Data Lake Solutions for Healthcare
Delivering Unified Healthcare Data Systems to Public Healthcare Authorities in 6 months, not 6 years.
Turn Your Healthcare Challenge into an Opportunity
COVID-19 has exposed the lack of coherent and joined-up information systems across and within public healthcare systems in Europe, Asia, and the Americas. What data is available is siloed and is not easily integrated, which has resulted in public healthcare systems struggling to respond to the pandemic in an agile manner. The lack of a coherent and joined-up information system means that we still cannot answer many important clinical questions of relevance to this epidemic:
What existing conditions pre-dispose people to Covid-19 infection or a bad outcome?
How do authorities deploy their resources to maximise their efficiency and provide better care to patients in their system?
Why do some younger people need hospitalisation but most barely notice the infection?
What defines best work practices in the healthcare community, so that preparations can be made to adapt and prepare for a second wave?
A Unified Healthcare Data System would not only allow us answer all of these questions, it would enable us better manage and understand the risk factors around major non-infectious diseases such as cancer, heart disease, stroke and diabetes which are the main work of Public Healthcare Authorities between pandemics.
The BDM Health Solution
Existing data systems – Electronic Health Records, Pathology Systems, Primary Care Data Systems, etc – cannot and should not be expanded to give an overview of what is happening in the overall healthcare system. They should be allowed continue doing the job that they were designed and installed to do.
What is required instead is to build a Data Lake into which these disparate systems can deliver their data. Ingesting data into this data lake from these systems, in a secure and compliant manner, will allow this data to be combined to provide complete views of the data from a patient, disease, care and administration viewpoint.
Combining this data on a data lake will provide the processing power and tools required to run AI and Machine Learning models on this dataset, ensuring that clinicians, researchers and administrators can have access to the insights they require at the time they require them.
BDM Health is a suite of data automation tools that allows healthcare professionals to build data lakes without having to become experts in the underlying technology that makes the data lake work.
BDM Health allows healthcare data to be ingested onto the data lake, in a secure and anonymized manner, but compliant with all data governance regulations and in a manner that all access and activities on the date are recorded and auditable. Data pipelines can be built, operational and in production in hours rather than in weeks or months, ensuring the most up to data is available as and when it is needed.
Transform Your Data Experience in Healthcare
Different levels of access and different views of the data can be made available to different user personas. A Clinician or healthcare professional may be allowed to see data that is available on a patient they are treating, while a Researcher may only be allowed access to de-identified patient data. Federated access to the data can be configured, ensuring the maximum value can be derived from the underlying data in a secure and compliant manner, from the largest possible audience of users.
Different levels of access and different views of data can be now made available.
Unify All Your Data for Different Healthcare Users
Imperial Use Case
In collaboration with our partners Imperial College Healthcare NHS Trust and UKCloud, the NIHR Imperial BRC has set up high performance, cloud-based, informatics solutions that will allow NHS Trust staff to access de-identified data with enhanced tooling, compute power and security (called iCARE).
"Choosing BDM as our core data processing engine has not only increased our data governance and trust capabilities but also reduced data operations costs by 70%."
-Head of Data Engineering, Major European Bank