Skip to content

Identifying High-Priority Concerns and Benefits among the stakeholders for an AI-based screening tool to detect rare diseases using Electronic Health Record Data: A qualitative study

Identifying High-Priority Concerns and Benefits among the stakeholders for an AI-based screening tool to detect rare diseases using Electronic Health Record Data: A qualitative study

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00037417
Enrollment
64
Registered
2025-09-22
Start date
2025-09-05
Completion date
Unknown
Last updated
2025-10-06

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

Conditions

Qualitative analysis of group discussion transcripts of patients and the public’s concerns and benefits regarding an AI-based screening tool for detecting rare diseases using electronic health data

Interventions

Group 1: This study examines how people in Germany view the use of AI for the early detection of rare diseases. The aim is to find out what opportunities are seen, what concerns exist, and under what

Sponsors

Klinik für Neurologie, Universitätsmedizin Göttingen
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 85 Years

Inclusion criteria

Inclusion criteria: •Capable of giving written consent •Being able to read and speak German proficiently

Exclusion criteria

Exclusion criteria: •Severe mental or psychiatric disorders •Participants unable to give consent

Design outcomes

Primary

MeasureTime frame
After evaluating the transcripts from group discussions (focus group discussions (FGD)) using qualitative content analysis, a comprehensive list of concerns raised by patients and the public, as well as the expected benefits of using an AI-supported electronic health data system for the detection of rare diseases, will be compiled.

Secondary

MeasureTime frame
Under what circumstances would the German public accept an AI-based screening tool for electronic health records?

Countries

Germany

Contacts

Public ContactElisabeth Felicite Nyoungui

Universitätsmedizin Göttingen, Institut für Medizinische Informatik

elisabeth.nyoungui@med.uni-goettingen.de+49 551 3961543

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026