Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-15T15:21:59.338Z Has data issue: false hasContentIssue false

EPA-1399 – A Journey Through Shared Decision Making in Schizophrenia

Published online by Cambridge University Press:  15 April 2020

J. Munro
Affiliation:
Head Office, Optimal Medicine Ltd, Montpellier, France
C. Young
Affiliation:
Head Office, Optimal Medicine Ltd, London, United Kingdom

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Digital health technologies may improve the management of individuals with mental health disorders by targeting important barriers to effective care. For patients with schizophrenia, for example, addressing:

  • The challenge of dealing with individual variation in treatment response. No specific tools are available to facilitate the delivery of truly patient-centric care. Predictors of an individual's side effects or treatment efficacy are not available, patients’ views on care are often not recorded, clinical state between appointments cannot be easily assessed, precise symptoms and side effects experiences are not captured in a reliable way and physical health is often neglected.

  • The challenge of effectively accessing and utilizing the vast amounts of evidence-based information to direct patient management at the point-of-care. Valuable evidence-based information, including guidelines and systematic reviews, is not used to guide care because there is too much information to assimilate, it is inaccessible at the point-of-care and it is difficult to personalize to any individual patient.

Optimal Medicine will present findings related to use of a web-based clinical decision support software system which enables clinicians to deliver individualised, evidence-based treatment at the point of care including:

  • Delivery of context-specific personalized decision support through a workflow driven interface

  • Interactive visualisation and monitoring of longitudinal status

  • Side effect risk profiling based on an individual's unique and evolving characteristics

  • Symptom and side effect rapid evaluation and monitoring using a hierarchical data selection

  • Integrated remote-monitoring technologies (iTunes app) for use between clinical contacts at times of particular vulnerability, such as discharge from hospital.

Type
S523 - TeleMental Health - 24/7 expertise!
Copyright
Copyright © European Psychiatric Association 2014
Submit a response

Comments

No Comments have been published for this article.