Sickness certification of workers compensation claimants by general practitioners in Victoria, 2003-2010

Objective: To examine patterns of the sickness certification of workers compensation claimants by general practitioners in Victoria, Australia, by nature of injury or illness. Design, setting and patients: Retrospective analysis of Victorian workers compensation data for all injured and ill workers with an accepted workers compensation claim between 2003 and 2010. Main outcome measures: Type (unfit for work, alternative duties, or fit for work) and duration of initial medical certificates relating to workers compensation claims that were issued by GPs, in six categories of injury and illness. Results: Of 124 424 initial medical certificates issued by GPs, 74.1% recommended that workers were unfit for work and 22.8% recommended alternative duties. Unfit-for-work certificates were issued to 94.1% of workers with mental health conditions, 81.3% of those with fractures, 79.1% of those with other traumatic injuries, 77.6% of those with back pain and strains, 68.0% of those with musculoskeletal conditions and 53.0% of those with other diseases. Alternative-duties certificates were significantly longer in duration than unfit-for-work certificates in all injury and illness categories (P<0.001) but certificates for workers with musculoskeletal injuries and diseases, back pain and strains and other traumatic injuries were of lesser duration than those for workers with fractures, mental health conditions and other diseases. Conclusion: The high proportion of medical certificates recommending complete absence from work presents major challenges in terms of return to work, labour force productivity, the viability of the compensation system, and long-term social and economic development. There is substantial variation in the type and duration of medical certificates issued by GPs. People with mental health conditions are unlikely to receive a certificate recommending alternative duties. Further research is required to understand GP certification behaviour

A retrospective analysis of Victorian and South Australian clinical registries for prostate cancer: trends in clinical presentation and management of the disease

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Abstract Background: Prostate cancer (PCa) is the most commonly diagnosed malignancy reported to Australian cancer registries with numerous studies from individual registries summarizing diagnostic and treatment characteristics. The aim of this study was to describe annual trends in clinical and treatment characteristics, and changes in surveillance practice within a large combined cohort of men with PCa in South Australia (SA) and Victoria, Australia in 2008–2013. Methods: Common data items from clinical registries in SA and Victoria were merged to develop a crossjurisdictional dataset consisting of 13,598 men with PCa. Frequencies were used to describe these variables using the National Comprehensive Cancer Network risk of disease progression categories in 10 year age groups. A logistic regression analysis was performed to assess the impact of a number of factors (both individually and together) on the likelihood of men receiving no active treatment within twelve months of the diagnosis (i.e. managed with active surveillance/watchful waiting). Results: Trend analysis showed that over time: (1) men in SA and Victoria are being diagnosed at older age in 2013, 66.1 (SD = 9.7) years compared to 2009 (64.5 (SD = 9.7)); (2) diagnostic methods and characteristics have changed with time; and (3) types of the treatments have changed, with more men having no active treatment. The majority of men were diagnosed with Prostate-Specific Antigen (PSA) <10 ng/mL (66 %) and Grade Group < 4 (65 %). Nearly seventy percent received radical treatment within 12 months of diagnosis, while ~20 % had no active treatment. In 14 % of cases treatment was not recorded or had not commenced. Having no active treatment was strongly associated older age, lower PSA and lower Grade Group at diagnosis, and in 2013 it was offered more frequently (more than 3 times) than in 2009 (OR = 2.63, 95 % CI: 2.16–3.22). Conclusions: Findings of this study provide the first cross-jurisdictional description of PCa characteristics and management in Australia. These findings will provide benchmarking for ongoing monitoring and feedback of disease management and outcomes of PCa through the Prostate Cancer Outcomes Registry–Australia New Zealand to improve evidence-based practice

Development of South Australian-Victorian Prostate Cancer Health Outcomes Research Dataset

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.BACKGROUND: Prostate cancer is the most commonly diagnosed and prevalent malignancy reported to Australian cancer registries, with numerous studies from single institutions summarizing patient outcomes at individual hospitals or States. In order to provide an overview of patterns of care of men with prostate cancer across multiple institutions in Australia, a specialized dataset was developed. This dataset, containing amalgamated data from South Australian and Victorian prostate cancer registries, is called the South Australian-Victorian Prostate Cancer Health Outcomes Research Dataset (SA-VIC PCHORD). RESULTS: A total of 13,598 de-identified records of men with prostate cancer diagnosed and consented between 2008 and 2013 in South Australia and Victoria were merged into the SA-VIC PCHORD. SA-VIC PCHORD contains detailed information about socio-demographic, diagnostic and treatment characteristics of patients with prostate cancer in South Australia and Victoria. Data from individual registries are available to researchers and can be accessed under individual data access policies in each State. CONCLUSIONS: The SA-VIC PCHORD will be used for numerous studies summarizing trends in diagnostic characteristics, survival and patterns of care in men with prostate cancer in Victoria and South Australia. It is expected that in the future the SA-VIC PCHORD will become a principal component of the recently developed bi-national Australian and New Zealand Prostate Cancer Outcomes Registry to collect and report patterns of care and standardised patient reported outcome measures of men nation-wide in Australia and New Zealand

Development of a percutaneous coronary intervention patient level composite measure for a clinical quality registry

© 2020 The Author(s). Background: Composite measures combine data to provide a comprehensive view of patient outcomes. Despite composite measures being a valuable tool to assess post-intervention outcomes, the patient perspective is often missing. The purpose of this study was to develop a composite measure for an established cardiac outcome registry, by combining clinical outcomes following percutaneous coronary interventions (PCI) with a patient-reported outcome measure (PROM) developed specifically for this population (MC-PROM). Methods: Two studies were undertaken. Study 1: Patients who had undergone a PCI at one of the three participating registry hospital sites completed the 5-item MC-PROM. Clinical outcome data for the patients (e.g. death, myocardial infarction, repeat vascularisation, new bleeding event) were collected 30 days post-intervention as part of routine data collection for the cardiac registry. Exploratory factor analysis of clinical outcomes and MC-PROM data was conducted to determine the minimum number of constructs to be included in a composite measure. Study 2: Clinical experts participated in a Delphi technique, consisting of three rounds of online surveys, to determine the clinical outcomes to be included and the weighting of the clinical outcomes and MC-PROM score for the composite measure. Results: Study 1: Routine clinical outcomes and the MC-PROM data were collected from 266 patients 30 days post PCI. The MC-PROM score was not significantly correlated with any clinical outcomes. Study 2: There was a relatively consistent approach to the weighting of the clinical outcomes and MC-PROM items by the expert panel (n = 18) across the three surveys with the exception of the clinical outcome of 'deceased at 30 days'. The final composite measure included five clinical outcomes within 30 days weighted at 90% (new heart failure, new myocardial infarction, new stent thrombosis, major bleeding event, new stroke, unplanned cardiac rehospitalisation) and the MC-PROM score (comprising 10% of the total weighting). Conclusions: A single patient level composite score, which incorporates weighted clinical outcomes and a PROM was developed. This composite score provides a more comprehensive reported measure of individual patient wellbeing at 30 days post their PCI-procedure, and may assist clinicians to further assess and address patient level factors that potentially impact on clinical recovery

Bayesian D-Optimal Choice Designs for Mixtures

__Abstract__ \n \nConsumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondents\' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set. \n \nHowever, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating an optimal design for such choice experiments. To this end, we first introduce mixture models in the choice context and next present an algorithm to construct optimal experimental designs, assuming the multinomial logit model is used to analyze the choice data. To overcome the problem that the optimal designs depend on the unknown parameter values, we adopt a Bayesian D-optimal design approach. We also consider locally D-optimal designs and compare the performance of the resulting designs to those produced by a utility-neutral (UN) approach in which designs are based on the assumption that individuals are indifferent between all choice alternatives. We demonstrate that our designs are quite different and in general perform better than the UN designs

What is return to work? An investigation into the quantification of return to work

PURPOSE: To describe and demonstrate issues with return to work (RTW) outcome metrics in common use among clinical researchers and injury compensation organisations. We also aim to describe a framework on which to capture relevant RTW information including current employment status and data on participation and maintenance. METHODS: Structured telephone interviews discussing participant health and vocational status were conducted following compensable transport-related injury. Participants who were working at the time of injury and took time off work because of their injuries (N = 414) were asked questions relating to their work participation and maintenance, including length of continuous employment, hours worked and duties performed before and after injury. A series of RTW metrics was developed and applied to survey data. Rates of RTW according to each metric were calculated. RESULTS: Eighty-four per cent of participants had achieved some employment since their injury, and 74% were working at the time of the survey. In contrast, only 58% of participants were working the same hours as prior to their injury and had been doing so for at least 3 months. These data show that different impressions of rehabilitative success can be obtained depending on the criterion used to define RTW suggesting that reliance on a single RTW index (e.g. 'are you currently working?') will not represent important characteristics of employment. CONCLUSION: A multi-layered approach to measuring RTW that includes data on reasons for not working, length of continuous employment, hours and duties performed after injury provides greater insight into the vocational status of injured individuals compared to single metrics or outcomes that fail to capture key detail on motives and participation. This information can assist clinicians to more accurately monitor the progress of rehabilitation following injury and compensation schemes to more effectively monitor their performance