The economic impact of diabetes through lost labour force participation on individuals and government: evidence from a microsimulation model.

BACKGROUND: Diabetes is a costly and debilitating disease. The aim of the study is to quantify the individual and national costs of diabetes resulting from people retiring early because of this disease, including lost income; lost income taxation, increased government welfare payments; and reductions in GDP. METHODS: A purpose-built microsimulation model, Health&WealthMOD2030, was used to estimate the economic costs of early retirement due to diabetes. The study included all Australians aged 45-64 years in 2010 based on Australian Bureau of Statistics' Surveys of Disability, Ageing and Carers. A multiple regression model was used to identify significant differences in income, government welfare payments and taxation liabilities between people out of the labour force because of their diabetes and those employed full time with no chronic health condition. RESULTS: The median annual income of people who retired early because of their diabetes was significantly lower (AU$11,784) compared to those employed full time without a chronic health condition who received almost five times more income. At the national level, there was a loss of AU$384 million in individual earnings by those with diabetes, an extra AU$4 million spent in government welfare payments, a loss of AU$56 million in taxation revenue, and a loss of AU$1,324 million in GDP in 2010: all attributable to diabetes through its impact on labour force participation. Sensitivity analysis was used to assess the impact of different diabetes prevalence rates on estimates of lost income, lost income taxation, increased government welfare payments, and reduced GDP. CONCLUSIONS: Individuals bear the cost of lost income in addition to the burden of the disease. The Government endures the impacts of lost productivity and income taxation revenue, as well as spending more in welfare payments. These national costs are in addition to the Government's direct healthcare costs.

An evaluation of the quality of evidence underpinning diabetes management models: a review of the literature.

OBJECTIVE: There is a paucity of research on the quality of evidence relating to primary care workforce models. Thus, the aim of the present study was to evaluate the quality of evidence on diabetes primary care workforce models in Australia. METHODS: The National Health and Medical Research Council of Australia's (National Health and Medical Reseach Council; 2000, 2001) frameworks for evaluating scientific evidence and economic evaluations were used to assess the quality of studies involving primary care workforce models for diabetes care involving Australian adults. A search of medical databases (MEDLINE, AMED, RURAL, Australian Indigenous HealthInfoNet and The Cochrane Institute), journals for diabetes care (Diabetes Research and Clinical Practice, Diabetes Care, Diabetic Medicine, Population Health Management, Rural and Remote Health, Australian Journal of Primary Health, PLoS Medicine, Medical Journal of Australia, BMC Health Services Research, BMC Public Health, BMC Family Practice) and Commonwealth and state government health websites was undertaken to acquire Australian studies of diabetes workforce models published 2005-13. Various diabetes workforce models were examined, including 'one-stop shops', pharmacy care, Aboriginal services and telephone-delivered interventions. The quality of evidence was evaluated against several criteria, including relevance and replication, strength of evidence, effect size, transferability and representativeness, and value for money. RESULTS: Of the 14 studies found, four were randomised controlled trials and one was a systematic review (i.e. Level II and I (best) evidence). Only three provided a replicable protocol or detailed intervention delivery. Eleven lacked a theoretical framework. Twelve reported significant improvements in clinical (patient) outcomes, commonly HbA1c, cholesterol and blood pressure; only four reported changes in short- and long-term outcomes (e.g. quality of life). Most studies used a small or targeted population. Only two studies assessed both benefits and costs of their intervention compared with usual care and cost effectiveness. CONCLUSIONS: More rigorous studies of diabetes workforce models are needed to determine whether these interventions improve patient outcomes and, if they do, represent value for money. WHAT IS KNOWN ABOUT THE TOPIC?: Although health systems with strong primary care orientations have been associated with enhanced access, equity and population health, the primary care workforce is facing several challenges. These include a mal-distribution of resources (supply side) and health outcomes (demand side), inconsistent support for teamwork care models, and a lack of enhanced clinical inter-professional education and/or training opportunities. These challenges are exacerbated by an ageing health workforce and general population, as well as a population that has increased prevalence of chronic conditions and multi-morbidity. Although several policy directions have been advocated to address these challenges, there is a lack of high-quality evidence about which primary care workforce models are best (and which models represent better value for money than current practice) and what the health effects are for patients. WHAT DOES THIS PAPER ADD?: This study demonstrated several strengths and weaknesses of Australian diabetes models of care studies. In particular, only five of the 14 studies assessed were designed in a way that enabled them to achieve a Level II or I rating (and hence the 'best' level of evidence), based on the NHMRC's (2000, 2001) frameworks for assessing scientific evidence. The majority of studies risked the introduction of bias and thus may have incorrect conclusions. Only a few studies described clearly what the intervention and the comparator were and thus could be easily replicated. Only two studies included cost-effectiveness studies of their interventions compared with usual care. WHAT ARE THE IMPLICATIONS FOR PRACTITIONERS?: Although there has been an increase in the number of primary care workforce models implemented in Australia, there is a need for more rigorous research to assess whether these interventions are effective in producing improved health outcomes and represent better value for money than current practice. Researchers and policymakers need to make decisions based on high-quality evidence; it is not obvious what effect the evidence is having on primary care workforce reform.

Economic costs of informal care for people with chronic diseases in the community: Lost income, extra welfare payments, and reduced taxes in Australia in 2015-2030.

We estimated the economic costs of informal care in the community from 2015 to 2030, using an Australian microsimulation model, Care&WorkMOD. The model was based on data from three Surveys of Disability, Ageing, and Carers (SDACs) for the Australian population aged 15-64 years old. Estimated national income lost was AU$3.58 billion in 2015, increasing to $5.33 billion in 2030 (49% increase). Lost tax payments were estimated at AU$0.99 billion in 2015, increasing to AU$1.44 billion in 2030 (45% increase), and additional welfare payments were expected to rise from $1.45 billion in 2015 to AU$1.94 in 2030 (34% increase). There are substantial economic costs both to informal carers and the government due to carers being out of the labour-force to provide informal care for people with chronic diseases. Health and social policies supporting carers to remain in the labour force may allow governments to make substantial savings, while improving the economic situation of carers.

The costs of diabetes among Australians aged 45-64†years from 2015 to 2030: projections of lost productive life years (PLYs), lost personal income, lost taxation revenue, extra welfare payments and lost gross domestic product from Health&WealthMOD2030.

OBJECTIVES: To project the number of people aged 45-64 years with lost productive life years (PLYs) due to diabetes and related costs (lost income, extra welfare payments, lost taxation revenue); and lost gross domestic product (GDP) attributable to diabetes in Australia from 2015 to 2030. DESIGN: A simulation study of how the number of people aged 45-64 years with diabetes increases over time (based on population growth and disease trend data) and the economic losses incurred by individuals and the government. Cross-sectional outputs of a microsimulation model (Health&WealthMOD2030) which used the Australian Bureau of Statistics' Survey of Disability, Ageing and Carers 2003 and 2009 as a base population and integrated outputs from two microsimulation models (Static Incomes Model and Australian Population and Policy Simulation Model), Treasury's population and labour force projections, and chronic disease trends data. SETTING: Australian population aged 45-64 years in 2015, 2020, 2025 and 2030. OUTCOME MEASURES: Lost PLYs, lost income, extra welfare payments, lost taxation revenue, lost GDP. RESULTS: 18 100 people are out of the labour force due to diabetes in 2015, increasing to 21 400 in 2030 (18% increase). National costs consisted of a loss of $A467 million in annual income in 2015, increasing to $A807 million in 2030 (73% increase). For the government, extra annual welfare payments increased from $A311 million in 2015 to $A350 million in 2030 (13% increase); and lost annual taxation revenue increased from $A102 million in 2015 to $A166 million in 2030 (63% increase). A loss of $A2.1 billion in GDP was projected for 2015, increasing to $A2.9 billion in 2030 attributable to diabetes through its impact on PLYs. CONCLUSIONS: Individuals incur significant costs of diabetes through lost PLYs and lost income in addition to disease burden through human suffering and healthcare costs. The government incurs extra welfare payments, lost taxation revenue and lost GDP, along with direct healthcare costs.

Economic costs of chronic disease through lost productive life years (PLYs) among Australians aged 45-64†years from 2015 to 2030: results from a microsimulation model.

OBJECTIVES: To project the number of older workers with lost productive life years (PLYs) due to chronic disease and resultant lost income; and lost taxes and increased welfare payments from 2015 to 2030. DESIGN, SETTING AND PARTICIPANTS: Using a microsimulation model, Health&WealthMOD2030, the costs of chronic disease in Australians aged 45-64 were projected to 2030. The model integrates household survey data from the Australian Bureau of Statistics Surveys of Disability, Ageing and Carers (SDACs) 2003 and 2009, output from long-standing microsimulation models (STINMOD (Static Incomes Model) and APPSIM (Australian Population and Policy Simulation Model)) used by various government departments, population and labour force growth data from Treasury, and disease trends data from the Australian Burden of Disease and Injury Study (2003). Respondents aged 45-64 years in the SDACs 2003 and 2009 formed the base population. MAIN OUTCOME MEASURES: Lost PLYs due to chronic disease; resultant lost income, lost taxes and increased welfare payments in 2015, 2020, 2025 and 2030. RESULTS: We projected 380 000 (6.4%) people aged 45-64 years with lost PLYs in 2015, increasing to 462 000 (6.5%) in 2030-a 22% increase in absolute numbers. Those with lost PLYs experience the largest reduction in income than any other group in each year compared to those employed full time without a chronic disease, and this income gap widens over time. The total economic loss due to lost PLYs consisted of lost income modelled at $A12.6 billion in 2015, increasing to $A20.5 billion in 2030-a 62.7% increase. Additional costs to the government consisted of increased welfare payments at $A6.2 billion in 2015, increasing to $A7.3 billion in 2030-a 17.7% increase; and a loss of $A3.1 billion in taxes in 2015, increasing to $A4.7 billion in 2030-a growth of 51.6%. CONCLUSIONS: There is a need for greater investment in effective preventive health interventions which improve workers' health and work capacity.

The indirect costs of back problems (dorsopathies) in Australians aged 45 to 64 years from 2015 to 2030: results from a microsimulation model, Health&WealthMOD2030.

This study projected the indirect costs of back problems through lost productive life years (PLYs) from the individual's perspective (lost disposable income), the governmental perspective (reduced taxation revenue, greater welfare spending), and the societal perspective (lost gross domestic product, GDP) from 2015 to 2030, using Health&WealthMOD2030-Australia's first microsimulation model on the long-term impacts of ill-health. Quantile regression analysis was used to examine differences in median weekly income, welfare payments, and taxes of people unable to work due to back problems with working full-time without back problems as comparator. National costs and lost GDP resulting from missing workers due to back problems were also projected. We projected that 90,000 people have lost PLYs due to back problems in 2015, increasing to 104,600 in 2030 (16.2% increase). People with lost PLYs due to back problems are projected to receive AU$340.91 less in total income and AU$339.77 more in welfare payments per week than full-time workers without back problems in 2030 and pay no income tax on average. National costs consisted of a loss of AU$2931 million in annual income in 2015, increasing to AU$4660 million in 2030 (60% increase). For government, extra annual welfare payments are projected to increase from AU$1462 million in 2015 to AU$1709 million in 2030 (16.9% increase), and lost annual taxation revenue to increase from AU$671 million in 2015 to $961 million in 2030 (43.2% increase). We projected losses in GDP of AU$10,543 million in 2015, increasing to AU$14,522 million in 2030 due to back problems.

Cluster Randomized Controlled Trial of An Aged Care Specific Leadership and Management Program to Improve Work Environment, Staff Turnover, and Care Quality.

OBJECTIVE: To evaluate the effectiveness of a leadership and management program in aged care. DESIGN: Double-blind cluster randomized controlled trial. SETTING: Twelve residential and community-aged care sites in Australia. PARTICIPANTS: All care staff employed for 6 months or longer at the aged care sites were invited to participate in the surveys at 3 time points: baseline (time 1), 9 months from baseline (time 2), and 9 months after completion of time 2 (time 3) from 2011 to 2013. At each time point, at least 500 care staff completed a survey. At baseline (N = 503) the largest age group was 45 to 54 years (37%), and the majority of care staff were born in Australia (70%), spoke English (94%), and had at least completed secondary education (57%). INTERVENTION: A 12-month Clinical Leadership in Aged Care (CLiAC) program for middle managers, which aimed to further develop their leadership and management skills in creating positive workplace relationships and in enabling person-centered, evidence-based care. MAIN OUTCOME MEASURES: The primary outcomes were care staff ratings of the work environment, care quality and safety, and staff turnover rates. Secondary outcomes were care staff's intention to leave their employer and profession, workplace stress, job satisfaction, and cost-effectiveness of implementing the program. Absenteeism was excluded due to difficulty in obtaining reliable data. Managers' self-rated knowledge and skills in leadership and management are not included in this article, which focuses on care staff perceptions only. RESULTS: At 6 months after its completion, the CLiAC program was effective in improving care staff's perception of management support [mean difference 0.61, 95% confidence interval (CI) 0.04-1.18; P = .04]. Compared with the control sites, care staff at the intervention sites perceived their managers' leadership styles as more transformational (mean difference 0.30, 95% CI 0.09-0.51; P = .005), transactional (mean difference 0.22, 95% CI 0.05-0.39; P = .01), and less passive avoidant (mean difference 0.30, 95% CI 0.07-0.52; P = .01); and were rated higher on the overall leadership outcomes (mean difference 0.35, 95% CI 0.13-0.56; P = .001) as well as individual manager outcomes: extra effort (P = .004), effectiveness (P = .001), and satisfaction (P = .01). There was no evidence that CLiAC was effective in reducing staff turnover, or improving patient care quality and safety. CONCLUSIONS: While the CLiAC leadership program had direct impact on the primary process outcomes (management support, leadership actions, behaviors, and effects), this was insufficient to change the systems required to support care service quality and client safety. Nevertheless, the findings send a strong message that leadership and management skills in aged care managers can be nurtured and used to change leadership behaviors at a reasonable cost.