Aperture is a purpose-built solution to speed up creation of data sets for clinical research. Aperture includes the following features:
- Exploration of lab results, diagnosis, risk factor,allergy, medication, care plan, organisation, practitioner, device and other variables
- In-database feature construction
- Feature selection
- Cohort selection
- Data set creation and extraction using CSV and SQL.
- Scheduling of tabular data generation
- Accountable transformation process for reproducible research
Aperture is complementary to existing tools for data analysis and analytic workspace management, acting as a pre-processing step to produce tabular data for consumption by statistics and analytics tools. With Aperture the complete transformation process from raw data to tabular data is documented and versioned, which enables re-use of constructed features, and also helps reproducible research and quality assurance of the transformation process.
Built on the MGRID Healthcare Data Model, Aperture can perform in-database operations to transform physical quantity continuous variables from one unit to another, for instance from mg/dL to mmol/L. In addition, for categorical coded values, Aperture has support for selections and calculations using knowledge from clinical and drug ontologies, to perform data selection and integration based on concept subtree search for hierarchical code systems such as SNOMED-CT, and search and transform drug features using synonym drug names, ingredients and interactions, based on the RxNorm database.