TreeAge Pro Healthcare 2008
Introduction
The TreeAge Pro Healthcare Module is designed to meet the special needs of health care professionals. The Healthcare module integrates seamlessly with TreeAge Pro and adds two types of functionality - Markov processes and cost-effectiveness analysis - of critical importance to anyone working on healthcare models.
TreeAge Pro Healthcare module also adds functionality to the core Monte Carlo simulation features already a part of TreeAge Pro.
Markov processes and cost-effectiveness analysis are included in the Healthcare module because it's hard to imagine serious modeling in this field which would not use at least one of these techniques. It does not follow, however, that all use of Markov processes and cost-effectiveness analysis is confined to healthcare-related questions.
Markov processes have application to a broad range of repetitive processes, such as marketing problems where consumers repeatedly face the same decision (which brand of coffee, milk, margarine, crackers, etc., to buy). The methodology is also used to model the changing states (condition) of physical plant, such as railroad tracks and ties, telephone polls, highway bridge components, in order to develop an optimal maintenance program.
Cost-effectiveness analysis
can be applied to a broad range of problems where the potential
costs exceed the potentially available funding. Examples of
current interest include protecting infrastructure against
possible terrorist attack, and optimal use of military to
contain and defeat terrorists.
Key Benefits
- Analyze better ways to monitor and improve quality of care
- Evaluate healthcare problems involving multiple transitions between health states
- Determine the most effective healthcare practices and interventions
- Efficiently represent cyclical, recursive events - both short and long term
- Assess the impact of healthcare services
- Easily understand benefits, risks and results of competing treatments
- Help determine the most effective treatment strategies
- Simplify complex healthcare decisions
- Evaluate the cost-effectiveness of competing drugs and treatments
- Efficiently build and analyze complex models
- Automatically simulate populations and cohorts by aggregating simulated individuals