ILIA – IT-based relapse monitoring for schizophrenia
The project is funded by the Innovation Fund of the German Federal Government (funding code: 01VSF22033) and registered at the German Clinical Trial Register (Registration number: DRKS00034991). More information here↗ (German).
Due to the high relapse rates among patients with schizophrenia and the associated high costs, care can be significantly improved through relapse-reducing measures. Guidelines consistently emphasize the importance of identifying early warning signs of schizophrenia, which are known to appear several weeks before a relapse.
As part of the ILIA study, it is being evaluated whether app-based monitoring of early warning signs in schizophrenia and their evaluation can lead to behavioral changes in patients and caregivers, ultimately resulting in fewer rehospitalizations and reduced treatment costs.
In this multicenter, randomized controlled study, 106 patients with schizophrenia or schizoaffective disorder are recruited across six participating study centers. Participants in the intervention group enter the ten early warning sign items weekly into an app on their own smartphone during a twelve-month intervention phase. Both patients and caregivers have access to view the progression of the early warning signs at any time through the app/dashboard. If the total score exceeds a certain threshold, an alert is triggered, notifying both the caregiver and the patient. In this case, the caregiver and patient are advised to establish timely contact, such as through a phone call, to assess the patient's current health status.
This process represents a shared responsibility between the patient and caregiver. As part of a shared decision-making process, the next treatment steps should then be jointly decided upon. These may include psychoeducation, improving sleep, issuing a sick note, adjusting antipsychotic medication, or the participatory decision that no further action is needed.
Correspondence: Selina Hiller
Supervisors: Prof. Dr. Stefan Leucht
ILIA Team: Stefan Leucht, Selina Hiller, Mareike Winckel (student assitant), Emilia Herlitzius (student assistant), Melanie Antelmann (student assistant)