##ForLAB (multi-method laboratory quantification tool)
ForLab is a standardized, open-source tool developed by CHAI and SCMS with clearly defined requirements, improving programs’ ability to collect and analyze data to accurately forecast commodity needs. ForLAB performs long- and short-term forecasts and guides improvements in diagnostic services.
###Functionality & features
- Able to analyze the following data sets to
generate informed, evidence-based forecasts:
- Service statistics (test numbers)
- Logistics data (consumption)
- Demographic (program targets)
- Able to import high volumes of data from MS-Excel template file
- Compares forecasting methodologies to identify programmatic and commodity gaps
- Analyzes actual and forecasted instrument utilization, diagnostics contribution, and instrument diversity
- Models cost estimates costs associated with guideline shifts
###Benefits within the quantification process
- Planning & Preparation: Focuses data collection efforts to populate a standardized template
- Reduces forecasting analysis time to minutes
- Improves the reliability of the forecast
- Demand and supply planning: Promotes development of evidence-based supply plans
- Resource analysis: Provides the opportunity to identify efficiencies within a laboratory network
- Validates consumption with service rates
###Source code
- Clone the sources: git clone https://github.com/forlab/ForLAB.git
###Building
For the full supported experience, you will need to have Visual Studio 2010 or later.
To get started on Visual Studio 2010:
- Install Visual Studio 2010 or later.
- Clone the source code (see above).
- Open LQT.sln solution in Visual Studio 2010.
###How to Engage, Contribute and Provide Feedback
Before you contribute, please read through the contributing and developer guides to get an idea of what kinds of pull requests we will or won't accept.
Want to get more familiar with what's going on in the code?
You are also encouraged to start a discussion by filing an issue or creating a gist.
###Found a bug? Another way you can contribute to ForLAB is by providing issue reports, for information on how to submit an issue report refer to our online guide for reporting issues.
To view existing issues please visit https://github.com/forlab/ForLAB/issues
###License ForLAB is licensed under the Affero GPL (AGPL) v3.