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Effects of an AI-based software on clinical workflow and clinician outcomes – an example of Quantib software for the detection of abnormalities on MRI prostate scans

Effects of an AI-based software on clinical workflow and clinician outcomes – an example of Quantib software for the detection of abnormalities on MRI prostate scans

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00027391
Enrollment
9
Registered
2022-01-11
Start date
2021-12-20
Completion date
Unknown
Last updated
2025-04-07

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

Conditions

Reading of prostate MRI scans with suspected prostate cancer

Interventions

Group 1: This is an exploratory, non-interventional study using a mixed methods design with aspects of an interrupted time series analysis with a study group. Study data will be generated from semi-st

Sponsors

Institut für Patientensicherheit, Universitätsklinikum Bonn
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: The study is conducted in the Department of Diagnostic and Interventional Radiology at the University Hospital Bonn. The participants of this study are the radiologists and radiology assistants who use the software (estimated N = 9). Since we are limited to those working in this clinic and with the software for prostate MRI scans, no preliminary sample size calculation was performed (i.e. convenience sampling). When possible, it is planned to conduct semi-structured interviews with clinicians in other departments (esp. Department and Polyclinic of Urology and Pediatric Urology) who are involved in the clinical process surrounding prostate diagnosis. For the interrupted time series design, multiple measurement time points are needed for the observational data. In order to have a sufficient number of cases (in this case, diagnostic reporting scans to prostate MRIs) that can be compared before and after implementation, and that is realistically achievable with the number of patients coming into the radiology department for prostate MRI, we are aiming for N = 45 cases for each study phase.

Exclusion criteria

Exclusion criteria: radiologists and radiology assistants who do not examine prostate MRI scans

Design outcomes

Primary

MeasureTime frame
The study will generate the following study data: Participant observations of a total of N = 90 prostate examinations by scientific staff members of the IfPS. The workflow will not be influenced as far as possible. No additional staff is necessary. After each observation point a short questionnaire will be given to the staff, duration approx. 5 minutes. Participant observation with the method of thinking aloud in a maximum of 20% of the observations.

Secondary

MeasureTime frame
In total, a maximum of up to 18 semi-structured interviews are planned with the staff members performing prostate assessment; duration: approx. 20 minutes before introduction and 45 minutes after introduction of the AI (total max.: 9:45 hours). The number of interviews may be reduced during the course of data collection if sufficient data saturation is achieved ahead of time. If necessary, semi-structured interviews with additional persons involved in prostate diagnostics at the University Hospital Bonn (UKB) should be conducted e.g. second diagnosis, urology.

Countries

Germany

Contacts

Public ContactMatthias Weigl

Institut für Patientensicherheit, Universitätsklinikum Bonn

matthias.weigl@ukbonn.de+49 228 28710390

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 7, 2026