SHINE stands for Scalable Health Intervention Evaluation. SHINE quantifies the future health and cost impacts of preventive, screening and treatment interventions. Using league tables and graphs, we then compare the health, cost and cost effectiveness of multiple interventions that have been evaluated by the same standardized methods used in SHINE.
SHINE-Consulting is that part of SHINE that provides services to clients in policy institutions, NGOs and the private sector. SHINE also provides services to other researchers, either as part of SHINE-Consulting or a more traditional collaborative approach as outline at SHINE-Research .
SHINE offers the following tools and services:
- Australian NZ Health Intervention League Table (ANZ-HILT) . This free tool collates and compared interventions conducted with similar methods and data in Australasia, ranging from the ACE Prevention to stand alone publications.
- Health Intervention Impact Calculator (HIIC) . HIIC is a free online calculator in protype form. It will allow users to estimated health adjusted life years gained, and health expenditure averted (cost offsets) for any intervention specified in terms of:
- A change in disease incidence rate(s)
- And in the future changes in disease morbidity and disease case fatality rates.
- A change in risk factors (e.g. tobacco, physical activity)
- COVID-19 Pandemic Tradeoffs . This online data visualization tool, periodically updated for new data, gives estimates of infection/hospitalisation/ICU/death rates, and time in lockdown, for 100s of scenarios for varying vaccine coverage, in-country suppression strategies and expected daily cross-border quarantine-free arrivals of vaccinated but infected people.
- Customized consultancy services. For evaluations beyond those that can be retrieved from the above tools or where the user prefers us to generate the findings, SHINE undertakes bespoke quantification of intervention impacts and other services:
- Evaluations of primary and secondary preventative interventions. The options are unlimited. Evaluations will typically be specified in terms of:
- An intervention module:
- How the intervention leads to changes in risk factors, or changes in disease incidence/morbidity/case fatality rates directly
- What the world looks like without the intervention (business-as-usual)
- How many people are impacted by the intervention, for how long, with what attenuation
- Scaling-down. If the user is interested in comparing sub-populations, e.g. socioeconomic groups to determine inequality impacts, or disease risk strata (e.g. absolute risk of CVD event in the next five years) to determine the most (cost) effective sub-populations to intervene in.
- Scaling-up. If the user is interested in packages of interventions, and their total health and cost impacts.
- Scaling-out. If the use is interested in the same analysis being conducted across multiple states or territories, or multiple countries.
- An intervention module:
- For a cost-effectiveness analysis, what the upfront and ongoing costs are of the intervention
- The types of outputs required, including differences between intervention and BAU for:
- Health adjusted life years (HALYs), including by time period into the future
- Deaths averted in the first 10, 20 or so years
- Health expenditure impacts (usually reduction) due to changes in future disease incidence, prevalence and mortality
- Income gains due to a healthier working age population. More specifically, the productivity gains from a human capital perspective, using linked disease-tax data from NZ purchase power parity adjusted to Australia.
- Changes in future risk factor distributions
- Changes in future disease incidence/prevalence/morbidity/mortality rates
- Other services such as in-depth modelling of intervention options (e.g. as per our agent-based model for COVID-19), lifetable analyses to inform study power, and such like.
Please see the main SHINE page for Research Outputs
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