Experimental Medicine Application Platform (EMAP) produces a near real-time database containing clinical data for research and dashboard development within UCLH.

This is a non-operational “mirror” of a subset of UCLH data (historical and live). The underpinning aim is to ensure that no clinical data are corrupted or destroyed during the interaction between the research process and the hospital’s systems and that the systems are not compromised (for instance, that they are not interrupted or slowed down by research enquiries).

• Technical overview

• Historical overview

PIXL Image eXtraction Laboratory (PIXL) is a system for extracting, linking and de-identifying DICOM imaging data, structured EHR data and free-text data from radiology reports at UCLH.

Learn more about PIXL

• System design

• Deidentification

We use Cogstack to anonymise free text data from clinical notes and imaging reports.

A detailed description is available on our wiki.

FlowEHR 🌺 is a safe, secure & cloud-native development & deployment platform for digital healthcare research & innovation.

We designed this to:

• Enable iterative, robust & sustainable development & deployment of digital interventions at UCLH by enabling our multi-disciplinary teams to work higher up the stack

• Add momentum to the Trust’s digital transformation journey

• Establish UCLH/UCL as the premier partner for academia, the HealthTech sector and the UCLP Academic Health Sciences Network

• Cross the Machine Learning for Healthcare (ML4H) chasm

and to ultimately provide direct benefit to patient outcomes and the health system.

It should be considered as an evolution of the original vision for EMAP as UCLH’s Experimental Medicine Applications Platform.

Our primary and original use case is the safe & effective development & deployment of real-time translational Machine Learning interventions in clinical and operational settings inside the hospital.

FlowEHR is pronounced like flower.

By default, UCLH clinical data is provided for research in a format called the OMOP Common Data Model (CDM), also referred to as simply ‘OMOP’.

OMOP-ES is our OMOP data Extraction Pipeline. It allows a diverse range of data and systems to be mapped to OMOP in a controlled, governed manner – with rules to anonymise and redact data so as to respect the privacy of patients.

OMOP-ES easily allows new types of data to be incorporated, enforces high quality mapping and portability to other EPIC sites.