信息详情

1771 Provision of Risk Stratification Algorithms Tool For NHS Arden and GEM CSU

2024-05-14

中文

英语 (English)

所属地区: --

所属机构: --

Published date: 10 May 2024

Open opportunity - This means that the contract is currently active, and the buying department is looking for potential suppliers to fulfil the contract.

Closing: 11 June 2024, 5pm

Contract summary

Industry

  • IT software package - 48517000

  • Location of contract

    DE1 3QT

    Value of contract

    £0 to £190,000

    Procurement reference

    CF-2362600D0O000000rwimUAA

    Published date

    10 May 2024

    Closing date

    11 June 2024

    Closing time

    5pm

    Contract start date

    1 July 2024

    Contract end date

    30 June 2025

    Contract type

    Service contract

    Procedure type

    Open procedure (above threshold)

    Any interested supplier may submit a tender in response to an opportunity notice.

    This procedure can be used for procurements above the relevant contract value threshold.

    Contract is suitable for SMEs?

    Yes

    Contract is suitable for VCSEs?

    No


    Description

    NHS Arden & GEM CSU seeks competitive offers for the supply, installation, support, and maintenance of Risk Stratification Algorithms within a Tool able to cover a population of 3.3 million patients.

    The Risk Stratification Algorithms/Tool must meet the following key requirements:
    Have a proven evidence base and be rigorously tested using standardised statistical metrics and support repeatable results from the same data set.
    Be continually updated and supported to reflect changes in clinical practice and patient behaviour.
    The tool should have had experience of operating in the NHS and with associated NHS data flows or equivalent.
    Must be predicated on clinical evidence including a combination of prescription, diagnosis, and event data rather than purely historical financial spend in secondary care.
    Be able to utilise, as a minimum, acute, and primary care data records as a basis for its stratification
    Use multiple years of data to support a longitudinal record which can be updated on an automated basis by AGCSU.
    The Risk Stratification Tool must have a range of predictive models with ability to include as a minimum:
    Current and predicted costs.
    Predicted resource utilisation.
    Risk of hospitalisation.
    The algorithms within the tool must be able to factor in sufficient historical data to enable the clinical evidence-base of the tool, including historical diagnosis of long-term conditions and support and provide disease profiling. It should capture the multidimensional nature of an individual's health.
    The Risk Stratification algorithms must be able to be housed and run within the AGCSU data management environment to maintain our data controls and governance and allow it to be augmented by other data elements managed by the customer. All outputs of the tool must be programmatically readable, must output validation to measure success of the processing and use a server-based technology not a desktop to enable flexible and secure working.

    To register your interest, please follow the link below, and search for the project reference as detailed: https://health-family.force.com/s/Welcome
    Project Reference: C283610
    Project Name: 1771 Provision of Risk Stratification Algorithms Tool For NHS Arden and GEM CSU


    More information

    Additional text

    To register your interest, please follow the link below, and search for the project reference as detailed: https://health-family.force.com/s/Welcome
    Project Reference: C283610
    Project Name: 1771 Provision of Risk Stratification Algorithms Tool For NHS Arden and GEM CSU

    Should Tenderers have any queries, or having problems using the portal, they should contact Helpdesk at:

    Phone: 0800 9956035

    E-mail: support-health@atamis.co.uk


    How to apply

    Follow the instructions given in the description or the more information section.


    About the buyer

    Contact name

    Mark Didcock AGEM

    Address

    Cardinal Square 10 Nottingham Road
    Derby
    DE1 3QT
    England

    Email

    mark.didcock@nhs.net


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