CDRGen: A Clinical Data Registry Generator (Formal and/or Technical Paper)

Abstract

In the health sector, data analysis is typically performed by specialty using clinical data stored in a Clinical Data Registry (CDR), specific to that medical specialty. Therefore, if we want to analyze data from a new specialty, it is necessary to create a new CDR, which is usually done from scratch. Although the data stored in CDRs depends on the medical specialty, typically data has a common structure and the operations over it are similar (e.g., entering and viewing patient data). These characteristics make the creation of new CDRs possible to automate. In this paper, we present a software system for automatic CDR generation, called CDRGen, that relies on a metadata specification language to describe the data to be collected and stored, and the types of supported users as well as their permissions for accessing data. CDRGen parses the input specification language and generates the code needed for a functional CDR. The specification language is defined on top of a metamodel that describes the metadata of a generic CDR. The metamodel was designed taking into account the analysis of eleven existing CDRs. The experimental assessment of the CDRGen indicates that: (i) developers can create new CDRs more efficiently (in less than 2% of the typical time), (ii) CDRGen creates the user interface functionalities to enter and access data and the database to store that data, and finally, (iii) its specification language has a high expressiveness enabling the inclusion of a large variety of data types. Our solution will help developers creating new CDRs for different specialties in a fast and easy way, without the need to create everything from scratch.

P. Alves—This work was developed while the author was a Master student at IST.