---
title: "1808 Risk Stratification Algorithms Tool for NHS AGEM CSU"
ocid: "ocds-h6vhtk-0458e8"
canonical_url: "https://d3tenders.com/contract/?ocid=ocds-h6vhtk-0458e8"
markdown_url: "https://d3tenders.com/contract/ocds-h6vhtk-0458e8.md"
json_url: "https://d3tenders.com/contract/ocds-h6vhtk-0458e8.json"
source: "Find A Tender Service"
current_stage: "Award"
buyer: "NHS ARDEN AND GEM CSU"
published: "2024-11-26"
---

# 1808 Risk Stratification Algorithms Tool for NHS AGEM CSU

Buyer: NHS ARDEN AND GEM CSU  
Current stage: Award  
OCID: ocds-h6vhtk-0458e8

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## Summary

The procurement contracting process initiated by NHS Arden and GEM CSU sought competitive offers for the supply, installation, support, and maintenance of Risk Stratification Algorithms within a Tool to manage a population of 3.3 million patients. This award, dated 26th November 2024, follows a competitive procedure with negotiation under Regulation 32(2)(a) and is categorised under IT software development services. The award has been made to Johns Hopkins HealthCare LLC. The procurement stage is in the Award phase with the contract dated 15th November 2024, with the process now completed. The work is to be conducted in Leicester (region UKF2) and includes a focus on health services.

This tender offers substantial growth opportunities for businesses specialising in IT software development and healthcare data management. The key requirements for the tool, which include rigorous testing, adherence to clinical evidence, and integration with NHS data flows, are well-suited to companies with a proven track record in these domains. Furthermore, the contract's value of £188,400 presents significant business potential for firms able to provide continuous support and updates to reflect changes in clinical practices and patient behaviour. Companies experienced in operating within NHS structures and data environments can leverage this contract to expand their portfolio and technical capabilities.

## Notice

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 stratification
Use multiple years of data to support a longitudinal record which can be updated on an automated basis by AGCSU.

### Lot Information

Lot 1

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 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.

## Key Details

| Field | Value |
| --- | --- |
| Publication source | Find A Tender Service |
| Latest notice | https://www.find-tender.service.gov.uk/Notice/038164-2024 |
| Notice type | Tender Notice |
| Procurement type | Standard |
| Procurement category | Services |
| Procurement method | Selective |
| Procurement method details | Competitive procedure with negotiation |
| Tender suitability | Not specified |
| Awardee scale | Large |
| All stages | Tender, Award |

## Dates

| Field | Value |
| --- | --- |
| Publication date | 26 Nov 2024 |
| Submission deadline | 11 Jun 2024 |
| Future notice date | Not specified |
| Award date | 15 Nov 2024 |
| Contract period | 30 Jun 2024 - 30 Jun 2025 |
| Recurrence | Not specified |

## Values

| Field | Value |
| --- | --- |
| Tender value | £190,000 |
| Lots value | £190,000 |
| Awards value | Not specified |
| Contracts value | £188,400 |

## Status

| Field | Value |
| --- | --- |
| Tender status | Complete |
| Lots status | Cancelled |
| Awards status | Active, Unsuccessful |
| Contracts status | Active |

## Buyer

| Field | Value |
| --- | --- |
| Main buyer | NHS ARDEN AND GEM CSU |
| Locality | LEICESTER |
| Post town | Leicester |
| Postcode | LE1 6NB |
| Country | England |
| ITL 1 | TLF East Midlands (England) |
| ITL 2 | TLF2 Leicestershire, Rutland and Northamptonshire |
| ITL 3 | TLF21 Leicester |
| Local authority | Leicester |
| Electoral ward | Castle |
| Westminster constituency | Leicester South |
| Delivery location | TLF1 Derbyshire and Nottinghamshire |

## Supplier

| Field | Value |
| --- | --- |
| Number of suppliers | 1 |
| Supplier names | JOHNS HOPKINS HEALTHCARE |

## CPV Codes

### Divisions

- 72 - IT services: consulting, software development, Internet and support

### Codes

- 72212517 - IT software development services

## Release History

- 26 Nov 2024 at 13:55 - Award - Award Notice - https://www.find-tender.service.gov.uk/Notice/038164-2024
- 21 Nov 2024 at 10:10 - Award - Award Notice - https://www.find-tender.service.gov.uk/Notice/037619-2024
- 10 May 2024 at 15:34 - Tender - Tender Notice - https://www.find-tender.service.gov.uk/Notice/015058-2024

## Notice URLs

- https://health-family.force.com/s/Welcome
- https://www.ardengemcsu.nhs.uk/
- https://www.judiciary.uk/courts-and-tribunals/high-court/

## Provenance

This Markdown file is an alternate public rendering of the D3 Tenders contract record. The canonical page is https://d3tenders.com/contract/?ocid=ocds-h6vhtk-0458e8. The underlying structured data is available as OCDS JSON at https://d3tenders.com/contract/ocds-h6vhtk-0458e8.json.