The MAPPED study

Developing and internally validating a prognostic model (P Risk) to improve the prediction of psychosis in a primary care population using electronic health records

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This study investigates how routinely collected clinical data can be used to improve the early identification of individuals at increased risk of developing psychosis.

The researchers evaluated prediction approaches designed to support healthcare professionals in recognising people who may benefit from specialist assessment and early intervention. The findings highlight the potential of digital risk prediction models to enhance clinical decision-making, reduce delays in diagnosis and strengthen preventive mental healthcare by making better use of existing healthcare information.

By advancing evidence-based approaches for early detection, this research contributes to the ongoing development of scalable digital tools that support timely intervention and more personalised care for people at risk of severe mental disorders.

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