Imperial College Case Study
30% Productivity Gains
How Oka-Bi Automation Accelerated a Healthcare Data Platform with Privacy Enhancing Technology
Challenge
Imperial College NIHR Biomedical Research Centre needed to develop an internal data warehouse in order to support Pulmonary Hypertension research. Stringent requirements included the robust protection of Personally Identifiable Information (PII) as well as ability to integrate with Qlik Business Analytics Systems. During the project, Oka-Bi were also engaged to build a web base biobank management system and database, and to integrate into the data privacy/analytics platform, protecting the identities of patients who provided samples.
Solution
Oka-Bi deployed its SQL Server based data privacy and automation framework (then called "The Oka-Bi Pseudonymisation Toolkit") in order to accelerate the delivery of the data warehouse, whilst employing Privacy Enhancing Techniques at the heart of the software to protect PII. Oka-Bi then trained internal Imperial College data administrators in use of the software, before concluding the BioBank web based system build & integration with the data warehouse.
Result
30% productivity gain compared to manual consultancy builds, enabling a powerful internal capability in the college to integrate further datasets into the platform, which integrated ~20 systems over the next 10 years.
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30% Time To Risk Reduction (TTRR) achieved
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Enablement of internal Database Administrators to automate and self serve new dataset integrations
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Successful integration with Imperial College NHS Infrastructure, BioBank Website and Qlik analytics
We chose the Oka-Bi Pseudonymisation Toolkit for our Translational Research in Pulmonary Hypertension at Imperial College (TRIPHIC) programme because it combined the stringent protection of patient information with a flexible and scalable approach to handling data from diverse sources. With the support of Oka-Bi, we have been able to develop a robust system that links together clinical datasets, helps manage the associated biological samples in our Bio-repository and makes pseudonymised information available for research purposes. Oka-Bi enabled us to be self-reliant and remain fully in control of the data, within our infrastructure.
Professor Martin Wilkins, Imperial College