1808 Risk Stratification Algorithms Tool for NHS AGEM CSU

Concepts

• it software
• leicester
• associated nhs data
• risk stratification algorithms
• agcsu.the risk stratification tool
• risk stratification tool
• nhs agem csu
• nhs arden
• 1808 risk stratification algorithms tool
• gem csu

Location

Derbyshire and Nottinghamshire: NHS Arden & Greater East Midlands Commissioning Support Unit

Description

NHS Arden & GEM CSU sought 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 stratificationUse multiple years of data to support a longitudinal record which can be updated on an automated basis by AGCSU.

Total Quantity or Scope

NHS Arden & GEM CSU sought 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 stratificationUse 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.

Award Detail

Award Criteria

CPV Codes

• 72212517 - IT software development services

Other Information

** PREVIEW NOTICE, please check Find a Tender for full details. ** This service has been awarded using Regulation 32(2)(a) of the negotiated procedure without prior publication, in line with the PCR15 Regulations; following a non-award of contract ref: (2024/S 000-015058).The successful provider did not meet the advertised Social Value requirement of the initial process advertised and following clarification and assurance from the provider of their ability, has been awarded the contract under Regulation 32.