Health Economic Modeling with TreeAge Pro
Build healthcare models to evaluate treatment and diagnosis strategies
With limited budgets, it is critical for healthcare decisions to be made rationally based on healthcare costs and health outcomes.
TreeAge Pro is the tool you need to quickly build models to make better healthcare policy decisions.
Built-in cost-effectiveness analysis and other analysis tools to assess whether a new treatment provides sufficiently better health outcomes to justify its cost based on the Incremental Cost-Effectiveness Ratio (ICER).
Modeling Frameworks
Modeling frameworks make it easy to build many types of models in a standard visual structure. Create your patient pathways, add your inputs, and you’re ready to go.
- Decision Trees
- Markov Models
- Patient Simulation
- Discrete Event
- Partitioned Survival
Analysis Tools
TreeAge Pro’s built-in analysis tools generate the reports and graphs you want in a single click. All analyses are applied directly to your model’s patient pathways and inputs with no coding required.
- Cost-Effectiveness
- Markov Cohort Trace
- Sensitivity Analysis
- Probabilistic Sensitivity Analysis
- Budget Impact
Models Simulate Patient Treatment
Healthcare models are designed to represent true health issues and the consequences of treatments. With TreeAge Pro, you build the pathways visually based on your expertise on the issue.
Sophisticated healthcare simulation models use the same frameworks as more typical cohort models, so they’re just as easy to build. Running simulated patients expands the scope and flexibility of your model by allowing for changes to pathways and values based on patient characteristics and patient history.
Build models quickly with TreeAge Pro
with no coding required
- Add your strategies
- Build patient pathways visually
- Enter and reference inputs
- Analyses with a single click
TreeAge Pro grows with you
TreeAge Pro provides advanced healthcare modeling tools for our complex health economic research projects.
- Markov
- Patient Simulation
- Partitioned Survival
- Calibration
- And more
Decision Trees
Create Decision Trees to map out patient pathways visually to create a full picture of what could happen to patients as a result of treatment/diagnostic strategies. Incorporate probabilities of events into the decision tree, so that each pathway is weighted appropriately based on its likelihood. Build in the impact of each pathway in terms of cost and health outcomes. Then analyze the tree to determine which strategy provides the best value for patients.
Markov Models
Create Markov Models to extend the power of Decision Trees to map out disease progression over time. By breaking progression into a series of Health States and Events, Markov models accurately represent disease progression for the patient cohort. Built-in Markov calculations account for some patients progressing quickly while others may progress slowly or not at all, generating the average expected impact on cost and health outcomes for comparison with other strategies.