Not applicable. Not applicable.
Conditions
Interventions
Not applicable.
Sponsors
Erasmus MC, Universitair Medisch Centrum Rotterdam
Eligibility
Age
18 Years to 99 Years
Inclusion criteria
Inclusion criteria: Senior digital-health executives (e.g., Managing Director / Senior Management or Chief Information / Digital Officer or equivalent) designated by each hospital.Written informed consent
Exclusion criteria
Exclusion criteria: No further restrictions were made for participation in this study.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| In this mixed-methods cross-sectional study, we will analyze the AI governance of leading hospitals globally. The survey data will be analyzed using SPSS or Python, with descriptive statistics computed to provide an overview of participants’ responses. The survey answers are categorical data and will be reported as counts and percentages. The interview data will undergo qualitative synthesis using thematic analysis, involving coding and theme development, to identify key elements of the AI governance. We will triangulate the qualitative data with the quantitative survey results to ensure a comprehensive understanding of the AI governance. By integrating quantitative and qualitative findings, we aim to identify convergences and divergences, providing insights into the AI governance of leading hospitals in healthcare. | — |
Secondary
| Measure | Time frame |
|---|---|
| Insights on governance domains with low maturity, highlighting areas where additional support or policy development is needed. Condensing all information to provide a practical governance toolkit for dissemination to hospitals worldwide. | — |
Countries
Netherlands
Contacts
Public ContactM.E. Genderen
Erasmus MC, Universitair Medisch Centrum Rotterdam
Outcome results
None listed