The objective is to automate the migration of complex health economics Excel models based on Markov chains to modern software platforms, such as Mobile or Web. In this research project, we have developed a software solution that is capable of transforming a Microsoft Excel model into a self-contained platform-independent programming module.  This module fully preserves the original model along with cell values, formulas and dependencies, and is capable of running the model independently from the Microsoft Excel environment. The module is used as a basis for creating web and mobile applications supporting calculations identical to that in Excel model.  These applications will give the user means to manipulate model inputs and see the results of his actions immediately without having the full model delivered, thus preserving the confidentiality of proprietary data and algorithms. By using our method, several Excel based Markov cohort models with more than 1000 cycles were transformed and used as a basis for development of web-based and iPad applications for healthcare decision making.  These applications showed performance comparable to Microsoft Excel and complete outcomes correlation with the original model. With the proposed solution, mature Excel models developed over the years in various institutions can be connected with modern information technologies in a fast and reliable way.  Our method makes automated model transformation possible without human intrusion into a stable model core.  By eliminating the dependency on Microsoft Excel, we open new ways for integration of time-proven Excel models with modern software platforms, such as the Web or Mobile.