unclear. This study assessed and compared the effects of OI, no injury (control), and non-OI (NOI) on the development of psychiatric diseases.

Methods

We used Taiwan’s National Health Insurance Research Database to investigate the incidence of psychiatric disorders in OI, NOI, and control groups. The subjects were aged 20–50 years, actively employed in 2000, and did not have history of injury or psychiatric disorders. All subjects were followed from 2000 and were classified into OI, NOI, and control groups according to occurrence of target injury later on. Individuals in each group were matched by age, sex, insurance premium before the index date, and year of the index date. Psychiatric disease-free days were compared among the groups using survival analysis and Cox regression.

Results

We included a total of 12,528 patients for final analysis, with 4,176 in each group. Compared with the control group, the OI group had an increased occurrence of trauma and stress-related disorder, depressive disorders, anxiety disorders, and alcohol and other substance dependence. These increases were similar to those in the NOI group. Elevated cumulative incidence rate of any psychiatric disorders was observed among those with OI or NOI up to 10 years after injury.

Conclusion

We confirmed that OI and NOI induced psychiatric disorders. These findings highlight the need for workers’ compensation mechanisms to consider long-term psychological care among injured workers.

The Australian Injury Comorbidity Indices (AICIs) to predict in-hospital complications: A population-based data linkage study

Background

Hospital-admitted patients are at risk of experiencing certain adverse outcomes during their hospital-stay. Patients may need to be admitted to the intensive care unit or be placed on the ventilator while there is also a possibility for complications to develop. Pre-existing comorbidity could increase the risk of these outcomes. The Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Measure (ECM), originally derived for mortality outcomes among general medical populations, are widely used for assessing these in-hospital complications even among specific injury populations. This study derived indices to specifically capture the effect of comorbidity on intensive care unit and ventilator use as well as hospital-acquired complications for injury patients.

Methods

Retrospective data on injury hospital-admissions from July 2012 to June 2014 (161,334 patients) for the state of Victoria, Australia was analysed. Results from multivariable regression analysis were used to derive the Australian Injury Comorbidity Indices (AICIs) for intensive care unit and ventilator hours and hospital-acquired complications. The AICIs, CCI and ECM were validated on data from Victoria and two other Australian states.

Results

Five comorbidities were significantly associated with intensive care unit hours, two with ventilator hours and fifteen with hospital-acquired complications for hospitalised injury patients. Not all diseases listed in the CCI or ECM were found to be associated with these outcomes. The AICIs performed equally well in terms of predictive ability to the long-listed ECM and in most instances outperformed the CCI.

Conclusions

Associations between outcomes and comorbidities vary based on the type of outcome measure. The new comorbidity indices developed in this study provide a relevant, parsimonious and up-to-date method to capture the effect of comorbidity on in-hospital complications among admitted injury patients and is better suited for use in that context compared to the CCI and ECM.