TreeAge Pro Webinars
We are pleased to present a series of free webinars to help you become more familiar with key features of TreeAge Pro. Our experienced trainers will present these webinars as 30 minute online sessions.
We currently have one webinar scheduled for 2020:
- Partitioned Survival Analysis – 11 & 12 February 2020
– Let us show you around the new features of Partitioned Survival Analysis for TP2020.
– Learn about using Exit costs/utilities to accumulate value as the cohort leaves a state (Exit rewards).
– Use Hazard functions to define state membership and explore other the Survival functions.
You can also register your interest for future webinar and we will email you the schedule.
Past Webinar Recordings
The webinars were recorded live with no subsequent editing. Please forgive any mistakes made during the presentations.
- Model Calibration – published from a recording on 2020/01/15.
Calibration automatically adjusts selected model input values to generate outputs that match observed clinical data.
– It is critical that models mirror true disease progression and treatment effects as accurately as possible.
– Choose to replace the original model input values with the new values identified by the calibration process.
– New feature available for active licenses in January 2020.
- Probabilistic Sensitivity Analysis to measure Uncertainty – published from a recording on 2019/10/08.
Probabilistic Sensitivity Analysis (PSA) measures the impact of uncertainty on model outcomes.
– Add parameter distributions into your model using TreeAge Pro’s built-in distribution builder.
– Examine the tools available to measure confidence in your conclusions.
– Use TreeAge Pro’s built-in analyses and reports to examine parameter uncertainty in different ways.
- Partitioned Survival Analysis – published from a recording on 2019/09/10.
– Learn about Partitioned Survival Analysis (PartSA) models – frequently used to compare interventions in Oncology.
– Our experts will show you how to easily create Partitioned Survival models, mapping the state of the cohort from survival data.
– Explore survival curves, the analysis and the interpretation of outcomes.
– These features are available in TreeAge Pro 2019 R2.
– Commonly asked questions at the webinar are answered in out Knowledge Base (follow the link).
- Incorporating Patient history (Trackers) – published from a recording on 2019/05/13.
– Learn step-by-step how to capture patient history.
– Use patient history to impact model values.
– Use reporting tools to review patient history.
- Reviewing TreeAge models – published from a recording on 2019/04/09.
– Review patient pathways and model configuration.
– Explore the tools available to find information about your model.
– Compare strategies through Cost Effectiveness Analysis.
– Study uncertainty through Sensitivity Analysis.
- Reuse patient pathways (clones) – published from a recording on 2019/03/13.
– Learn about re-using model structure via clones.
– Best practice to save time model building.
– Tips to check for errors.
- Sharing models – published from a recording on 2019/02/12.
– Use Excel to share model scenarios created in TreeAge.
– Convert Markov Cohort models to fully stand-alone Excel models.
- Patient Level Simulation made easy – published from a recording on 2019/01/22.
– Leverage the power of patient level simulation to introduce heterogeneity and track critical patient events.
– Learn to incorporate Real World Data in your model via bootstrapping.
– Use the built in reporting to quickly validate your model and assumptions.
– Seeding your model to get repeatable results from simulations.
- Debunking the Black Box! – published from a recording on 2018/11/29.
– “Look under the hood” to validate TreeAge Pro models.
– Follow your patients as they pass through the model using patient tracking reports for both cohort and simulation models.
– Review every step in complex calculations
– Convert your Markov Cohort model to a standalone Excel model with a single click, then examine the calculations in Excel.
- Debugging TreeAge Pro Models – published from recording on 2018/02/20
– Configure your model to review internal calculations behind model analyses.
- Infectious Disease Modeling (Dynamic Cohorts) – published from recording on 2018/03/15.
– Make cohort transition probabilities dependent on how the overall cohort is distributed among the Health States.
– Use a full cohort size rather than fractions of a cohort of size 1.
– Add to the cohort size with time.
- Validate Your Model by Reviewing Patient Flows in Markov Models – published from recording on 2018/04/05
– Examine how your cohort moves through health states and transitions via Markov Reporting.
– See how cost and eff values are accumulated within the context of the cohort movement.
- Patient Interaction with a Limited Resource – published from recording on 2018/05/10
– Run patients through your model at the same time to facilitate patient interaction (Parallel Trials).
– Manage patient competition for limited resources – manage resource usage and release (Stop Nodes).
– Manage the overall model environment by storing global data accessible to all patients (Global Trackers)
- Review Patient Pathways in a Patient Simulation Model – published from recording on 2018/06/07
– Review every event in each patient’s disease progression including when/how cost and effectiveness was accumulated.
– Review patient pathways with aggregated cohort-level reports to study and validate patient flows.
- Sensitivity Analysis: What if your parameter assumptions are wrong? – published from recording on 2018/07/31
– Use univariate sensitivity analysis tools for model validation. Examine how parameter uncertainty affects your model outputs. Could this change your strategy recommendation?
– Create Tornado diagrams to examine the relative effect of individual parameter uncertainties on your model.
- How confident can you be about your model conclusions? – published from recording on 2018/08/27.
– Models contain many assumptions about parameter values. Probabilistic Sensitivity Analysis (PSA) measures the impact of uncertainty on model outcomes.
– Measure confidence in your conclusions.
– Integrate parameter distributions into your model for PSA using TreeAge Pro’s built-in distribution builder.
– Run PSA using TreeAge Pro’s built-in analyses and reports to examine parameter uncertainty in different ways.
- DES: Build Discrete Event Simulation models in TreeAge Pro – published from a recording on 2018/09/25
– Compare and contrast Markov and DES models in TreeAge Pro.
– Examine the important elements of DES models including time-to-event distributions, accumulating cost and utility over time, and other considerations.