Identifying clinical/translational research cohorts: ascertainment via querying an integrated multi-source database

Ascertainment of potential subjects has been a longstanding problem in clinical research. Various methods have been proposed, including using data in electronic health records. However, these methods typically suffer from scaling effects-some methods work well for large cohorts; others work for small cohorts only.

We propose a method that provides a simple identification of pre-research cohorts and relies on data available in most states in the USA: merged public health data sources.

The Utah Population Database Limited query tool allows users to build complex queries that may span several types of health records, such as cancer registries, inpatient hospital discharges, and death certificates; in addition, these can be combined with family history information. The architectural approach incorporates several coding systems for medical information. It provides a front-end graphical user interface and enables researchers to build and run queries and view aggregate results. Multiple strategies have been incorporated to maintain confidentiality.

This tool was rapidly adopted; since its release, 241 users representing a wide range of disciplines from 17 institutions have signed the user agreement and used the query tool. Three examples are discussed: pregnancy complications co-occurring with cardiovascular disease; spondyloarthritis; and breast cancer.

This query tool was designed to provide results as pre-research so that institutional review board approval would not be required. This architecture uses well-described technologies that should be within the reach of most institutions.