Getting the right care from the very start - digital psychiatry advances in risk prediction and clinical decision making at first presentation of psychosis

Date: Monday 17 June
Time: 2.00pm - 3.15pm
Stream: Quality improvement

Overview

Ms Aida Seyedsalehi will introduce the audience to technical terms such as discrimination, calibration and net benefit. She will talk in general about risk prediction in psychiatry in comparison to other branches of medicine, and describe her own work developing a model in 2000 patients (with external validation on 1500) to predict, at the time of the first presentation, which patients are at highest risk of additional future psychotic episodes

Dr Emanuele Osimo will talk in general about electronic health record research and give examples from his own work:  developing risk prediction tools MOZART and PsyMetRiC, for prediction, at psychosis onset, of later adverse psychiatric outcomes (treatment resistance) and adverse cardio-metabolic outcomes using routinely collected predictors, including demographics and biomarkers. He will describe work towards implementing these tools into clinical practice, including further model updating and external validation in multiple countries. He will conclude with an outlook on attempts to combine routine electronic health record data with ‘omics biomarkers for personalised treatment.

Professor Graham Murray will describe the large scale initiative of the U.K. Mental Health Mission MHM, funded at >£40million  by the Office of Life Sciences and NIHR, to improve clincial research infrastructure in the U.K.. She will talk about digital psychiatry initiatives in the MHM, including EPICare, a project working towards a national registry and clinical decision making support tool in early psychosis and how this is integrated with the Careloop app for patient reported measures. Upthegrove will describe the PPIE work that has shaped the project , and report on integration of digital phenotyping with ‘omic biomarker measures for stratification in research and clinical practice.

This session aims to:

  • To gain an overview into two of the main tools of digital psychiatry - mining information in electronic health records for quality improvement and the use of mobile phone based patient report outcome measures (PROMS).
  • To gain insight into how to assess a predictive model and know whether it is 'good enough' for clinical practice. To  understand the relevance of terms such as discrimination, calibration and net benefit. 
  • To understand current strengths and weakness of electronic health records based predictive models that attempt, at the time of a first presentation of psychosis, to predict future relapse, treatment resistance and adverse cardiometabolic outcomes. 
  • To become familiar with the latest national large-scale initiatives in digital psychiatry in early psychosis - the EPICare digital registry and clinical decision making support tool and the Mental Health Mission early psychosis biomarker and digital phenotyping project.

Speakers

Chair: Dr Christelle Langley, University of Cambridge, Cambridge

Ms Aida Seyedsalehi, University of Oxford, Oxford

Dr Emanuele Osimo,  University of Cambridge, Cambridgeshire and Peterborough NHS Trust, Cambridge

Professor Graham Murray, University of Cambridge, Cambridgeshire and Peterborough NHS Trust, Cambridge
Register for Congress 2024

Please email congress@rcpsych.ac.uk or call 020 8618 4120 with any enquiries.