Mapping the 12-item World Health Organization disability assessment schedule 2.0 (WHODAS 2.0) onto the assessment of quality of life (AQoL)-4D utilities.

PURPOSE: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a widely used disability-specific outcome measure. This study develops mapping algorithms to estimate Assessment of Quality of Life (AQoL)-4D utilities based on the WHODAS 2.0 responses to facilitate economic evaluation. METHODS: The study sample comprises people with disability or long-term conditions (n = 3376) from the 2007 Australian National Survey of Mental Health and Wellbeing. Traditional regression techniques (i.e., Ordinary Least Square regression, Robust MM regression, Generalised Linear Model and Betamix Regression) and machine learning techniques (i.e., Lasso regression, Boosted regression, Supported vector regression) were used. Five-fold internal cross-validation was performed. Model performance was assessed using a series of goodness-of-fit measures. RESULTS: The robust MM estimator produced the preferred mapping algorithm for the overall sample with the smallest mean absolute error in cross-validation (MAE = 0.1325). Different methods performed differently for different disability subgroups, with the subgroup with profound or severe restrictions having the highest MAE across all methods and models. CONCLUSION: The developed mapping algorithm enables cost-utility analyses of interventions for people with disability where the WHODAS 2.0 has been collected. Mapping algorithms developed from different methods should be considered in sensitivity analyses in economic evaluations.

The impact of Disability Insurance reassessment on healthcare use.

Several Organisation for Economic Co-operation and Development countries have constrained Disability Income Insurance (DI) eligibility and reassessed those on DI to encourage workforce participation. But these policies can also have unintended consequences. While receiving less income can directly worsen physical and mental health, the stress related to reassessment and the possibility of losing DI may also adversely affect mental health. This paper uses Australian population-wide administrative data to explore how a 2014 policy - where DI recipients under 35 were reassessed under stricter criteria - affected healthcare use. We exploit this age targeting using a difference-in-difference regression design and find that the policy increased nervous system drug prescriptions (which includes antidepressants). Our findings suggest that the reassessment of DI recipients, even without income loss, may have had a significant negative impact on their mental health. DI reassessment policies may have the unintended consequence of worsening mental health and this needs be considered when deciding if reassessment is worthwhile.

Social interventions to support people with disability: A systematic review of economic evaluation studies.

Social interventions are essential in supporting the health and well-being of people with disability, but there is a critical need to prioritise resources for those that provide the best value for money. Economic evaluation is a widely used tool to assist priority setting when resources are scarce. However, the scope and consistency of economic evaluation evidence for disability social services are unclear, making it hard to compare across interventions to guide funding decisions. This systematic review aims to summarise the current evidence in the economic evaluation of social services for people with disability and to critically compare the methodologies used in conducting the economic evaluations with a focus on the outcomes and costs. We searched seven databases for relevant studies published from January 2005 to October 2021. Data were extracted on study characteristics such as costs, outcomes, perspectives, time horizons and intervention types. Overall, economic evaluation evidence of social services for people with disability was scarce. Twenty-four economic evaluations were included, with the majority conducting a cost-effectiveness analysis (n = 16). Most interventions focused on employment (n = 10), followed by community support and independent living (n = 6). Around 40% of the studies addressed people with mental illnesses (n = 10). The evidence was mixed on whether the interventions were cost-effective but the methods used were highly variable, which made comparisons across studies very difficult. More economic evidence on the value of interventions is needed as well as a more standardised and transparent approach for future research.

Association between density of gaming venues in a geographical area and prevalence of insolvency: longitudinal evidence from Australia.

BACKGROUND AND AIMS: Problem gambling can lead to a myriad of harmful consequences, including unmanageable amounts of debt and serious financial problems. The aim of this study was to examine whether changes in the number of electronic gaming machine (EGM) venues within a local area (due to venue openings and closings) are associated with changes in the rates of serious financial problems. DESIGN: Area-level longitudinal multivariate regressions controlling for possible confounders (fixed and time-varying local area characteristics). SETTING: Australia's three largest states (New South Wales, Victoria, Queensland), during the period 2011-18. PARTICIPANTS: A total of 225 local areas (Statistical Area 3 level) within the three states. MEASUREMENTS: Serious financial problems were measured by administrative data on total number of personal insolvencies (bankruptcies, debt agreements and insolvency agreements) in each local area per annum. The number of EGM venues in each local area was the regressor of primary interest. Area-level covariates included the number of non-gaming pubs and clubs, unemployment rate, population count, local area dummies, local area linear time trends and a separate set of state dummies for each year. FINDINGS: A one-venue decrease over time within a local area decreased the number of personal insolvencies by 1.8 per year [95% confidence interval (CI) = 0.4-3.2]. The result is robust to alternative specifications, including allowing for geographical spillovers (ß = 2.2, 95% CI = 0.7-3.7), temporal lagged effects (ß = 1.6, 95% CI = 0.6-2.8) and the spatial variability of venues within areas (ß = 2.7, 95% CI = 0.9-4.5). CONCLUSIONS: There is a positive association between the number of gaming venues in a local geographic area and the number of personal insolvencies in that area. Reducing the number or accessibility of gaming venues could help to reduce financial harms associated with problem gambling.