State of the Art Decision Analysis for Healthcare

The TreeAge Pro Healthcare Module integrates seamlessly with TreeAge Pro, adding Markov processes, comparative effectiveness and cost-effectiveness analysis, functionality of critical importance in many healthcare decision models. The Healthcare module also adds functionality to TreeAge Pro's Monte Carlo simulation engine, in order to fully support Markov, comparative effectiveness and cost-effectiveness models.

The Healthcare module is designed to meet the special needs of professionals and students in healthcare, health services research, and pharmacoeconomics. Although Markov, comparative effectiveness and cost-effectiveness models are used primarily in health-related fields, the Healthcare module also has applications in other areas. Markov models can be used to represent and analyze the uncertainties found in complex and repetitive processes, such as systems maintenance and product marketing. Markov models can incorporate the changing states (conditions) of markets, physical plant, and communications/transportation infrastructure.

Cost-effectiveness analysis can be applied to a broad range of problems where the non-monetary benefits of various strategies must be balanced against their potential costs, taking into account available budgets. Examples include decisions about environmental disaster cleanup, protecting infrastructure against possible terrorist attack, and optimal use of military resources.

Key Benefits

• Analyze potential changes in healthcare practices and priorities
• Evaluate the cost-effectiveness of complex treatments for multiple sub-populations
• Represent both short- and long-term diseases and interventions
• Communicate the relative benefits and risks of competing treatments
• Simulate the uncertainty in costs and effects of treatments

Features
Markov Models Calculate survival using a state transition model, in order to determine expected cost and effectiveness. Run cohort analysis, generate survival curves, and run microsimulations.

Cost-Effectiveness Analysis Analyze competing strategies' on the basis of cost and effectiveness, incremental cost-effectiveness, net health benefits, and net monetary benefits.

Monte Carlo Simulation Resample parameter values from historical data stored in tables, or from 18 continuous or discrete probability distributions. Reevaluate the tree using 1-, 2-, or 3-dimensional simulations with millions of iterations. Run lengthy simulations using multiple processors or a network of computers.

Reporting Display, print, and export a variety of text reports, histograms, scatter plots, bar graphs and more …