Using predictive analytics to improve mental health services

Catherine Mitchell

30 June 2022


Mersey Care NHS Foundation Trust provides physical health and mental health services in the North West of England. Services are delivered by over 11,000 staff across more than 150 sites. The trust has nearly 1,000 inpatient beds, but over 90% of all contacts are in the community. 

In common with many other mental health trusts, Mersey Care’s community mental health teams (CMHTs) were experiencing rising caseloads and increasing numbers of service users with complex mental health problems. This meant that the service was prioritising the management of risk to keep people safe, and had limited time to deliver recovery-based care. 

The lack of information about the size and complexity of team and practitioner caseloads meant that it was hard for managers to ensure that adequate time and resource was allocated to those service users who needed it most. The trust was keen to make better use of the information held in their clinical systems to address these issues.  

Using Global Digital Exemplar funding, the trust worked in collaboration with Holmusk to develop a digital solution, called the Management and Supervision Tool (MaST). 

The tool uses a ‘risk of crises’ algorithm to identify those people who are most likely to require crisis services such as A&E, community mental health crisis services or inpatient care. It can also be used to identify people who are at the lowest risk of using crisis services, who can be reviewed and potentially discharged from the CMHT, with support from other services for their continued recovery. This has the potential to reduce the size of CMHT caseloads, freeing up time to care for others. 
Using predictive analytics to improve mental health services

June 2022 (PDF 1121KB)

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