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The rail industry in Australia screens workers for probable obstructive sleep apnea (OSA) due to known safety risks. However, existing criteria to trigger screening only identify a small proportion of workers with OSA. The current study sought to examine the relationship between OSA risk and rail incidents in real-world data from Australian train drivers, and conducted a proof of concept analysis to determine whether more conservative screening criteria are justified. Health assessment (2016–2018) and subsequent rail incident data (2016–2020) were collected from two passenger rail service providers. Predictors included OSA status (confirmed no OSA with a sleep study, controlled OSA, unknown OSA [no recorded sleep assessment data] and confirmed OSA with no indication of treatment); OSA risk according to the current Standard, and OSA risk according to more conservative clinical markers (BMI threshold and cardiometabolic burden). Coded rail safety incidents involving the train driver were included. Data were analysed using zero-inflated negative binomial models to account for over-dispersion with high 0 counts, and rail safety incidents are reported using Incidence Risk Ratios (IRRs). A total of 751 train drivers, typically middle-aged, overweight to obese and mostly men, were included in analyses. There were 43 (5.7%) drivers with confirmed OSA, 62 (8.2%) with controlled OSA, 13 (1.7%) with confirmed no OSA and 633 (84.4%) drivers with unknown OSA. Of the 633 train drivers with unknown OSA status, 21 (3.3%) met 'at risk' criteria for OSA according to the Standard, and incidents were 61% greater (IRR: 1.61, 95% Confidence Interval (CI) 1.02–2.56) in the years following their health assessment compared to drivers who did not meet 'at risk' criteria. A more conservative OSA risk status using lower BMI threshold and cardiometabolic burden identified an additional 30 'at risk' train drivers who had 46% greater incidents compared to drivers who did not meet risk criteria (IRR (95% CI) 1.46 (1.00–2.13)). Our more conservative OSA risk criteria identified more workers, with greater prospective incidents. These findings suggest that existing validated tools could be considered in future iterations of the Standard in order to more sensitively screen for OSA. [ABSTRACT FROM AUTHOR]

Background: On-call research and guidance materials typically focus on 'traditional' on-call work (e.g., emergency services, healthcare). However, given the increasing prevalence of non-standard employment arrangements (e.g., gig work and casualisation), it is likely that a proportion of individuals who describe themselves as being on-call are not included in current on-call literature. This study therefore aimed to describe the current sociodemographic and work characteristics of Australian on-call workers. Methods: A survey of 2044 adults assessed sociodemographic and work arrangements. Of this population, 1057 individuals were workforce participants, who were asked to provide information regarding any on-call work they performed over the last three months, occupation type, weekly work hours, and the presence or absence of non-standard work conditions. Results: Of respondents who were working, 45.5% reported working at least one day on-call in the previous month. There was a high prevalence of on-call work in younger respondents (63.1% of participants aged 18–24 years), and those who worked multiple jobs and more weekly work hours. Additionally, high prevalence rates of on-call work were reported by machinery operators, drivers, community and personal service workers, sales workers, and high-level managers. Conclusions: These data suggest that on-call work is more prevalent than previously recorded and is likely to refer to a broad set of employment arrangements. Current classification systems may therefore be inadequate for population-level research. A taxonomy for the classification of on-call work is proposed, incorporating traditional on-call work, gig economy work, relief, or unscheduled work, and out of hours work. [ABSTRACT FROM AUTHOR]

Background: Chronic insomnia is a highly prevalent disorder, with ten to thirty percent of Australian adults reporting chronic difficulties falling asleep and/or staying asleep such that it causes significant daytime impairment. Current Australian general practice guidelines recommend cognitive behavioural therapy for insomnia (CBTi) as first line treatment for insomnia, however research suggests that most general practice consultations for insomnia result in a prescription for hypnotic or sedative medicines. Although the first point of contact for patients experiencing symptoms of insomnia is often general practice, little is known about the current role, experiences and capacity of Australian general practitioners to manage insomnia. This study aimed to address that gap by exploring the attitudes and opinions of general practitioners regarding insomnia management, to inform the development and implementation of new models of best practice insomnia care within general practice. Methods: A descriptive, pragmatic qualitative study. Purposive sampling was used to recruit practising Australian general practitioners, varying in age, years of experience and geographic location. Semi-structured interviews were conducted, and data analysed using thematic analysis. Results: Twenty-eight general practitioners participated in the study. Three major themes were identified: 1) Responsibility for insomnia care; 2) Complexities in managing insomnia; and 3) Navigating treatment pathways. Whilst general practitioners readily accepted responsibility for the management of insomnia, provision of care was often demanding and difficult within the funding and time constraints of general practice. Patients presenting with comorbid mental health conditions and insomnia, and decision-making regarding long-term use of benzodiazepines presented challenges for general practitioners. Whilst general practitioners confidently provided sleep hygiene education to patients, their knowledge and experience of CBTi, and access and understanding of specialised referral pathways for insomnia was limited. Conclusions: General practitioners report that whilst assessing and managing insomnia can be demanding, it is an integral part of general practice. Insomnia presents complexities for general practitioners. Greater clarity about funding options, targeted education about effective insomnia treatments, and referral pathways to specialist services, such as benzodiazepine withdrawal support and psychologists, would benefit insomnia management within general practice. [ABSTRACT FROM AUTHOR]

Background frailty is a dynamic condition for which a range of interventions are available. Health state utilities are values that represent the strength of an individual's preference for specific health states, and are used in economic evaluation. This is a topic yet to be examined in detail for frailty. Likewise, little has been reported on minimally important difference (MID), the extent of change in frailty status that individuals consider to be important. Objectives to examine the relationship between frailty status, for both the frailty phenotype (FP) and frailty index (FI), and utility (preference-based health state), and to determine a MID for both frailty measures. Design and setting population-based cohort of community-dwelling Australians. Participant in total, 874 adults aged ≥65 years (54% female), mean age 74.4 (6.2) years. Measurements frailty was measured using the FP and FI. Utilities were calculated using the short-form 6D health survey, with Australian and UK weighting applied. MID was calculated cross-sectionally. Results for both the FP and FI, frailty was significantly statistically associated (P  < 0.001) with lower utility in an adjusted analysis using both Australian and UK weighting. Between-person MID for the FP was identified as 0.59 [standard deviation (SD) 0.31] (anchor-based) and 0.59 (distribution-based), whereas for the FI, MID was 0.11 (SD 0.05) (anchor-based) and 0.07 (distribution-based). Conclusions frailty is significantly associated with lower preference-based health state utility. Frailty MID can be used to inform design of clinical trials and economic evaluations, as well as providing useful clinical information on frailty differences that patients consider important. [ABSTRACT FROM AUTHOR]

Aims: National 30‐day mortality and readmission rates after heart failure (HF) hospitalisations are a focus of US policy intervention and yet have rarely been assessed in other comparable countries. We examined the frequency, trends and institutional variation in 30‐day mortality and unplanned readmission rates after HF hospitalisations in Australia and New Zealand. Methods and results: We included patients >18 years hospitalised with HF at all public and most private hospitals from 2010–15. The primary outcomes were the frequencies of 30‐day mortality and unplanned readmissions, and the institutional risk‐standardised mortality rate (RSMR) and readmission rate (RSRR) evaluated using separate cohorts. The mortality cohort included 153 592 patients (mean age 78.9 ± 11.8 years, 51.5% male) with 16 442 (10.7%) deaths within 30 days. The readmission cohort included 148 704 patients (mean age 78.6 ± 11.9 years, 51.7% male) with 33 158 (22.3%) unplanned readmission within 30 days. In 392 hospitals with at least 25 HF hospitalisations, the median RSMR was 10.7% (range 6.1–17.3%) with 59 hospitals significantly different from the national average. Similarly, in 391 hospitals with at least 25 HF hospitalisations, the median RSRR was 22.3% (range 17.7–27.1%) with 24 hospitals significantly different from the average. From 2010–15, the adjusted 30‐day mortality [odds ratio (OR) 0.991/month, 95% confidence interval (CI) 0.990–0.992, P < 0.01] and unplanned readmission (OR 0.998/month, 95% CI 0.998–0.999, P < 0.01) rates declined. Conclusion: Within 30 days of a HF hospitalisation, one in 10 patients died and almost a quarter of those surviving experienced an unplanned readmission. The risk of these outcomes varied widely among hospitals suggesting disparities in HF care quality. Nevertheless, a substantial decline in 30‐day mortality and a modest decline in readmissions occurred over the study period. [ABSTRACT FROM AUTHOR]

Background: Effective prevention of type 2 diabetes (T2D) requires early identification of high-risk individuals who might benefit from intervention. We sought to determine whether low serum testosterone, a novel risk factor for T2D in men, adds clinically meaningful information beyond current T2D risk models. Methods: The Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) study population consists of 2563 community-dwelling men aged 35-80 years in Adelaide, Australia. Of the MAILES participants, 2038 (80.0 %) provided information at baseline (2002-2006) and follow-up (2007-2010). After excluding participants with diabetes (n = 317), underweight (n = 5), and unknown BMI status (n = 11) at baseline; and unknown diabetes status (n = 50) at follow-up; 1655 participants were followed for 5 years. T2D at baseline and follow-up was defined by self-reported diabetes, or fasting plasma glucose (FPG) ≥7.0 mmol/L (126.1 mg/dL), or glycated haemoglobin (HbA1c) ≥6.5 %, or diabetes medications. Risk models were tested using logistic regression models. Sensitivity, specificity, positive predictive values (PPV) were used to identify the optimal cut-off point for low serum testosterone for incident T2D and the area under the receiver operating characteristic (AROC) curve was used to summarise the predictive power of the model. 15.5 % of men had at least one missing predictor variable; addressed through multiple imputation. Results: The incidence rate of T2D was 8.9 % (147/1655) over a median follow-up of 4.95 years (interquartile range: 4.35-5.00). Serum testosterone level predicted incident T2D (relative risk 0.96 [95 % CI: 0.92,1.00], P = 0.032) independent of current risk models including the AUSDRISK, but did not improve corresponding AROC statistics. A cut-off point of <16 nmol/L for low serum testosterone, which classified about 43 % of men, returned equal sensitivity (61.3 % [95 % CI: 52.6,69.4]) and specificity (58.3 % [95 % CI: 55.6,60.9) for predicting T2D risk, with a PPV of 12.9 % (95 % CI: 10.4,15.8). Conclusions: Low serum testosterone predicts an increased risk of developing T2D in men over 5 years independent of current T2D risk models applicable for use in routine clinical practice. Screening for low serum testosterone in addition to risk factors from current T2D risk assessment models or tools, including the AUSDRISK, would identify a large subgroup of distinct men who might benefit from targeted preventive interventions. [ABSTRACT FROM AUTHOR]

Background: To determine the extent to which variations in monthly Mental Health Emergency Department (MHED) presentations in South Australian Public Hospitals are associated with the Australian Bureau of Statistics (ABS) monthly unemployment rates. Methods: Times series modelling of relationships between monthly MHED presentations to South Australian Public Hospitals derived from the Integrated South Australian Activity Collection (ISAAC) data base and the ABS monthly unemployment rates in South Australia between January 2004–June 2011. Results: Time series modelling using monthly unemployment rates from ABS as a predictor variable explains 69 % of the variation in monthly MHED presentations across public hospitals in South Australia. Thirty-two percent of the variation in current month’s male MHED presentations can be predicted by using the 2 months’ prior male unemployment rate. Over 63 % of the variation in monthly female MHED presentations can be predicted by either male or female prior monthly unemployment rates. Conclusions: The findings of this study highlight that even with the relatively favourable economic conditions, small shifts in monthly unemployment rates can predict variations in monthly MHED presentations, particularly for women. Monthly ABS unemployment rates may be a useful metric for predicting demand for emergency mental health services. [ABSTRACT FROM AUTHOR]

Background: Levels of vitamin D in the population have come under increasing scrutiny, however there are only a few studies in Australia which measure levels in the general population. The aim of this study was to measure the levels of vitamin D within a large population cohort and examine the association with seasons and selected demographic and health risk factors. Methods: A longitudinal cohort study of 2413 participants in the northwest suburbs of Adelaide, South Australia conducted between 2008 and 2010 was used to examine serum levels of 25-hydroxy vitamin D (25(OH)D) in relation to demographic characteristics (age, sex, income, education and country of birth), seasons, the use of vitamin D supplements and selected health risk factors (physical activity, body mass index and smoking). Both unadjusted and adjusted mean levels of serum 25(OH)D were examined, as were the factors associated with the unadjusted and adjusted prevalence of serum 25(OH)D levels below 50 and 75 nmol/L. Results: Overall, the mean level of serum 25(OH)D was 69.2 nmol/L with 22.7% of the population having a serum 25(OH)D level below 50 nmol/L, the level which is generally recognised as vitamin D deficiency. There were significantly higher levels of 25(OH)D among males compared to females (t = 4.65, p < 0.001). Higher levels of 25 (OH)D were also measured in summer and autumn compared with winter and spring. Generally, mean levels of 25 (OH)D were lower in those classified as obese. Smokers and those undertaking no or less than 150 minutes/week of physical activity also had lower levels of serum vitamin D. Obesity (as classified by body mass index), season and undertaking an insufficient level of physical activity to obtain a health benefit were significantly associated with the prevalence of vitamin D deficiency. Conclusions: Vitamin D deficiency is prevalent in South Australia, affecting almost one quarter of the population and levels are related to activity, obesity and season even when adjusted for confounding factors. Improved methods of addressing vitamin D levels in population are required. [ABSTRACT FROM AUTHOR]

Purpose: To compare the relationship of the eight SF-36 v1 subscale scores to the summary scores of the PCS and MCS derived from two different scoring algorithms: one based on the original scoring method (Ware, Kosinski and Keller, SF-36 physical and mental health summary scales: a users manual. The Health Institute, New England Medical Centre, Boston, MA, 1994); and the other based on scoring algorithms that use parameters derived from structural equation modelling. Further, to provide SF-12 scoring algorithms similarly based on structural equation modelling. Methods: The Australian Bureau of Statistics 1995 Australian National Health Survey dataset was used as the basis for the production of coefficients. There were 18,141 observations with no missing data for all eight SF-36 subscales following imputation of data items, and 17,479 observations with no missing data for the SF-12 data items. Data were analysed in LISREL V8.71. Structural equation models were fit to the data in confirmatory factor analyses producing weighted least squares estimates, which overcame anomalies found in the traditional orthogonal scoring methods. Results: Models with acceptable fits to the hypothesised factor structure were produced, generating factor score weighting coefficients for use with the SF-36 and SF-12 data items, to produce PCS and MCS summary scores consistent with their underlying subscale scores. Conclusions: The coefficients generated will score the SF-36 summary PCS and MCS in a manner consistent with their subscales. Previous Australian studies using version 1 of SF-36 or SF-12 can re-score their summary scores using these coefficients. [ABSTRACT FROM AUTHOR]

Background: Analysis was undertaken on data from randomly selected participants of a biomedical cohort study to assess representativeness. The research hypotheses was that there was no difference in participation and non-participations in terms of health-related indicators (smoking, alcohol use, body mass index, physical activity, blood pressure and cholesterol readings and overall health status) and selected socio-demographics (age, sex, area of residence, education level, marital status and work status). Methods: Randomly selected adults were recruited into a bio-medical representative cohort study based in the north western suburbs of the capital of South Australia -- Adelaide. Comparison data was obtained from cross-sectional surveys of randomly selected adults in the same age range and in the same region. The cohort participants were 4060 randomly selected adults (18+ years). Results: There were no major differences between study participants and the comparison population in terms of current smoking status, body mass index, physical activity, overall health status and proportions with current high blood pressure and cholesterol readings. Significantly more people who reported a medium to very high alcohol risk participated in the study. There were some demographic differences with study participants more likely to be in the middle level of household income and education level. Conclusion: People with risky behaviours participated in this health study in the same proportions as people without these risk factors. [ABSTRACT FROM AUTHOR]

Background and Objectives: Emerging evidence suggests potential effects of nutrients/foods on sleep parameters. However, no studies have addressed the complex interactions among nutrients/foods and relate them to sleep outcomes. To investigate the associations between dietary patterns and sleep parameters (polysomnography (PSG) measured and self-reported sleep symptoms) in a large sample of community dwelling men in South Australia.Methods and Study Design: Cross-sectional analysis was conducted of participants in the Men Androgen Inflammation Lifestyle Environment and Stress cohort enrolled in a sleep sub-study (n=784, age 35-80 years). Dietary intake was measured by a validated food frequency questionnaire. Dietary patterns were identified by factor analysis. Sleep was assessed by an overnight home PSG and self-reported questionnaires.Results: Two factors were obtained by factor analysis: Factor 1 was characterised by high intakes of vegetables, fruits, and legumes and factor 2 was characterised by processed meat, snacks, red meat and take-away foods. Three categories of the dietary patterns were defined (prudent, mixed and western) through classification of the sample according to the actual consumption higher or lower of each factor. The prudent (factor 1 dominant) and mixed dietary patterns were inversely associated with sleep onset, compared with the western dietary pattern (factor 2 dominant) (β=-6.34 (95% CI-1.11, -11.57), β=-4.34 (95% CI-8.34, -0.34) respectively)). The association was only significant with the prudent dietary pattern after multiple comparison adjustment. No associations were found with between dietary patterns and other sleep outcomes.Conclusions: The prudent dietary pattern was associated with a faster sleep onset, which may provide a solution for sleep management. [ABSTRACT FROM AUTHOR]

Background: Obstructive sleep apnoea (OSA) and insomnia are the two most common sleep disorders and are frequent reasons for presentation in Australian general practice., Objective: This article describes the development, content and suggested uses of the online sleep health primary care clinical resource, which provides general practitioners and other primary healthcare professionals with evidence-based information on the aetiology, assessment, management, referral and ongoing care for OSA and chronic insomnia., Discussion: The Royal Australian College of General Practitioners-accepted clinical resource for the management of OSA and chronic insomnia in primary care was developed by the Australian National Centre for Sleep Health Services Research. The resource is designed to be used during consultations (eg following the steps in assessment and management and the use of online questionnaires for the assessment of OSA [Epworth Sleepiness Scale/OSA50/STOP-Bang] and insomnia [Sleep Condition Indicator/and Insomnia Severity Index]) and as an education/training tool (eg evidence on the role of continuous positive airway pressure/mandibular advancement splints for management of OSA and brief behavioural therapy for insomnia/cognitive behavioural therapy for insomnia for the management of insomnia).

Background: Shift work is characterised by displaced sleep opportunities and associated sleep disturbance. Shift workers often report sleepiness and other wake time symptoms associated with poor sleep. However, clinical sleep disorders are also prevalent in shift workers. Although prevalence rates are similar or higher in shift workers compared with the general population, help seeking in shift workers with sleep disorders is low., Objective: This article aims to provide general practitioners with a contemporary overview of the prevalence rates for sleep disorders in shift workers, to clarify the existing evidence relating to mental and physical health consequences of sleep disorders in shift workers and to highlight the need to consider undiagnosed sleep disorders before attributing sleep-related symptoms solely to work schedules., Discussion: Symptoms of sleep loss associated with shift work overlap with symptoms experienced by individuals living with sleep disorders. Although >40% of middle-aged Australians live with a sleep disorder that requires investigation and management, symptoms in shift workers are often attributed to the work schedule and, as a result, might not be investigated for appropriate diagnosis and treatment. We argue that screening for sleep disorders in shift workers with sleep complaints should be a priority.

Background: Paramedics are routinely exposed to shift work. Existing research shows that shift work exposure is associated with adverse mental and physical health outcomes. However, the current understanding of the impact of commencing shift work in a paramedic role on health is limited. This can be addressed by recruiting new paramedics before they commence shift work, and conducting regular follow-ups of potential biological, psychological and social changes. The present study aimed to examine changes in biological, psychological and social factors relative to pre-shift work baseline in a cohort of paramedics commencing intern employment with an Australian ambulance service., Method and Analysis: This observational, mixed-methods, longitudinal study aims to recruit 40 interns from one Australian ambulance service. Data collection will occur at baseline (standard day schedule for initial training), and subsequently at three months, six months, nine months and twelve months, to measure biological, psychological and social changes relative to baseline measurements. Changes in cardiometabolic markers (cholesterol, triglycerides, fasting glucose), microbiome (self-collected stool samples), sleep and physical activity (actigraphy) will be measured. Interns will also complete a battery of self-report questionnaires, sleep diaries and qualitative interviews to explore various psychological and social variables over time. Statistical analyses will be conducted using mixed effects regression, specifying a random effect of subject on the intercept, allowing participants to vary according to individual baseline levels, as well as tracking progress over time, appropriately accounting for serial correlation. Qualitative study components will be analysed via coding and thematic analysis procedures., Discussion: The present study protocol is a comprehensive outline of the observational study planned. The study will allow for greater knowledge of any changes in biological, psychological and social factors during a 12-month transition to shift work. The findings from the proposed study will have implications for the development of strategies to support early-career shift workers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Crowther et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Aims: Contemporary long-term survival following a heart failure (HF) hospitalization is uncertain. We evaluated survival up to 10 years after a HF hospitalization using national data from Australia and New Zealand, identified predictors of survival, and estimated the attributable loss in life expectancy., Methods and Results: Patients hospitalized with a primary diagnosis of HF from 2008-2017 were identified and all-cause mortality assessed by linking with Death Registries. Flexible parametric survival models were used to estimate survival, predictors of survival and loss in life expectancy. A total of 283 048 patients with HF were included (mean age 78.2 ± 12.3 years, 50.8% male). Of these, 48.3% (48.1-48.5) were surviving by 3 years, 34.1% (33.9-34.3) by 5 years and 17.1% (16.8-17.4) by 10 years (median survival 2.8 years). Survival declined with age with 53.4% of patients aged 18-54 years and 6.2% aged ≥85 years alive by 10 years (adjusted hazard ratio [aHR] for mortality 4.84, 95% confidence interval [CI] 4.65-5.04 for ≥85 years vs. 18-54 years) and was worse in male patients (aHR 1.14, 95% CI 1.13-1.15). Prior HF (aHR 1.20, 95% CI 1.18-1.22), valvular and rheumatic heart disease (aHR 1.11, 95% CI 1.10-1.13) and vascular disease (aHR 1.07, 95% CI 1.04-1.09) were cardiovascular comorbidities most strongly associated with long-term death. Non-cardiovascular comorbidities and geriatric syndromes were common and associated with higher mortality. Compared with the general population, HF was associated with a loss of 7.3 years in life expectancy (or 56.6% of the expected life expectancy) and reached 20.5 years for those aged 18-54 years., Conclusion: Less than one in five patients hospitalized for HF were surviving by 10 years with patients experiencing almost 60% loss in life expectancy compared with the general population, highlighting the considerable persisting societal burden of HF. Concerted multidisciplinary efforts are needed to improve post-hospitalization outcomes of HF., (© 2022 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Study Objectives: In a population-based survey, we determined sex differences in health profiles and quality of life between individuals who have a confirmed diagnosis of obstructive sleep apnea (OSA) and those who are at high risk of OSA yet remain undiagnosed., Methods: An online survey of Australian adults ≥ 18 years (n = 3,818) identified participants with self-reported diagnosed OSA (n = 460) or high-risk, undiagnosed OSA (OSA50 score ≥ 5, n = 1,015). Ever-diagnosed comorbidities, sociodemographics, and quality of life (EQ-5D-5L, Functional Outcomes of Sleep Questionnaire-10) were assessed., Results: Women were more frequently represented in the high-OSA-risk group compared with those with diagnosed OSA (55.5%, n = 563, versus 43%, n = 198; P < .001). In sex-specific logistic regression analyses, diagnosed OSA was associated with increased likelihoods of ≥ 1 cardiovascular condition (odds ratio: 3.0; 95% confidence interval: 2.0-4.5), hypertension (1.9; 1.3-2.8), gout (1.8; 1.1-2.9), and chronic obstructive pulmonary disease (3.8; 2.1-6.9) in men. In women, an association with asthma (2.0; 1.3-3.0) was seen. Diabetes, arthritis, mental health conditions (ever-diagnosed), and all EQ-5D-5L dimensions were associated with an OSA diagnosis regardless of sex, except for EQ-5D-5L anxiety/depression, which was only associated with an OSA diagnosis in women. A diagnosis of OSA was associated with sleepiness-related impairment (lowest quartile of Functional Outcomes of Sleep Questionnaire-10) in men (1.6; 1.01-2.5) and women (2.2; 1.4-3.6)., Conclusions: Sex-specific health conditions may drive diagnosis of OSA; however, clinical suspicion of OSA needs to be increased in men and women. The impaired quality of life and persistent sleepiness in participants with diagnosed OSA observed at a population level requires greater clinical attention., Citation: Krishnan S, Chai-Coetzer CL, Grivell N, et al. Comorbidities and quality of life in Australian men and women with diagnosed and undiagnosed high-risk obstructive sleep apnea. J Clin Sleep Med . 2022;18(7):1757-1767., (© 2022 American Academy of Sleep Medicine.)

Background: Little is known about the utilisation and safety of catheter ablation of atrial fibrillation (AF) among public and private sector hospitals., Aims: To examine the uptake of AF ablations and compare procedural safety between the sectors., Method: Hospitalisation data from all public and private hospitals in four large Australian states (NSW, QLD, VIC and WA) were used to identify patients undergoing AF ablation from 2012 to 17. The primary endpoint was any procedure-related complications up to 30-days post-discharge. Logistic regression was used to evaluate the association between treatment at a public hospital and risk of complications adjusting for covariates., Results: Private hospitals performed most of the 21,654 AF ablations identified (n = 16,992, 78.5 %), on patients who were older (63.5 vs. 59.9y) but had lower rates of heart failure (7.9 % vs. 10.4 %), diabetes (10.2 % vs. 14.1 %), and chronic kidney diseases (2.4 % vs. 5.2 %) (all p < 0.001) than those treated in public hospitals. When compared with private hospitals, public hospitals had a higher crude rate of complications (7.25 % vs. 4.70 %, p < 0.001). This difference remained significant after adjustment (OR 1.74 [95 % CI 1.54-2.04]) and it occurred with both in-hospital (OR 1.83 [1.57-2.14]) and post-discharge (OR 1.39 [1.06-1.83]) complications, with certain complications including acute kidney injury (OR 5.31 [3.02-9.36]), cardiac surgery (OR 5.18 [2.19-12.27]), and pericardial effusion (OR 2.18 [1.50-3.16])., Conclusions: Private hospitals performed most of AF ablations in Australia with a lower rate of complications when compared with public hospitals. Further investigations are needed to identify the precise mechanisms of this observed difference., (© 2021. The Author(s).)

Objectives: To examine the relationship between depression burden, health service utilisation and depression diagnosis in community-based men., Design: Prospective cohort study., Setting: Community-based., Participants: Men aged 35-80 years at recruitment (2002-2005), randomly selected from the northern and western suburbs of Adelaide, Australia, without depression at baseline, who attended follow-up visits (2007-2010) (n=1464)., Primary and Secondary Outcome Measures: Depression symptoms were categorised into high burden (total score of ≥13 for the Beck Depression Inventory (BDI) or ≥10 for the Centre for Epidemiologic Studies Depression Scale (CES-D) or low burden (<13 for the BDI or <10 for the CES-D). Diagnosed depression was determined by patient-reported physician diagnosis. Frequent general practitioner (GP) visits were those occurring 5+ times over the preceding year. Use of national medical and prescription services (Medicare Benefit Schedule and Pharmaceutical Benefit Scheme; MBS and PBS) was assessed through data linkage., Results: Frequent attendance and depression diagnosis was more common in men with a high than low burden of depression symptoms (45.9% vs 29.3%-18.7% vs 1.9%, p<0.001). Depression diagnoses were also more common in frequent GP attenders compared with low-average attenders (5.1% vs 2.2%, p<0.001). Among men with high burden of symptoms, there was no age-adjusted or multi-adjusted difference for likelihood of depression diagnosis between non-regular and frequent GP attenders. Annualised MBS and PBS expenditure was highest for men with undiagnosed depression., Conclusions: Men with a high burden of depression symptoms have commensurate use of health services when compared with those with a low burden, but only half report a physician diagnosis of depression. Undiagnosed depression led to a higher usage of medical and prescription services., Competing Interests: Competing interests: SM has received research funding from the National Health and Medical Research Council of Australia. RJA reports grants from National Health & Medical Research Council (Project Grant no. 627227), grants from ResMed Foundation during the conduct of the study; non-financial support from Embla Systems, Colorado, outside the submitted work. GAW reports grants from National Health & Medical Research Council (Project Grant no. 627227), grants from ResMed Foundation during the conduct of the study; non-financial support from Embla Systems, Colorado, personal fees from Eli Lilly, Bayer Schering, Sanofi, Novo Nordisk, AstraZeneca, INova and Elsevier outside the submitted work. IZ, AV and SA have no competing interests to declare., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

This study sought to determine patterns of multimorbidity and quantify their impact on use of primary health services in the presence and absence of anxiety and depression among a cohort of urban community-dwelling men in Australia. The analytic sample consisted of men ( n = 2039; age 38-85) from the follow-up wave of a prospective cohort study of all participants of the Florey Adelaide Male Ageing Study (FAMAS; Stage 2 [2007-2010]) and age-matched men from the North-West Adelaide Health Study (NWAHS; Stage 3 [2008-2010]). Self-reported data and linkage with a national universal health coverage scheme (Medicare) provided information on the prevalence of eight chronic conditions and health service utilization information (including annual GP visits). Obesity and cardiovascular disease (CVD) were associated with the highest number of comorbid conditions. Two nonrandom multimorbidity "clusters" emerged: "CVD, Obesity, Diabetes" and "CVD, Obesity, Osteoarthritis." Participants with conditions comorbid with CVD were more likely to have 10 or more annual GP visits, compared to multimorbidity involving other conditions. In comparison to participants without CVD, the presence of CVD increased the chance of having 10 or more annual GP visits (adjusted risk ratio: 3.7; 95% CI [2.8, 4.8]). When CVD was comorbid with anxiety and depression, having 10 or more annual GP visits was more common (adjusted risk ratio: 1.8; 95% CI [1.2, 2.5]). Multimorbidity patterns involving CVD, especially for multimorbidity that includes CVD with comorbid anxiety and depression, should be considered in developing clinical trials to better inform medical decision-making and care for patients with CVD and comorbid conditions.

Introduction: Despite global concerns about the safety and quality of health care, population-wide studies of hospital outcomes are uncommon. The SAFety, Effectiveness of care and Resource use among Australian Hospitals (SAFER Hospitals) study seeks to estimate the incidence of serious adverse events, mortality, unplanned rehospitalisations and direct costs following hospital encounters using nationwide data, and to assess the variation and trends in these outcomes., Methods and Analysis: SAFER Hospitals is a cohort study with retrospective and prospective components. The retrospective component uses data from 2012 to 2018 on all hospitalised patients age ≥18 years included in each State and Territories' Admitted Patient Collections. These routinely collected datasets record every hospital encounter from all public and most private hospitals using a standardised set of variables including patient demographics, primary and secondary diagnoses, procedures and patient status at discharge. The study outcomes are deaths, adverse events, readmissions and emergency care visits. Hospitalisation data will be linked to subsequent hospitalisations and each region's Emergency Department Data Collections and Death Registries to assess readmissions, emergency care encounters and deaths after discharge. Direct hospital costs associated with adverse outcomes will be estimated using data from the National Cost Data Collection. Variation in these outcomes among hospitals will be assessed adjusting for differences in hospitals' case-mix. The prospective component of the study will evaluate the temporal change in outcomes every 4 years from 2019 until 2030., Ethics and Dissemination: Human Research Ethics Committees of the respective Australian states and territories provided ethical approval to conduct this study. A waiver of informed consent was granted for the use of de-identified patient data. Study findings will be disseminated via presentations at conferences and publications in peer-reviewed journals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Non-standard working hours are associated with negative health outcomes. However, little is known about the early years of exposure to non-standard work hours, or whether workers new to these work schedules perceive their work as impacting their health. This limits our ability to develop meaningful intervention strategies for transitioning into non-standard work hour schedules. This exploratory study investigated whether recent Australian graduates in various non-standard workhour schedules perceive that their work schedule negatively impacts their health. The responses of 120 graduates within four years of completing their tertiary qualification collected from an online survey were analysed. Graduates were asked whether they perceived their work arrangements as impacting their health. Significantly more of those who were engaged in non-standard work schedules or worked beyond contracted hours perceived their working arrangements as having an impact on their health. This study highlights the importance of studying workers' perceptions of the impact of work hours on health, particularly when workers may be experiencing good global health but be at risk for negative health outcomes in future.

Context: Sex hormone-binding globulin (SHBG) levels are associated with cardiovascular disease (CVD) risk factors. However, prospective data on the association between SHBG levels and CVD events are sparse, with conflicting results., Objectives: To examine associations between serum SHBG, total testosterone (TT), and incident CVD and CVD-related mortality in middle-aged to elderly men., Design and Methods: Data on 2563 community-dwelling men (35 to 80 years) were obtained from participants in the Men Androgen Inflammation Lifestyle Environment and Stress cohort. The analytic sample included 1492 men without baseline (2002 to 2007) CVD and with fasted morning serum SHBG and TT available at both baseline and follow-up (2007 to 2010) and without medications affecting TT or SHBG. Associations of baseline SHBG and TT, with incident CVD and CVD mortality, were analyzed using logistic regression for incident CVD and Cox proportional hazard regression for CVD mortality, adjusting for established CVD risk factors., Results: In multivariable models, elevated baseline SHBG and lower baseline TT were independently associated with incident CVD (SHBG: OR, 1.54; 95% CI, 1.15 to 2.06 per SD increase in SHBG, P = 0.003; TT: OR, 0.71; 95% CI, 0.52 to 0.97 per SD decrease in TT; P = 0.03). A decrease in TT between time points was associated with incident CVD (OR, 0.72; 95% CI, 0.56 to 0.92; P = 0.01). Neither SHBG nor TT was significantly associated with all-age CVD mortality [hazard ratio (HR), 0.69; 95% CI, 0.29 to 1.63; P = 0.40; and HR, 0.60; 95% CI, 0.28 to 1.26; P = 0.18, respectively]., Conclusions: Among all men and men >65 years, elevated SHBG and lower TT were independently associated with both a greater risk of CVD and an increased CVD mortality risk., (Copyright © 2019 Endocrine Society.)

Background: Few studies have investigated the relationship between physical activity (PA) of low intensity and duration with quality of life (QoL) among individuals at risk or with cardiovascular disease (CVD)., Objectives: To investigate whether PA of different intensity and duration moderates the relationship between CVD and its risk factors (obesity, hypertension, diabetes, dyslipidaemia) and QoL in adults., Methods: Population-based cross-sectional studies using data from the EpiFloripa Cohort Study (Southern Brazil; n = 1,220, 38.8±12.0 years, 48.2% males) and the North West Adelaide Health Study (NWAHS, South Australia; n = 1,661, 43.7±11.1 years, 49.7% males). The physical and psychological domains of QoL were assessed using the WHOQOL-Bref (EpiFloripa) or the SF-36 (NWAHS) questionnaires. The diagnosis of CVD and its risk factors were self-reported. PA was self-reported and quantified by its intensity ["walking" or moderate/vigorous (MVPA)] and duration (none, 1-150, ≥150 min/week). Both studies were analysed separately, and results were adjusted for sociodemographic variables., Results: Participants at risk or with CVD from both studies showed a lower QoL than 'healthy' individuals with a stronger relationship for the physical domain. PA duration showed a direct-trend relationship with QoL, but the associations were stronger for MVPA in both studies. However, when stratified by health status, the magnitude of the association between "walking" duration and a higher physical QoL was greater among those at risk or with CVD compared to 'healthy' individuals. Conversely, among Australians with CVD, MVPA was associated with a better physical QoL only when its duration was ≥150 min/week. All associations were stronger in the NWAHS than in the Brazilian study., Conclusions: "Walking" was more prevalent than MVPA and was consistently associated with a better physical QoL among those at risk or with CVD. These findings should be considered in the design of public health interventions designed to increase PA and improve QoL., Competing Interests: The authors have declared that no competing interests exist.

Background and Objectives: Emerging evidence suggests potential effects of nutrients/foods on sleep parameters. However, no studies have addressed the complex interactions among nutrients/foods and relate them to sleep outcomes. To investigate the associations between dietary patterns and sleep parameters (polysomnography (PSG) measured and self-reported sleep symptoms) in a large sample of community dwelling men in South Australia., Methods and Study Design: Cross-sectional analysis was conducted of participants in the Men Androgen Inflammation Lifestyle Environment and Stress cohort enrolled in a sleep sub-study (n=784, age 35-80 years). Dietary intake was measured by a validated food frequency questionnaire. Dietary patterns were identified by factor analysis. Sleep was assessed by an overnight home PSG and self-reported questionnaires., Results: Two factors were obtained by factor analysis: Factor 1 was characterised by high intakes of vegetables, fruits, and legumes and factor 2 was characterised by processed meat, snacks, red meat and take-away foods. Three categories of the dietary patterns were defined (prudent, mixed and western) through classification of the sample according to the actual consumption higher or lower of each factor. The prudent (factor 1 dominant) and mixed dietary patterns were inversely associated with sleep onset, compared with the western dietary pattern (factor 2 dominant) (β=-6.34 (95% CI-1.11, -11.57), β=-4.34 (95% CI-8.34, -0.34) respectively)). The association was only significant with the prudent dietary pattern after multiple comparison adjustment. No associations were found with between dietary patterns and other sleep outcomes., Conclusions: The prudent dietary pattern was associated with a faster sleep onset, which may provide a solution for sleep management.

The Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) Study was established in 2009 to investigate the associations of sex steroids, inflammation, environmental and psychosocial factors with cardio-metabolic disease risk in men. The study population consists of 2569 men from the harmonisation of two studies: all participants of the Florey Adelaide Male Ageing Study (FAMAS) and eligible male participants of the North West Adelaide Health Study (NWAHS). The cohort has so far participated in three stages of the MAILES Study: MAILES1 (FAMAS Wave 1, from 2002-2005, and NWAHS Wave 2, from 2004-2006); MAILES2 (FAMAS Wave 2, from 2007-2010, and NWAHS Wave 3, from 2008-2010); and MAILES3 (a computer-assisted telephone interview (CATI) survey of all participants in the study, conducted in 2010). Data have been collected on a comprehensive range of physical, psychosocial and demographic issues relating to a number of chronic conditions (including cardiovascular disease, diabetes, arthritis and mental health) and health-related risk factors (including obesity, blood pressure, smoking, diet, alcohol intake and inflammatory markers), as well as on current and past health status and medication., (Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2013; all rights reserved.)

Objectives: To estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes., Design: Data from the North-West Adelaide Health Survey (NWAHS) were used to develop a model which predicts total diabetes at a small area. This model was then applied to cross-sectional data from general practices to predict the total level of expected diabetes. The difference between total expected and already diagnosed diabetes was defined as undiagnosed diabetes prevalence and was estimated for each small area. The patterns of diagnosed and undiagnosed diabetes were mapped to highlight the areas of high prevalence., Setting: North-West Adelaide, Australia., Participants: This study used two population samples-one from the de-identified GP practice data (n=9327 active patients, aged 18 years and over) and another from NWAHS (n=4056, aged 18 years and over)., Main Outcome Measures: Total diabetes prevalence, diagnosed and undiagnosed diabetes prevalence at GP practice and Statistical Area Level 1., Results: Overall, it was estimated that there was one case of undiagnosed diabetes for every 3-4 diagnosed cases among the 9327 active patients analysed. The highest prevalence of diagnosed diabetes was seen in areas of lower socioeconomic status. However, the prevalence of undiagnosed diabetes was substantially higher in the least disadvantaged areas., Conclusions: The method can be used to estimate population prevalence of diabetes from general practices wherever these data are available. This approach both flags the possibility that undiagnosed diabetes may be a problem of less disadvantaged social groups, and provides a tool to identify areas with high levels of unmet need for diabetes care which would enable policy makers to apply geographic targeting of effective interventions., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Background: Sarcopenia is the presence of low muscle mass and low muscle function. The aim of this study was to establish cutoffs for low muscle mass using three published methods and to compare the prevalence of sarcopenia in older Australians., Methods: Gender specific cutoffs levels were identified for low muscle mass using three different methods. Low grip strength was determined using established cutoffs of <30 kg for men and <20 kg for women to estimate the prevalence of sarcopenia., Results: Gender specific cutoffs levels for low muscle mass identified were (a) <6.89 kg/m(2) for men and <4.32 kg/m(2) for women, <2 standard deviation (SD) of a young reference population; (b) <7.36 kg/m(2) for men and <5.81 kg/m(2) for women from the lowest 20% percentile of the older group; and (c) <-2.15 for men and <-1.42 for women from the lowest 20% of the residuals of linear regressions of appendicular skeletal mass, adjusted for fat mass and height. Prevalence of sarcopenia in older (65 years and older) people by these three methods for men was 2.5%, 6.2%, and 6.4% and for women 0.3%, 9.3%, and 8.5%, respectively., Conclusions: Sarcopenia is common but consensus on the best method to confirm low muscle mass is required.

Purpose: A number of previous studies have shown inconsistencies between sub-scale scores and component summary scores using traditional scoring methods of the SF-36 version 1. This study addresses the issue in Version 2 and asks if the previous problems of disagreement between the eight SF-36 Version 1 sub-scale scores and the Physical and Mental Component Summary persist in version 2. A second study objective is to review the recommended scoring methods for the creation of factor scoring weights and the effect on producing summary scale scores., Methods: The 2004 South Australian Health Omnibus Survey dataset was used for the production of coefficients. There were 3,014 observations with full data for the SF-36. Data were analysed in LISREL V8.71. Confirmatory factor analysis models were fit to the data producing diagonally weighted least squares estimates. Scoring coefficients were validated on an independent dataset, the 2008 South Australian Health Omnibus Survey., Results: Problems of agreement were observed with the recommended orthogonal scoring methods which were corrected using confirmatory factor analysis., Conclusions: Confirmatory factor analysis is the preferred method to analyse SF-36 data, allowing for the correlation between physical and mental health.

Background: There is limited information on sleep duration and obesity among Australian children. The objective of the study is to cross-sectionally examine the relationship between sleep duration and obesity in Australian children aged 5 to 15 years., Methods: Data were collected using the South Australian Monitoring and Surveillance System between January 2004 and December 2008. Each month a representative random sample of South Australians are selected from the Electronic White Pages with interviews conducted using Computer Assisted Telephone Interviewing (CATI). Within each household, the person who was last to have a birthday was selected for interview. Parents reported the number of hours their children slept each day. Obesity was defined according to the International Obesity Task Force (IOTF) definition based on BMI calculated from reported body weight and height., Results: Overall, parents of 3495 children aged 5-15 years (mean 10.7 years, 50.3% boys) were interviewed. The prevalence of obesity was 7.7% (8.9% in boys, 6.6% in girls). In multivariate analysis after adjusting for sociodemographic variables, intake of fruit and vegetables, physical activity and inactivity, the odds ratio (OR) for obesity comparing sleeping <9 hours with ≥10 hours was 2.23 (95% CI 1.04-4.76) among boys, 1.70(0.78-3.73) among girls, and 1.97(1.15-3.38) in both genders. The association between short sleep (<9 hours) and obesity was stronger in the younger age group. No significant association between short sleep and obesity was found among children aged 13-15. There was also an additive interaction between short sleep and low level of physical activity., Conclusion: Short sleep duration is associated with increased obesity in children especially among younger age groups and boys.

Background: "Arthritis" is a common musculoskeletal condition but the knowledge of what type of arthritis people have, may be limited but may have changed over time in response to campaigns, increased awareness and improved health literacy. This paper describes people who did not know what type of arthritis they had, by a range of relevant demographic and socioeconomic variables, and assesses changes over time in the proportion of people who report having arthritis but do not know what type, using representative population surveillance data., Methods: Data were collected using the South Australian Monitoring and Surveillance System (SAMSS), a risk factor surveillance system where each month, a representative random sample of South Australians is selected from the Electronic White Pages, with interviews conducted using computer assisted telephone interviewing (CATI). Data were used for the period January 2006 to December 2008 (n = 16465) for respondents aged 18 years and over., Results: Overall, the proportion of respondents who did not know what type of arthritis they had, among people aged 18 years and over, for 2006 to 2008 was 6.5% (95% CI 6.1-6.9). When considering only those respondents reporting that they had been told by a doctor that they had arthritis, 30.1% did not know what type of arthritis they had. Multivariate analysis indicated that males, those with have a trade, certificate or diploma or secondary level of education, who spoke a language other than English at home, were widowed and earned $20,001 to $60,000, more than $80,000 or did not state their income were more likely to maintain that they did not know what type of arthritis they had., Conclusions: Population ageing and an increase in arthritis prevalence in the future will further increase the burden of arthritis. These increases in prevalence are not inevitable, especially if investments are made in public health prevention programs, particularly those addressing cultural and linguistic diversity and differences in socio-economic status and health literacy.

Objective: To examine the relationship between self-reported and clinical measurements for high blood pressure (HBP) and high cholesterol (HC) in a random population sample., Method: A representative population sample of adults aged 18 years and over living in the north-west region of Adelaide (n=1537) were recruited to the biomedical cohort study in 2002/03. In the initial cross-sectional component of the study, self-reported HBP status and HC status were collected over the telephone. Clinical measures of blood pressure were obtained and fasting blood taken to determine cholesterol levels. In addition, data from a continuous chronic disease and risk factor surveillance system were used to assess the consistency of self-reported measures over time., Result: Self-report of current HBP and HC showed >98% specificity for both, but sensitivity was low for HC (27.8%) and moderate for HBP (49.0%). Agreement between current self-report and clinical measures was moderate (kappa 0.55) for HBP and low (kappa 0.30) for HC. Demographic differences were found with younger people more likely to have lower sensitivity rates. Self-reported estimates for the surveillance system had not varied significantly over time., Conclusion: Although self-reported measures are consistent over time there are major differences between the self-reported measures and the actual clinical measurements. Technical aspects associated with clinic measurements could explain some of the difference., Implications: Monitoring of these broad population measures requires knowledge of the differences and limitations in population settings.

Objective: Lack of dose adjustment for renally cleared drugs in the presence of poor renal function is a common problem in the hospital setting. The absence of a clinical decision support system (CDSS) from direct clinician workflows such as computerized provider order entry (CPOE) hinders the uptake of CDSS. This study implemented CDSS in an environment independent of CPOE, introduced to prescribers via academic detailing, to address the dosing of renally cleared drugs., Design: GFR+ was designed to automatically calculate and update renal function, doses of key drugs adjusted for renal function, and highlight clinically significant decreases in renal function. Prescribers were made aware of GFR+, its navigation, and surrounding clinical issues, using academic detailing., Measurement: The rate of dosing conformity and management for key renally cleared drugs in hospitalized patients, before and after GFR+ implementation., Results: Improvements were seen in dosing conformity for enoxaparin (from 68% to 86%, p=0.03), gentamicin (63-87%, p=0.01), and vancomycin (47-77%, p=0.07), as well as the appropriate use of gentamicin therapeutic drug monitoring (70-90%, p=0.02). During episodes of acute renal impairment, renally cleared drugs were held on 38% of instances in the pre-intervention period compared with 62% post-intervention (p=0.01)., Conclusion: Clinical decision support implemented with academic detailing improved dosing conformity and management of key renally cleared drugs in a hospitalized population. Academic detailing should be strongly considered to facilitate the introduction of CDSS systems that cannot be placed directly into the clinician workflow.

Background: Health literacy is the ability to understand and interpret the meaning of health information in written, spoken or digital form and how this motivates people to embrace or disregard actions relating to health., Objective: This article aims to describe the concept of health literacy, its importance and its applications in the general practice setting., Discussion: Australia trails behind other western countries in practical applications of health literacy. Health literacy underpins the efficiency of consultations, health promotion efforts, and self management programs. Recognition of the health literacy status of individuals allows use of appropriate communication tools. This can save time and effort and improve patient satisfaction and health outcomes.

Purpose: To review information about adverse drug events (ADEs) and medication errors in Australia., Data Sources: Systematic literature reviews and reports from data collections of the Australian Bureau of Statistics, Institute of Health and Welfare, Council for Health Care Standards and Patient Safety Foundation., Results: (medical record reviews): We have shown that 2-4% of all hospital admissions, and up to 30% for patients > 75 years of age, are medication-related; up to three-quarters are potentially preventable. RESULTS (routine data collections): Routine death certificate and hospital discharge data coded using the International Classification of Diseases capture less than half as many ADEs as medical record reviews. Of coded adverse events that contributed to death, 27% involved an ADE, as did 20% of adverse events identified at discharge and 43% at general practice encounters. There is a strong correlation between increases in medication use and rates of adverse drug reactions (ADRs) associated with hospitalization. RESULTS (drugs implicated): These were similar in all the above studies: anticoagulants, anti-inflammatory drugs, opioids, anti-neoplastics, antihypertensives, antibiotics, cardiac glycosides, diuretics, hypoglycaemic agents, steroids, hypnotics, anticonvulsants, and antipsychotics. RESULTS (clinical indicators): An ADE is reported in 1% of hospital admissions, while some hospitals do not report ADRs to the national collection. Only three-quarters of patients with acute myocardial infarction receive thrombolytics within 1 hour of presentation. Five per cent of patients on warfarin record an international normalized ratio > 5, and 1%, 0.05%, and 0.2% -suffer abnormal bleeding, cerebral haemorrhage, or death, respectively. RESULTS (the Australian Incident Monitoring System): Twenty-six per cent of 27 000 hospital-related incidents were medication-related, as were 36% of 2000 anaesthesia-related incidents, and 50% of 2500 general practice incidents. RESULTS (errors): Errors occur in 15-20% of drug administrations when ward stock systems are used and 5-8% when individual patient systems are used. Previous allergic reactions to drugs may not be recorded more than 75% of the time., Conclusion: ADEs are common in the Australian health system. Anticoagulant, anti-inflammatory, and cardiovascular drugs feature prominently as preventable, high impact problems, and collectively make up over one-half of all ADEs. Methods for monitoring and preventing ADEs should be progressively improved.