The goal was clear and the challenge was accepted.
The following objectives were set:
- Automate migration of complex health economics Excel models to the Web and Mobile Devices, such as iPad
- Avoid intruding into a stable model core
- Preserve 100% outcomes correlation
- Achieve calculation performance which would be comparable to that of Microsoft Excel or exceed it
- Be able to create state-of-the art graphical user interfaces based on the model core.
The following background points were taken into account:
- Existing web solutions, such as online spreadsheets [4, 5], are limited in their application for heavy Excel models. The model size is usually restricted by providers [4, 5] and the calculation time is rather high (Figure 5) that hinders users’ interaction with the model “live”
- Reusing Microsoft Excel for the web applications violates the end-user licence agreement with Microsoft .
Creating the proper methodology was the next step. Methodology consisted of the following points:
Figure 1: Solution Architecture
Model Migration Process
Figure 2 illustrates the migration process of an Excel model into a Web-based model.
Model deployment modes
A web based model can be deployed in one of three modes (illustrated in Figure 3):
- Client mode. Model is run completely on the client side and doesn’t require any server communication. This mode is used when:
- The model must function without internet connection
- Calculations must be carried out live (network latency is unacceptable)
- The model has to be delivered as a mobile app or standalone application.
- Server mode. Model is run completely on the server side. This mode is used for extremely heavy models which are too big to be loaded and run on the client side.
- Mixed mode. This mode is used for heterogeneous models which have both very heavy and very light calculations. Therefore, for sake of performance, heavy calculations are carried out on the server side, while the light ones are executed on the client.
Key Solution Characteristics
- Excel model (both xls and xlsm) – the size of the original Excel file;
Every Excel model consists of a set of cells and formulas which connect them. The performance of such model is determined by the following factors: cell access time and actual formula execution time. Markov models usually contain simple arithmetic formulas executed on a large amount (several hundreds of thousands) of interconnected cells. The formula execution time in such models is rather short; therefore the performance impact is determined by the amount of formulas executed and the number of cells accessed. In our benchmark we perform various arithmetic operations on sets of interconnected cells (chains) in a range of 1,000 to 200,000 cells. Speaking in terms of Markov models, 200,000 cells are equivalent to a model with 200 health states that evolve over 1,200 months. The results illustrated in Figure 5 were measured for the following devices: iPad 2 (iOS), Asus TF700 tablet (Android) and MacBook Air 2011 (MacOS) , and various web browsers.
Other Solution Characteristics
- Transformation speed. The model transformation is done automatically; therefore, the mathematical component (model core) of the web application is created within a few minutes.
- No human intrusion into the model core. Upon the automated model transformation, the human factor, which can lead to introduction of new errors in the stable model core, is excluded.
- Multiple end user delivery modes. Multiple model deployment modes allow for better tailoring the model performance to the user needs.
- Model Specific Optimizations. We apply specific optimizations which improve the model performance and reduce its size. The key is to concentrate on visible parameters only and remove all unrelated data.
- Scalability. In the “client” deployment mode all the calculations are moved to the client, thus unloading the server and allowing the support for the high number of concurrent users.
- In the “client” deployment mode, some initial loading time is required. The loading time varies depending on an internet connection speed and the
- A level of development and design is required to obtain a final web-based model
We have evaluated our solution for a typical large Markov-chain based health economic Excel model:
- The model was used to compare different treatment strategies and based on the Markov chains with age specific transition probabilities among 200 health states, that evolve over 1,200 monthly cycles. The model results were expressed as a number of accumulated clinical and economic outcomes as well as QALYs and Lys gained over a lifetime of a hypothetical cohort.
- The model size – 14 MB (xlsx), 33.5 (xls); Number of sheets used – 35; Number of non-empty cells – 765, 433; Maximum length of an interconnected cell chain – 220025
- The size of the original Excel model was reduced from 13.3 to 1.72 MB;
- The speed of the most heavy calculation was reduced from 0,185 to 0,15 seconds;
- Further optimize the engine, improve the performance and reduce the data size;
- Be able to easily integrate, accommodate or weave existing or new third-party solutions, such as spreadsheets or Excel;
Figure 6: Integrating Third Party Solutions
- Discover additional model value through integrating the model core with additional services such as Location based services, Social media. Online Databases [13, 14] and other services.
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