ORCID Profile
0000-0003-2423-3784
Current Organisations
Monash University
,
Department of Health
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Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.ANNEPIDEM.2019.06.004
Abstract: Accounting for comorbidity in predicting outcomes for patients is vital in clinical care, epidemiological research, and health service planning. The aim of this study was to review published literature to compare the performance of existing comorbidity indices and their use in injury populations. A thematic literature search for comorbidity indices and/or injury outcomes was conducted. Methods, results, and recommendations from selected articles were abstracted, documented, and compared comparisons of results were made in terms of the indices' ability to predict outcomes, using the C-statistic, R Fifty-two articles relating to the derivation and/or validation of comorbidity measures were found. The most commonly used measures were the Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Measure (ECM). The ECM was found to outperform the CCI in terms of predictive ability, although the CCI was more widely used. Derivation of study-specific weights to the CCI added more predictive power to the index. Existing literature that compared the predictive abilities of the ECM and CCI favors the ECM. This literature review did not identify a measure specifically designed for general injury populations. Development of an injury-specific comorbidity measure will be timely and assist future research in injury epidemiology.
Publisher: Springer Science and Business Media LLC
Date: 21-06-2019
Publisher: Public Library of Science (PLoS)
Date: 11-07-2022
DOI: 10.1371/JOURNAL.PONE.0271341
Abstract: The majority of suicide decedents have had contact with health services close to their death. Some of these contacts include admissions to hospitals for physical and mental health conditions, injury and intentional self-harm. This study aims to establish and quantify the risks of suicide following hospital admission for a range of mental and physical illnesses. A retrospective analysis was carried out on existing morbidity and mortality data in Victoria. Data was extracted from the Victorian Admitted Episodes Dataset and the Victorian Suicide Register. Unplanned hospital admissions among adult patients ( = 15 years of age), discharged between 01 January 2011 and 31 December 2016 (2,430,154 admissions), were selected. Standardised Mortality Ratios were calculated for conditions with at least five linked suicides within one year of discharge from hospital. Forty-three conditions defined at the three-digit level of the International Statistical Classification of Diseases and Related Health Problems 10th Revision, were associated with at least five subsequent suicides (within one year of hospital discharge) 14 physical illnesses, 5 symptoms, signs and abnormal clinical and laboratory findings, 12 mental health conditions, and 12 types of injury and poisonings. The highest Standardised Mortality Ratios were for poisonings (range 27.8 to 140.0) and intentional self-harm (78.8), followed by mental health conditions (range 15.5 to 72.9), symptoms, signs and abnormal clinical and laboratory findings (range 1.4 to 43.2) and physical illnesses (range 0.7 to 4.9). Hospital admissions related to mental health conditions and injury and poisonings including self-harm were associated with a greater risk of suicide than physical conditions. Mental health conditions such as depressive episodes, personality disorders and psychotic episodes, injuries caused by intentional-self-harm and poisonings by certain types of drugs, carbon monoxide and hormones such as insulin can be prioritised for targeting suicide prevention initiatives for persons discharged from hospitals.
Publisher: AMPCo
Date: 04-2018
DOI: 10.5694/MJA17.00872
Publisher: Springer Science and Business Media LLC
Date: 15-02-2021
DOI: 10.1186/S12913-021-06149-1
Abstract: 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. 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. 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. 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.
Publisher: BMJ
Date: 12-2022
DOI: 10.1136/BMJOPEN-2022-063115
Abstract: The Victorian Emergency Minimum Dataset (VEMD) is a key data resource for injury surveillance. The VEMD collects emergency department data from 39 public hospitals across Victoria however, rural emergency care services are not well captured. The aim of this study is to determine the representativeness of the VEMD for injury surveillance. A retrospective observational study of administrative healthcare data. Injury admissions in 2014/2015–2018/2019 were extracted from the Victorian Admitted Episodes Dataset (VAED) which captures all Victorian hospital admissions only cases that arrived through a hospital’s emergency department (ED) were included. Each admission was categorised as taking place in a VEMD-contributing versus a non-VEMD hospital. There were 535 477 incident injury admissions in the study period, of which 517 207 (96.6%) were admitted to a VEMD contributing hospital. Male gender (OR 1.13 (95% CI 1.10 to 1.17)) and young age (age 0–14 vs 45–54 years, OR 4.68 (95% CI 3.52 to 6.21)) were associated with VEMD participating (vs non-VEMD-participating) hospitals. Residing in regional/rural areas was negatively associated with VEMD participating (vs non-VEMD participating) hospitals (OR=0.11 (95% CI 0.10 to 0.11)). Intentional injury (assault and self-harm) was also associated with VEMD participation. VEMD representativeness is largely consistent across the whole of Victoria, but varies vastly by region, with substantial under-representation of some areas of Victoria. By comparison, for injury surveillance, regional rates are more reliable when based on the VAED. For local ED-presentation rates, the bias analysis results can be used to create weights, as a temporary solution until rural emergency services injury data is systematically collected and included in state-wide injury surveillance databases.
Publisher: Elsevier BV
Date: 05-2022
DOI: 10.1016/J.BURNS.2021.06.007
Abstract: To describe incidence and characteristics of hospital presentations and deaths due to burn injury in the Australian state of Victoria from 2008 to 2017 and identify trends in incidence and patterns. Three population-based datasets were used to ascertain burn-related hospital admissions, emergency department presentations, and deaths. These were the Victorian Admitted Episodes Dataset (VAED), Victorian Emergency Minimum Dataset (VEMD), and the Cause of Death-Unit Record File (COD-URF), respectively. Descriptive statistics on demographics (age and gender), burn injury characteristics (intent, cause, burn size and body region) and hospital burden (length of stay (LOS) and costs) were used to present the profile of patients. Incidence rates by age, gender and intent were calculated. Trend analysis on incidence was carried out using forced Poisson Regression models with the natural logarithm of the annual populations as an offset. Incident rate ratios were used to interpret the models. Risk ratios were used to compare the risk differences between population sub-groups. A negative binomial model was used to test the association between LOS and age and the total body surface area (TBSA) of the burn. Overall males had higher rates of death, admission and ED presentation. For adults, the elderly had the highest rates of deaths and admissions while for children, the very young had highest rates for admissions and presentations. Exposure to smoke, fire and flames was the most common cause of deaths, and contact with heat and hot substances was most common among ED presentations. The elderly and those with Total Body Surface Area (TBSA) burn ≥20% had a higher risk of longer hospital stay. Rates of severe burns and deaths from burns remained stable during the study period in the setting of an annual 2% increase in population. Paediatric hospital admission rates decreased over time. The risk of sustaining burn injury, the types of burn and outcomes, varied by age and gender. We found evidence of a limited decrease in burn injury rates in some sub-groups: appropriate and effective targeted prevention strategies for burns are needed to avoid the significant short and long-term suffering experienced.
Publisher: Public Library of Science (PLoS)
Date: 11-09-2020
Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.ANNEMERGMED.2019.10.003
Abstract: 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. 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). 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). The newly derived Australian Injury Comorbidity Indices, which are a binary representation of in idual 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 in idual 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.
No related grants have been discovered for Dasamal Fernando.