Artificial intelligence and the doctor–patient relationship expanding the paradigm of shared decision making
Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI-based CDSS has an impact on the doctor–patient relationship, shaping their decisions...
| Published in: | Bioethics |
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| Authors: | ; ; ; |
| Format: | Electronic Article |
| Language: | English |
| Check availability: | HBZ Gateway |
| Journals Online & Print: | Drawer...
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Published: |
Wiley-Blackwell
2023
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| In: |
Bioethics
Year: 2023, Volume: 37, Issue: 5, Pages: 424-429 |
| IxTheo Classification: | NBE Anthropology NCH Medical ethics NCJ Ethics of science |
| Further subjects: | B
Artificial Intelligence
B shared decision-making B Healthcare B doctor–patient relationship B Autonomy |
| Online Access: |
Volltext (kostenfrei) Volltext (kostenfrei) |
| Summary: | Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI-based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI-based CDSS for shared decision-making to better comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. |
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| ISSN: | 1467-8519 |
| Contains: | Enthalten in: Bioethics
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| Persistent identifiers: | DOI: 10.1111/bioe.13158 |