Medicine (RMH) - Research Publications
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ItemThe Cost-Effectiveness of Supplemental Carnosine in Type 2 Diabetes(MDPI, 2022-01)In this paper, we assess the cost-effectiveness of 1 g daily of carnosine (an over the counter supplement) in addition to standard care for the management of type 2 diabetes and compare it to standard care alone. Dynamic multistate life table models were constructed in order to estimate both clinical outcomes and costs of Australians aged 18 years and above with and without type 2 diabetes over a ten-year period, 2020 to 2029. The dynamic nature of the model allowed for population change over time (migration and deaths) and accounted for the development of new cases of diabetes. The three health states were 'Alive without type 2 diabetes', 'Alive with type 2 diabetes' and 'Dead'. Transition probabilities, costs, and utilities were obtained from published sources. The main outcome of interest was the incremental cost-effectiveness ratio (ICER) in terms of cost per year of life saved (YoLS) and cost per quality-adjusted life year (QALY) gained. Over the ten-year period, the addition of carnosine to standard care treatment resulted in ICERs (discounted) of AUD 34,836 per YoLS and AUD 43,270 per QALY gained. Assuming the commonly accepted willingness to pay threshold of AUD 50,000 per QALY gained, supplemental dietary carnosine may be a cost-effective treatment option for people with type 2 diabetes in Australia.
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ItemEducating junior doctors and pharmacists to reduce discharge prescribing of opioids for surgical patients: a cluster randomised controlled trial(WILEY, 2020-11)OBJECTIVES: To evaluate whether educating junior doctors and hospital pharmacists about analgesic prescribing improved discharge prescribing of opioids for opioid-naïve patients after surgical admissions. DESIGN: Cluster randomised controlled trial, undertaken during the first half of 2019. SETTING: The Alfred Hospital, a major Melbourne teaching hospital with 13 surgical units. PARTICIPANTS: Opioid-naïve patients discharged from surgical units after a stay of at least 24 hours. INTERVENTION: Surgical units were randomised to the intervention or control arms. Interns, residents, and clinical pharmacists assigned to intervention arm units attended education sessions, presented by the hospital analgesic stewardship pharmacist, about appropriate analgesic prescribing for patients in hospital surgical units. MAIN OUTCOME MEASURES: The patients prescribed slow release opioids on discharge from hospital during the baseline (1 February - 30 April 2018) and post-intervention periods (17 February - 30 April 2019). RESULTS: During the baseline period, 1369 intervention unit and 1014 control unit admissions were included in our analysis; during the evaluation period, 973 intervention unit and 706 control unit episodes were included. After adjusting for age, length of stay, pain score, acute pain service involvement, and use of immediate release opioids prior to admission, patients in the intervention group were prescribed slow release opioids at discharge less frequently than patients in the control group (adjusted odds ratio [aOR], 0.52; 95% CI, 0.35-0.77) and were more frequently discharged without any prescribed opioids following the intervention (aOR, 1.69; 95% CI, 1.24-2.30). Providing de-escalation plans was more frequent for intervention than control group patients prescribed slow release opioids on discharge post-intervention (OR, 2.36; 95% CI, 1.25-4.45). CONCLUSIONS: Specific education for clinicians and pharmacists about appropriate analgesic prescribing for surgical patients is effective in reducing prescribing of opioids at discharge. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12618000876291 (prospective).
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ItemAssessing the impact of smoking on the health and productivity of the working-age Indonesian population using modelling(BMJ PUBLISHING GROUP, 2020)OBJECTIVES: To estimate the impact of smoking in the working-age Indonesian population in terms of costs, years of life, quality-adjusted life years (QALYs) and productivity-adjusted life years (PALYs) lost. METHODS: Life table modelling of Indonesian smokers aged 15-54 years, followed up until 55 years (retirement age). Contemporary data on demographics, all-cause mortality, population attributable fractions and prevalence of smoking were derived from the Institute for Health Metrics and Evaluation. The quality of life and reduction in productivity due to smoking were derived from published sources. The analysis was repeated but with the assumption that the cohorts were non-smokers. The differences in results represented the losses incurred due to smoking. Gross domestic product (GDP) per equivalent full-time worker (US$11 765) was used for estimation of the cost of each PALY, and an annual discount rate of 3.0% was applied to all costs and outcomes. RESULTS: The prevalences of smoking among Indonesian working-age men and women were 67.2% and 2.16%, respectively. This study estimated that smoking caused 846 123 excess deaths, 2.9 million years of life lost (0.40%), 41.6 million QALYs lost (5.9%) and 15.6 million PALYs lost (2.3%). The total cost of productivity loss due to smoking amounted to US$183.7 billion among the working-age population followed up until retirement. Healthcare cost was predicted to be US$1.8 trillion. Over a 1-year time horizon, US$10.2 billion was lost in GDP and 117 billion was lost in healthcare costs. CONCLUSION: Smoking imposes significant health and economic burden in Indonesia. The findings stress the importance of developing effective tobacco control strategies at the macro and micro levels, which would benefit the country both in terms of health and wealth.
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ItemHealth and productivity burden of coronary heart disease in the working Indonesian population using life-table modelling(BMJ PUBLISHING GROUP, 2020)OBJECTIVES: The impact of coronary heart disease (CHD) and its effect on work productivity at a population level remains unknown in Indonesia. This study estimates the health and productivity lost to CHD in terms of years of life, quality-adjusted life years (QALYs) and productivity-adjusted life years (PALYs). SETTING AND PARTICIPANTS: A life-table model was constructed to simulate the experiences of Indonesians currently aged 15-54 years (working age) with CHD, followed-up to 55 years (retirement age). The life-table analysis was then repeated assuming that the cohort did not have CHD. Differences in the results reflected the impact of CHD. Demographical, prevalence and mortality data were based on the 2017 Global Burden of Disease study and 2018 Indonesian National Health Survey. Costs, productivity indices and utilities were derived from published sources. The cost of each PALY was assumed to be equivalent to gross domestic product per equivalent full-time worker (US$11 765). Future costs and outcomes were discounted by 3% annually. PRIMARY AND SECONDARY OUTCOME MEASURES: Differences in total deaths, years of life and PALYs represented the impact of CHD. RESULTS: At present, 1 954 543 (1.45%) Indonesians of working-age have CHD. By retirement age, it was estimated that CHD resulted in 32 492 (36.6%) excess deaths, 128 132 (0.5%) years of life lost, 2 331 495 (10.5%) QALYs lost and 1 589 490 (6.9%) PALYs lost. The economic impact of lost productivity amounted to US$33.3 billion, and healthcare costs to US$139 billion. CONCLUSION: The health and economic burden of CHD in Indonesia looms large. This highlights the importance of its prevention and control, strategies for which, if effective, will deliver financial return.
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ItemThe impact of diabetes on the productivity and economy of Bangladesh(BMJ PUBLISHING GROUP, 2020-06)AIMS: To estimate the impact of type 2 diabetes in terms of mortality, years of life lost (YLL) and productivity-adjusted life years (PALY) lost in Bangladesh. METHODS: A life table model was constructed to estimate the productivity of the Bangladeshi population of current working age (20-59 years) with diabetes. Follow-up to 60 years (retirement age) was simulated. The life table analysis was then repeated assuming that the cohort did not have diabetes, with subsequent improvement in productivity. Differences in the results of the two analyses reflected the impact of diabetes on health and productivity. Demographic and the prevalence of diabetes data were sourced from the International Diabetes Foundation estimates for 2017 and mortality data were based on the 2017 Global Burden of Disease study. Relative risk and productivity indices were based on an Indian and Bangladeshi study, respectively. The cost of each PALY was assumed to be equivalent to gross domestic product (GDP) per equivalent full-time worker (US$8763). Future costs and years of life, and PALYs lived were discounted at an annual rate of 3%. RESULTS: Assuming a follow-up of this population (aged 20-59 years) until age 60 years or death, an estimated 813 807 excess deaths, loss of 4.0 million life years (5.5%) and 9.2 million PALYs (20.4%) were attributable to having diabetes. This was equivalent to 0.7 YLL, and 1.6 PALYs lost per person. The loss in PALYs equated to a total of US$97.4 billion lost (US$16 987 per person) in GDP. The results of the scenario analysis showed that the estimation was robust. CONCLUSION: In Bangladesh, the impact of diabetes on productivity loss and the broader economy looms large, and poses a substantial risk to the country's future prosperity. This highlights the critical importance of health strategies aimed at the control of diabetes.