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Objective. This study aimed to estimate costs of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) to patients, government and Australian society. Methods. Australian ME/ CFS patients and their carers were recruited using convenience sampling. Patients completed an online retrospective cost diary, providing ME/CFS-related direct medical, non-medical and indirect costs. Informal care costs were collected directly from carers. Data from the Pharmaceutical Benefits Scheme and Medicare Benefits Schedule were linked to participant survey data. Annual per patient and total societal costs were estimated, broken down by category and presented in 2021 AUD. Factors associated with higher costs were investigated using generalised linear models. Results. One hundred and seventy five patients (mean age 49 years s.d. 14, 79.4% female) completed the cost diary. Estimated total annual societal costs of ME/CFS in Australia ranged between $1.38 and $10.09 billion, with average annual total costs of $63 400/patient. Three-quarters of these costs were due to indirect costs ($46 731). Disability severity was the key factor associated with higher costs, particularly for indirect costs (being 2.27-fold higher for severe disability than no/mild disability). Conclusions. ME/CFS poses a significant economic burden in Australia, owing mainly to high indirect and informal care costs. [ABSTRACT FROM AUTHOR]

Background and Objective: Little is known about the association between ambient air pollution and idiopathic pulmonary fibrosis (IPF) in areas with lower levels of exposure. We aimed to investigate the impact of air pollution on lung function and rapid progression of IPF in Australia. Methods: Participants were recruited from the Australian IPF Registry (n = 570). The impact of air pollution on changes in lung function was assessed using linear mixed models and Cox regression was used to investigate the association with rapid progression. Results: Median (25th–75th percentiles) annual fine particulate matter (<2.5 μm, PM2.5) and nitrogen dioxide (NO2) were 6.8 (5.7, 7.9) μg/m3 and 6.7 (4.9, 8.2) ppb, respectively. Compared to living more than 100 m from a major road, living within 100 m was associated with a 1.3% predicted/year (95% confidence interval [CI] −2.4 to −0.3) faster annual decline in diffusing capacity of the lungs for carbon monoxide (DLco). Each interquartile range (IQR) of 2.2 μg/m3 increase in PM2.5 was associated with a 0.9% predicted/year (95% CI −1.6 to −0.3) faster annual decline in DLco, while there was no association observed with NO2. There was also no association between air pollution and rapid progression of IPF. Conclusion: Living near a major road and increased PM2.5 were both associated with an increased rate of annual decline in DLco. This study adds to the evidence supporting the negative effects of air pollution on lung function decline in people with IPF living at low‐level concentrations of exposure. [ABSTRACT FROM AUTHOR]

Objective To investigate the impact of total number and patterns of comorbidities on health-related quality of life (HRQoL) and identify the most prevalent and influential comorbidity patterns in people with OA over 10 years. Methods Participants from the Tasmanian Older Adult Cohort aged 50–80 years, with self-reported OA and data on comorbidities and HRQoL were included. Participants were interviewed at baseline (n  = 398), 2.5 (n  = 304), 5 (n  = 269) and 10 years (n  = 191). Data on the self-reported presence of 10 chronic comorbidities were collected at baseline. HRQoL was assessed using the Assessment of Quality of Life-4-Dimensions. The long-term impacts of the number and of the nine most prevalent combinations of cardiovascular (CVD), non-OA musculoskeletal (Ms), metabolic and respiratory comorbidities on HRQoL over 10 years were analysed using linear mixed regressions. Results Compared with comorbidity-free OA participants, the health state utility (HSU) of those with 2 or ≥3 comorbidities was respectively −0.07 and −0.13 units lower over 10 years, largely driven by reduced scores for independent living, social relationships and psychological wellness. Comorbidity patterns including 'CVD+Ms' were most influential, and associated with up to 0.13 units lower HSU, mostly through negative impacts on independent living (up to −0.12), psychological wellness (up to −0.08) and social relationship (up to −0.06). Conclusion Having more comorbidities negatively impacted OA patients' long-term HRQoL. OA patients with CVD and non-OA musculoskeletal conditions had the largest HSU impairment, and therefore optimal management and prevention of these conditions may yield improvements in OA patients' HRQoL. [ABSTRACT FROM AUTHOR]

Objectives. The aim of this exploratory study was to investigate resource use and predictors associated with critical care unit (CCU) admission after primary bariatric surgery within the Tasmanian public healthcare system. Methods. Patients undergoing primary bariatric surgery in the Tasmanian Health Service (THS) public hospital system between 7 July 2013 and 30 June 2019 were eligible for inclusion in this study. The THS provides two levels of CCU support, an intensive care unit (ICU) and a high dependency unit (HDU). A mixed-methods approach was performed to examine the resource use and predictors associated with overall CCU admission, as well as levels of HDU and ICU admission. Results. There were 254 patients in the study. Of these, 44 (17.3%) required 54 postoperative CCU admissions, with 43% requiring HDU support and 57% requiring more resource-demanding ICU support. Overall, CCU patients were more likely to have higher preoperative body mass index and multimorbidity and to undergo sleeve gastrectomy or gastric bypass. Patients undergoing gastric banding were more likely to requireHDUrather than ICU support. Total hospital stays and median healthcare costs were higher for CCU (particularly ICU) patients than non-CCU patients. Conclusions. Bariatric surgery patients often have significant comorbidities. This study demonstrates that patients with higher levels of morbidity are more likely to require critical care postoperatively. Because this is elective surgery, being able to identify patients who are at increased risk is important to plan either the availability of critical care or even interventions to improve patients' preoperative risk. Further work is required to refine the pre-existing conditions that contribute most to the requirement for critical care management (particularly in the ICU setting) in the perioperative period. [ABSTRACT FROM AUTHOR]

Objective: To comprehensively synthesize the evolution of health‐economic evaluation models (HEEMs) of all osteoarthritis (OA) interventions, including preventions, core treatments, adjunct nonpharmacologic interventions, pharmacologic interventions, and surgical treatments. Methods: The literature was searched within health‐economic/biomedical databases. Data extracted included OA type, population characteristics, model setting/type/events, study perspective, and comparators; the reporting quality of the studies was also assessed. The review protocol was registered at the International Prospective Register of Systematic Reviews (CRD42018092937). Results: Eighty‐eight studies were included. Pharmacologic and surgical interventions were the focus in 51% and 44% of studies, respectively. Twenty‐four studies adopted a societal perspective (with increasing popularity after 2013), but most (63%) did not include indirect costs. Quality‐adjusted life years was the most popular outcome measure since 2008. Markov models were used by 62% of studies, with increasing popularity since 2008. Until 2010, most studies used short‐to‐medium time horizons; subsequently, a lifetime horizon became popular. A total of 86% of studies reported discount rates (predominantly between 3% and 5%). Studies published after 2002 had a better coverage of OA‐related adverse events (AEs). Reporting quality significantly improved after 2001. Conclusion: OA HEEMs have evolved and improved substantially over time, with the focus shifting from short‐to‐medium‐term pharmacologic decision‐tree models to surgical‐focused lifetime Markov models. Indirect costs of OA are frequently not considered, despite using a societal perspective. There was a lack of reporting sensitivity of model outcome to input parameters, including discount rate, OA definition, and population parameters. While the coverage of OA‐related AEs has improved over time, it is still not comprehensive. [ABSTRACT FROM AUTHOR]

• PwMS perceived/experienced job loss due to workplace contextual factors. • The commonest factor for perceived job loss was transportation difficulties. • The commonest factor for experienced job loss was prolonged standing with equipment. • Professionals and blue-collar workers had higher number of workplace risk factors. • Those with moderate/severe disability had higher number of workplace risk factors. High unemployment rate of people with multiple sclerosis (PwMS) is associated with substantial economic costs. Whilst the impact of MS symptoms and other disease-related factors on employment outcomes of PwMS has been assessed, limited evidence exists on the impacts of workplace factors. To investigate the most common individual and group workplace factors associated with unemployment or a perceived risk of unemployment in PwMS, and to identify patient subgroups that are more susceptible to changes in employment status due to such factors. Data from the Australian MS Longitudinal Study (AMSLS) on employment status and workplace factors were used. Fifteen workplace factors were classified under four groups: organisational, commuting, moving around at work, and equipment usage factors. Participants answered 'Yes' to each factor if it related to their unemployment and/or perceived risk of becoming unemployed and a group factor was considered "Yes" if at least one individual factor within it was answered as "Yes". The proportions of "Yes" responses were calculated for both individual and group factors. Total number of individual factors was calculated and descriptive analyses and ordered logistic regression were used to summarize the total number of factors affecting each participant, and their association with participants' occupations, sex, disability severity and disease duration. Common workplace factors influencing employment were organisational (39.8 % perceived risk, 44.0 % lost employment), commuting (28.9 % perceived risk) and equipment usage difficulty (30.9 % lost employment). Common individual factors included inflexible working conditions, lack of suitable work, commuting difficulties, architectural barriers, and requirement to stand for long periods to use equipment. Professionals, blue-collar workers, and those with moderate/severe disability were more likely to report a higher number of workplace factors risking their employment. Workplace factors undermine PwMS employment, with variations among subgroups based on occupation and disability severity. Understanding these barriers is crucial for supporting PwMS in the workforce. [ABSTRACT FROM AUTHOR]

Objective: Determine the prevalence of multiple sclerosis (MS) in Australia in 2017 using MS-specific disease-modifying therapy (DMT) prescription data and estimate the change in prevalence from 2010. Methods: DMT prescriptions were extracted from Australia's Pharmaceutical Benefits Scheme (PBS) data for January–December 2017. Percentages of people with MS using DMTs (DMT penetrance) were calculated using data from the Australian MS Longitudinal Study. Prevalence was estimated by dividing the total number of monthly prescriptions by 12 (except alemtuzumab), adjusted for DMT penetrance and Australian population estimates. Prevalences in Australian states/territories were age-standardised to the Australian population. Comparisons with 2010 prevalence data were performed using Poisson regression. Results: Overall DMT penetrance was 64%, and the number of people with MS in Australia in 2017 was 25,607 (95% confidence interval (CI): 24,874–26,478), a significant increase of 4324 people since 2010 (p < 0.001). The prevalence increased significantly from 95.6/100,000 (2010) to 103.7/100,000 (2017), with estimates highest in Tasmania in 2017 (138.7/100,000; 95% CI: 137.2–140.1) and lowest in Queensland (74.6/100,000; 95% CI: 73.5–75.6). From 2010 to 2017 using the median latitudes for each state/territory, the overall latitudinal variation in MS prevalence was an increase of 3.0% per degree-latitude. Conclusion: Consistent with global trends, Australia's MS prevalence has increased; this probably reflecting decreased mortality, increased longevity and increased incidence. [ABSTRACT FROM AUTHOR]

Objectives: To quantify life expectancy (LE), quality-adjusted life years (QALYs) and total lifetime societal costs for a hypothetical cohort of Australians with multiple sclerosis (MS). Methods: A 4-state Markov model simulated progression from no/mild to moderate and severe disability and death for a cohort of 35-year-old women over a lifetime horizon. Death risks were calculated from Australian life tables, adjusted by disability severity. State-dependent relapse probabilities and associated disutilities were considered. Probabilities of MS progression and relapse were estimated from AusLong and TasMSL MS epidemiological databases. Annual societal (direct and indirect) costs (2017 Australian dollars) and health-state utilities for each state were derived from the Australian MS Longitudinal Study. Costs were discounted at 5% annually. Results: Mean (95% confidence interval (CI)) LE from age 35 years was 42.7 (41.6–43.8) years. This was 7.5 years less than the general Australian population. Undiscounted QALYs were 28.2 (26.3–30.0), a loss of 13.1 QALYs versus the Australian population. Discounted lifetime costs were $942,754 ($347,856–$2,820,219). Conclusion: We have developed a health economics model of the progression of MS, calculating the impact of MS on LE, QALYs and lifetime costs in Australia. It will form the basis for future cost-effectiveness analyses of interventions for MS. [ABSTRACT FROM AUTHOR]