PM.20.057 – Building a patient sensitive framework in psychiatry

Route: Personalised medicine: the individual at the centre

Cluster question: 105 How can Big Data and technological innovation (e-health) contribute to health care?

In the past decade, far too little progress has been made in psychiatry. Diagnostics have been dominated by a classification system (the DSM) while patients themselves ask for a personal problem analysis. Treatment guidelines are based on RCTs that do not do justice to the complex, dynamic nature of practice and patient variability, and as a result evidence-based interventions are often ineffective if applied on a large scale. Finally, care chains are fragmented, not attuned and not patient-centered. The present proposal aims to achieve a revolutionary change in Dutch psychiatry. By linking three existing consortia [Psychiatry & Development (P&D), Compute Visits Data (CoViDa), Prospective Psychiatric and Economic Research ((PROSPER)], this can be realized at all three levels (diagnostics, treatment, process). The three consortia will use applied big data statistics with complex existing and newly obtained data sources from daily practice. At the level of diagnostics, we will generate patient (risk) profiles that do justice to the individual context of patients without stigmatizing them. At the level of treatment, dynamic block chain guidelines and decision support systems will be built that take into account individual needs and patient-relevant outcome measures. At the level of processes, we will investigate how bottlenecks can be addressed and how health care-chains can be transformed into care-networks. With Statistics Netherlands (CBS) and the Association of Dutch Municipalities (VNG), standard profiles of the population will be made to offset our findings. The consortia each have their specific expertise but will synergistically reinforce each other by using and learning from each other’s methods and insights. In this way, a unique multidisciplinary research field will emerge that will apply big data statistics iteratively and in co-creation with patients, caregivers and professionals. By implementing results directly in practice we will realize the change that is urgently needed in psychiatry.

Keywords

Data Science, diagnostic profiling, learning- and care- networks, Psychiatry, treatment profiling

Other organisations

Eindhoven University of Technology (TU/e), Leiden Universitair Medisch Centrum (LUMC), Radboud Universiteit Nijmegen (RU), Trimbos, Utrecht University (UU)

Submitter

Organisation UMC Utrecht (UMCU)
Name Prof. dr. F. (Floortje) Scheepers
E-mail F.E.Scheepers-2@umcutrecht.nl
Website https://www.umcutrecht.nl/en/research/researchers/scheepers-floortje-fe