National Framework Agreement for the provision of Data Validation Services

Published facts

What the notice says

Buyer

Countess of Chester Hospital NHS Foundation Trust

Published status

complete

Latest release reference

fc893a98-fa46-46ba-9953-43f18a2cdb6a-692894

CPV codes

Common Procurement Vocabulary (CPV) codes: 72225000

Published tags

award

Latest record Bidwake loaded from this source

27 Aug 2026

This notice is published for transparency purposes only. Award Notice 2021/S 000-011272 was published on Find a Tender on 20 May 2021 in relation to this procurement. For the avoidance of doubt, no new procurement process has been undertaken. A number of NHS organisations are currently migrating, or are expected to migrate from a legacy Patient Administration System (PAS) to modern Electronic Patient Record (EPR) systems. Many legacy PAS are not Referral to Treatment (RTT) compliant and, therefore, RTT Pathways and associated Events for migration have to be manually manufactured from existing referrals and outcomes. There may also be significant data quality issues with legacy data that will impact on the management and integrity of that data prior to implementation of a new EPR system. NHS organisations may lack in-house expertise and/or capacity to undertake the necessary data cleansing exercises and may require expert assistance in undertaking a data validation exercise prior to the Client's planned migration of its legacy PAS to a modern EPR system. The objective of this framework is to provide NHS Organisations ("the Clients") with expert assistance in undertaking data validation exercises prior to and following a Client's planned migration of its PAS to a modern EPR system. This includes the validation of incomplete pathways, incomplete waiting lists and duplicated pathways as well as understanding the data quality issues that could facilitate the RTT migration to the EPR system and the Client's Covid-19 restoration and recovery work. This will enable the NHS Organisations to: - provide assurance to the Board, CCGs and patients of the accuracy of the patient data held, and particularly how this is managed in relation to supporting RTT and other associated patient access standards, - improve the quality of patient data held within the EPR and support the optimal use of the EPR from implementation. The Supplier will ensure that effective knowledge transfer takes place and will help the Client to develop an in-house central validation and booking team to achieve business as usual booking and reporting post the EPR implementation.

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Observed notice trail

How the published record developed

Events follow the publisher date where one is available. “Seen by Bidwake” is the date this service first found the record.

1. Award notice observed

   27 Oct 2023

   Latest variant observed by Bidwake on 20 Aug 2026.

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   Record references

   Release reference

   fc893a98-fa46-46ba-9953-43f18a2cdb6a-692894

   Published tags

   award

Awards and suppliers

Published award and contract facts

• National Framework Agreement for the provision of Data Validation Services

  Buyer: Countess of Chester Hospital NHS Foundation TrustSupplier: Acumentice Ltd

  End date in notice

  3 May 2025

  Value shown in notice

  £1Whole award value; not assigned to one supplier

  Official source

  Open the official Contracts Finder notice for National Framework Agreement for the provision of Data Validation Services

  About this figure

  • This award names more than one supplier but does not divide the published value between them. The figure is shown for context and is not assigned to one supplier.

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  Source

  Contracts Finder

  Award or lot reference

  ocds-b5fd17-b0258aed-7e00-4d4e-880d-e7797327a6dc-1

• National Framework Agreement for the provision of Data Validation Services

  Buyer: Countess of Chester Hospital NHS Foundation TrustSupplier:

Related evidence

Published terms and linked processes

No recurrence, renewal or options wording appears in these notices.

No exact source-published process relationship was found.