Impact of the Medicare Benefits Schedule Rebate (MBSR) freeze on General Practice (GP) use: multivariable regression analysis.

BACKGROUND: In 2015, the Australian government froze the Medicare Benefits Schedule Rebate (MBSR) for General Practitioner (GP) service use. This paper aimed to explore the impact of the MBSR freeze on the demand for GP services in Victoria, Australia, for three years, from 2014 to 2016. METHOD: Annual data on GP service utilisation by the Victorian State Statistical Area Level 3 (SA3) were analysed using 2015 as the reference year (MBSR freeze year). We compared annual per-person GP service use before and after the MBSR freeze for each SA3. Socioeconomic Indexes for Areas (SEIFA) scores and regions of Victoria (Greater Melbourne and the Rest of Victoria) were used to identify the most disadvantaged SA3s in Victoria. We conducted a multivariable regression analysis for the number of GP services per patient by SA3, controlling for regions of Victoria, the number of GP services, the proportion of bulk-billed visits, age group, gender and year. FINDINGS: After adjusting for age group, gender, region, SEIFA, the number of GPs and the proportion of bulk-billed GP visits, mean GP services per person per year declined steadily between 2014 and 2016, with a 3% or 0.11 visit (-0.114, 95%CI: -0.134; -0.094, P = < 0.001) reduction in mean utilisation in 2016 compared to 2014. In disadvantaged SA3s, there was a fall in the number of GP services that were bulk-billed during and after the MBSR freeze compared to 2014, and this fall was large in LOW SEIFA SA3s, with a reduction in 17% of mean bulk-billed GP services. CONCLUSION: The MBSR freeze for GP consultations in 2015 resulted in a reduction in the annual per capita demand for GP visits, with the impact of reduced demand more significant in lower socioeconomic and regional/rural areas. The GP funding policies must consider the demand differences by social-economic status and location.

Obesity and Bariatric Surgery in Australia: Future Projection of Supply and Demand, and Costs.

INTRODUCTION: The prevalence of obesity is increasing in developed countries, including Australia. There is evidence that bariatric surgery is effective in losing weight and reducing risk of chronic diseases. However, access to bariatric surgery remains limited in the public health sector. METHOD: We modelled population-based estimates of the likely numbers of people eligible for bariatric surgery in Australia using the recent Australian New Zealand Metabolic and Obesity Surgery Society (ANZMOSS) framework and estimated the potential costs that would be incurred from primary and subsequent reoperations in both public and private sector. RESULTS: The annual number of newly eligible patients is expected to rise, and hence the gap in demand is increasing relative to current baseline supply. If a 5-year program to treat all currently eligible patients was implemented, the maximum yearly demand is projected to be 341,343 primary surgeries, more than eight times the existing capacity of public and private sector, which can only offer 41,534 surgeries/year. A nine-fold increase is expected if we treat currently eligible patients over a 5-year program and all newly eligible patients as they occur each year. CONCLUSION: Our results highlighted the currently highly skewed distribution of bariatric surgeries between the private and public sectors. Improving access would bring substantial benefits to many Australians, given the demonstrated cost-effectiveness and cost savings. This requires a major increase in resourcing for publicly-funded access to bariatric surgery in the first instance. A national review of priorities and resourcing for all modes of obesity treatment is required in Australia.

Scoping review: Development and assessment of evaluation frameworks of mobile health apps for recommendations to consumers.

OBJECTIVE: The study sought to review the different assessment items that have been used within existing health app evaluation frameworks aimed at individual, clinician, or organizational users, and to analyze the scoring and evaluation methods used in these frameworks. MATERIALS AND METHODS: We searched multiple bibliographic databases and conducted backward searches of reference lists, using search terms that were synonyms of "health apps," "evaluation," and "frameworks." The review covered publications from 2011 to April 2020. Studies on health app evaluation frameworks and studies that elaborated on the scaling and scoring mechanisms applied in such frameworks were included. RESULTS: Ten common domains were identified across general health app evaluation frameworks. A list of 430 assessment criteria was compiled across 97 identified studies. The most frequently used scaling mechanism was a 5-point Likert scale. Most studies have adopted summary statistics to generate the total scoring of each app, and the most popular approach taken was the calculation of mean or average scores. Other frameworks did not use any scaling or scoring mechanism and adopted criteria-based, pictorial, or descriptive approaches, or "threshold" filter. DISCUSSION: There is wide variance in the approaches to evaluating health apps within published frameworks, and this variance leads to ongoing uncertainty in how to evaluate health apps. CONCLUSIONS: A new evaluation framework is needed that can integrate the full range of evaluative criteria within one structure, and provide summative guidance on health app rating, to support individual app users, clinicians, and health organizations in choosing or recommending the best health app.