Ethical Implications of AI in Healthcare Resource Allocation
Author Information
Author(s): Elgin Cansu Yüksel, Elgin Ceyhun
Primary Institution: Istanbul University-Cerrahpasa
Hypothesis
What are healthcare professionals' perspectives on the ethical implications of using AI-driven clinical decision support systems for resource allocation?
Conclusion
The integration of AI-CDSS into healthcare resource allocation presents both opportunities and significant ethical challenges.
Supporting Evidence
- Participants expressed concerns about AI-CDSS exacerbating healthcare disparities.
- The need for transparency and explicability in AI-CDSS was emphasized by participants.
- Healthcare professionals reported developing informal practices to maintain their professional autonomy while utilizing AI recommendations.
- Concerns about patient privacy and consent were raised regarding data usage in AI-CDSS.
Takeaway
This study talks to healthcare workers about how using AI in healthcare can help or hurt fairness in getting care.
Methodology
Semi-structured qualitative interviews with 23 healthcare professionals in Turkey, analyzed using thematic analysis.
Potential Biases
Potential biases in AI algorithms could exacerbate existing healthcare disparities.
Limitations
The study may not capture all perspectives on AI-CDSS as it focused on a specific group of healthcare professionals.
Participant Demographics
Participants included 10 physicians, 6 nurses, 4 healthcare administrators, and 3 medical ethicists, with an average age of 42 years.
Digital Object Identifier (DOI)
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