Hybrid AI system for delirium prediction to relieve nursing practice - participative explorative developement

Hybrid AI system for delirium prediction to relieve nursing practice - participative explorative developement - KIDELIR explore

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00033502

Enrollment

150

Registered

2025-09-19

Start date

2022-12-01

Completion date

Unknown

Last updated

2026-08-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

F05

Interventions

Group 1: The focus in this part of the project is on the exploration of information required for the development of the AI system and its implementation. Explorative, qualitative methods will be used

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: ? Nursing staff and doctors in direct patient care. ? Employees on one of the project wards

Exclusion criteria

Exclusion criteria: ? Persons under the age of 18 ? Trainees

Design outcomes

Primary

Measure	Time frame
The explorative, iterative qualitative data collection is intended to shed light on the importance potential users attach to an AI system for delirium prediction and which expectations and needs are relevant to them. In addition, the focus will be on processes and routines in everyday care that are potentially important for the development and use of an AI system. The following questions will be addressed as target variables: ? What relevance do users see in the prediction of delirium by an AI system? ? What expectations must an AI system for delirium prediction fulfil from the user's perspective? ? What are the potential ethical concerns and risks from the user's perspective?	—

Measure

Time frame

The explorative, iterative qualitative data collection is intended to shed light on the importance potential users attach to an AI system for delirium prediction and which expectations and needs are relevant to them. In addition, the focus will be on processes and routines in everyday care that are potentially important for the development and use of an AI system. The following questions will be addressed as target variables: ? What relevance do users see in the prediction of delirium by an AI system? ? What expectations must an AI system for delirium prediction fulfil from the user's perspective? ? What are the potential ethical concerns and risks from the user's perspective?

—

Countries

Germany

Contacts

Public ContactSven Ziegler

Universitätsklinikum Freiburg

sven.ziegler@uniklinik-freiburg.de+49 761 270 19023

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Aug 10, 2026