Gateshead Health Chooses BridgeHead's VNA for its Image Data Management Strategy

BridgeHead SoftwareGateshead Health NHS Foundation Trust, also known as QE Gateshead, has selected BridgeHead Software (BridgeHead), the Healthcare Data Management company, to implement its Vendor Neutral Archive (VNA) for a multi-staged image management project. QE Gateshead is actively taking strategic decisions across the Trust to create a comprehensive electronic patient record (EPR) and is embarking upon a data strategy to help facilitate the EPR of which the VNA plays a significant part.

Localisation of historic and current PACS data
Initially, the project commences with the requirement for QE Gateshead to meet its obligations as it withdraws from the National PACS programme (part of the National Programme for IT (NPfIT)), by taking control of all the PACS data currently residing in the LSP Central Data Store (CDS). After serving notice on its existing contract that ends in June 2014, QE Gateshead has a limited time to bring its centrally stored image data back under the Trust’s full control. Utilising traditional localisation methods of standard DICOM Query/Retrieve across N3, the Trust was working to an estimated 10-month timeframe to bring all of the data back from the CDS.

However, by working with BridgeHead, the Trust is able to utilise the tape store from its HSM system (put in place as part of the originally specified PACS environment) that contains a copy of all of the Trust’s PACS data archived in the CDS. As a result, taking control of the image studies, by transferring them into the BridgeHead VNA, is estimated at a massively reduced 12 weeks. These timings also include the storing of the latest 12 months of PACS image data, currently stored in the local cache, into the BridgeHead VNA. Finally, the Trust intends to use the BridgeHead VNA as one of the target nodes for new imaging studies created by the go forward PACS.

Ultimately, phase one of the project will result in QE Gateshead using BridgeHead's VNA as its local storage and management repository for all of its historic and current PACS data.

Integrating a new PACS application with the VNA
One of the reasons QE Gateshead selected BridgeHead’s VNA was as a result of its true vendor neutrality - BridgeHead’s VNA has the ability to interface with any PACS applications, regardless of the provider, as well as being able to work with any chosen storage device, irrespective of media or brand. This was very important for QE Gateshead as they plan to replace their PACS application and wanted to avoid vendor lock-in. Consequently, QE Gateshead’s strategy was to ensure that their chosen VNA could be utilised as the target archive for both existing images from the Trust’s current PACS and those created by a new PACS in the future – essentially keeping all of their studies in one place.

The implementation of BridgeHead’s VNA will proceed in advance of any PACS replacement to ensure that all archived studies are consolidated into a local, central store, completely under QE Gateshead’s control. This will pave the way for the implementation of the go forward PACS application, once selected.

The future - a VNA for all imaging disciplines and beyond
In the future, QE Gateshead intends that the scope of the BridgeHead VNA extends to become the Trust’s single, enterprise-wide archive for all clinical imaging. This would result in the VNA environment being open to data from other disciplines outside of radiology PACS, such as (but not limited to) endoscopy, medical photography and scanned documents.

Once the image data management strategy has been fully implemented, QE Gateshead will consider adding administrative data sources into the fold. BridgeHead’s VNA is a subset of its wider Healthcare Data Management (HDM) Solution, which has the capability of storing and protecting all healthcare data, both clinical and administrative. By simply adding BridgeHead Agents to the solution, as required, QE Gateshead will be able to extend the VNA environment to BridgeHead’s full solution, having the ability to archive and manage a greater variety and volume of hospital data. As a result, the system will offer a horizontal view of all data, enabling applications, such as its Medway EPR, to search for all data pertaining to a patient. By keeping clinical and administrative data in one place, and offering this back to the hospital’s EPR system, QE Gateshead will be ever closer to achieving their vision by providing a holistic view of a patient’s entire medical record.

"With the end of our current LSP contract looming, we have been tasked with removing all of our PACS data from the CDS and onto another storage platform to support on-going patient care," said Clare Jones, Radiology IT Systems Manager at Gateshead Health NHS Foundation Trust. "We knew BridgeHead could assist us with our immediate imaging data needs in a cost effective way. However, BridgeHead was also able to help and guide us to take a long-term, strategic view - ensuring we store and manage other healthcare data in the future as we transition to a fully electronic patient record."

"We are delighted to help Gateshead explore strategies to help set the pathway towards the vision of a holistic digital patient record, starting with the short-term tactical requirements to localise their data as they withdraw from the National PACS Programme" said Jim Beagle, President and CEO of BridgeHead Software. "The BridgeHead approach to VNA is standards-based and vendor agnostic - that was extremely important to QE Gateshead to give them total control of their image data environment and avoid vendor lock-in. Beyond the Trust’s immediate challenges of PACS replacement and data migration, the BridgeHead VNA can be extended to the full HDM Solution and thereby act as the key enabler to effectively store and protect both clinical and administrative information across the Trust. We look forward to driving forward on the short term tactical objectives as well as a long-term strategic relationship to help QE Gateshead achieve their data management ambitions."

About BridgeHead Healthcare Data Management (HDM) Solution
BridgeHead’s VNA is part of its Healthcare Data Management (HDM) Solution that enables hospitals to efficiently manage all of their systems and data, within one environment. BridgeHead’s HDM offers a VNA for DICOM images and a compatible archive for non-DICOM files, featuring a rich policy engine used for Information Lifecycle Management (ILM), and controlling features like encryption and compression. BridgeHead’s HDM also offers comprehensive protection of all manner of data found within healthcare environments, from medical images, scanned patient documents, and patient notes, through to email, PDFs and other office type files.

About BridgeHead Software
With 20 years’ experience in data and storage management, and 12 years in healthcare, BridgeHead Software is trusted by over 1,000 hospitals worldwide. Today, BridgeHead Software helps healthcare facilities overcome challenges stemming from rising data volumes and increasing storage costs while delivering peace of mind around how to store, protect and share clinical and administrative information.

BridgeHead’s Healthcare Data Management solutions are designed to work with any hospital’s chosen applications and storage hardware, regardless of vendor, providing greater choice, flexibility and control over the way data is managed, now and in the future.

Most Popular Now

Stepping Hill Hospital Announced as SPAR…

Stepping Hill Hospital, part of Stockport NHS Foundation Trust, has replaced its bedside units with state-of-the art devices running a full range of information, engagement, communications and productivity apps, to...

DMEA 2025: Digital Health Worldwide in B…

8 - 10 April 2025, Berlin, Germany. From the AI Act, to the potential of the European Health Data Space, to the power of patient data in Scandinavia - DMEA 2025...

New System for the Early Detection of Au…

A team from the Human-Tech Institute-Universitat Politècnica de València has developed a new system for the early detection of Autism Spectrum Disorder (ASD) using virtual reality and artificial intelligence. The...

Is AI in Medicine Playing Fair?

As artificial intelligence (AI) rapidly integrates into health care, a new study by researchers at the Icahn School of Medicine at Mount Sinai reveals that all generative AI models may...

Generative AI's Diagnostic Capabili…

The use of generative AI for diagnostics has attracted attention in the medical field and many research papers have been published on this topic. However, because the evaluation criteria were...

Diagnoses and Treatment Recommendations …

A new study led by Prof. Dan Zeltzer, a digital health expert from the Berglas School of Economics at Tel Aviv University, compared the quality of diagnostic and treatment recommendations...

AI Tool can Track Effectiveness of Multi…

A new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS) has been developed by UCL researchers. AI uses...

Surrey and Sussex Healthcare NHS Trust g…

Surrey and Sussex Healthcare NHS Trust has marked an important milestone in connecting busy radiologists across large parts of South East England, following the successful go live of Sectra's enterprise...

DMEA 2025 Ends with Record Attendance an…

8 - 10 April 2025, Berlin, Germany. DMEA 2025 came to a successful close with record attendance and an impressive program. 20,500 participants attended Europe's leading digital health event over the...

Dr Jason Broch Joins the Highland Market…

The Highland Marketing advisory board has welcomed a new member - Dr Jason Broch, a GP and director with a strong track record in the NHS and IT-enabled transformation. Dr Broch...

AI-Driven Smart Devices to Transform Hea…

AI-powered, internet-connected medical devices have the potential to revolutionise healthcare by enabling early disease detection, real-time patient monitoring, and personalised treatments, a new study suggests. They are already saving lives...

Multi-Resistance in Bacteria Predicted b…

An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically...