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We aim to personalise treatment for depression using a living algorithm, which will incorporate multi-modal data (from demographic characteristics to imaging and genetics), individual preferences and real-time outcomes from patients. Embedded in a continuously learning environment, this clinical decision-support tool will produce more precise recommendations that will be more generalisable to people seen in routine care settings.

Part of our Mental health across the life course research theme

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Aims

To investigate:

    • Understand which methods better capture individual preferences and their implementation into clinical shared decision-making processes

    • Move from a “static” to a “dynamic” and “living” model, with outcome data continuously improving the clinical shared decision-support model

    • Expanding the existing care model for depression to effectively integrate findings from imaging and genetic data

    • Facilitate communication of findings in shared decision-support process

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    Deliverables

    • We will continue the ongoing discussion with experts in health decision making and behavioural science, local PPIEP group and representative from local GP surgeries to ensure the use of state-of-the-art models for patient preferences

    • We will transparently publish our findings in high impact scientific journals

    • We will explore the implementation of our clinical shared decision-support model locally with the Oxford Health NHS Foundation Trust

    • By engaging NIHR infrastructures like the NIHR Applied Research Collaboration Oxford and Thames Valley (ARC OxTV), we will explore how to successfully expand the implementation of our clinical shared decision-support model regionally, and then nationally

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    Expected Impact

    We expect our work to have an impact on individual patients with depression with the introduction of precision mental health in the standard healthcare pathway. We expect our clinical shared decision-support model to be implemented into the primary care services under the NHS, starting locally at the Oxford Health NHS Foundation Trust.

    Taken together, these will result in a reduction of direct costs by preventing prescription of only partially beneficial drugs compared to available alternatives, as well as indirect costs by affecting the economic consequences of work lost due to illness.

    Related research themes