Clinical Trial Registration

Medical Trial Registration

Medical Trial Registration

Admin View

Admin View

Registering for a clinical trial involves ensuring consent, gathering information, validating where possible (e.g. GP practice, postcodes, telephone numbers, emails, NHS numbers). This example system also includes automatic email reminders and matching of twins.

Data security is paramount in designing, building and running this system.

No prizes for guessing where the look and feel comes from, most used site on 31st Jan?

Clinic staff have access to an Admin view of the data enabling search, edit, matching twins manually etc.

The fully completed data can be extracted for the main department database.

The technology used is primarily Rails, Bootstrap, Postgres with Python/Pandas running on a nginx/thin services on an CentOS virtual server.

Data Requests

Phenotype Requests

Phenotype Requests

Once data, samples (phenotypes) have been collected and collated, researchers can request access. This is a non-trivial process of collecting request details and authorisation. 

Clinic staff have access to an Admin view of the data enabling search, edit and monitoring the process.

The technology used is primarily Rails, Bootstrap, Postgres with Python running on a nginx/thin services on an CentOS virtual server.

Phenotype Storage (in development)

Participant Phenotypes

Participant Phenotypes

Query using NHS FHIR SNOMED CT API

Query using NHS FHIR SNOMED CT API

The system supports the loading, storing, query and extraction of phenotype data. Phenotypes vary greatly from measures to questions so the Observational Medical Outcomes Partnership (OMOP) Common Data Model was used as an initial database design.

An Extract Transform & Load (ETL) solution maps incoming CSV format text files to the model. During the import process the phenotype data is indexed using both SNOMED CT terms and text.

The data can then be queried using a wildcard text query, SNOMED Expression Constraint Language (ECL) query and a hybrid “Snomed” approach comprising a wildcard query of any matching SNOMED CT terms followed by an ECL expansion query. SNOMED CT is a polyhierarchical thesaurus, where terms can have multiple parents and children. An ECL expansion query can be used to obtain results for any child terms (e.g. ECL query for “33468001 | Hematology procedure |” will pick up child terms such as “43396009 | Hemoglobin A1c measurement |”). This enables phenotype data to be indexed with low level / detailed terms and then retrieved using high level general terms.

SNOMED and ECL queries are via the NHS FHIR API (fast and currently free!)