A Solution to Bridge the Gap Between Data Collection and Analysis

In the continuing battle to track and understand the incidence and distribution of disease around the world, public health information technologies that speed up epidemiologic studies are critical to researchers’ success. Two large challenges for epidemiologists are the collection of data and the statistical analysis of data. Excellent software exists for both, yet there is no simple method of transferring and manipulating data from one process into the other. The researcher must collapse records, drop observations, stratify variables, query for missing data, and merge datasets in either a long, difficult-to-read program, or in a set of commands that are difficult to retrace. Additionally, compatibility of storage and statistical analysis package formats is also exigent.

Cancer studies had been hindered at the US Air Force School of Aerospace Medicine (USAFSAM), due to the magnitude of effort and time to configure the disparate sources data for analysis, thus slowing epidemiologic and prevention efforts. Integrated Solutions Inc., in collaboration with the USAFSAM, bridged this data collection to analysis gap by designing a novel software application. It is developed on a Service-Oriented Architecture (SOA) based platform and efficiently integrates and extracts epidemiological data from multiple sources for a wide array of study designs. This software assists researchers, including those without programming experience, in dynamically applying inclusion and exclusion criteria, merging and splitting records or datasets and extracting the necessary data. It allows the researcher to visualize and document the dataset configuration process and its results, and export the datasets to a variety of statistical analysis packages. This technology provides web-based, graphical, and re-usable interface modules that interact with the behind-the-scene databases. Use of this software could significantly decrease time and effort to accomplish research. This will lead to faster policy making and rapid delivery of interventions resulting into efficient disease prevention, therefore, saving lives.