The demand for clinical information and for involvement in medical treatment decision making: An empirical examination in the general population

2008 ◽  
Vol 37 (5) ◽  
pp. 1746-1755
Author(s):  
Amir Shmueli

2018 ◽  
Vol 45 (3) ◽  
pp. 156-160 ◽  
Author(s):  
Rosalind J McDougall

Artificial intelligence (AI) is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system creates both important risks and significant opportunities for promoting shared decision making. If value judgements are fixed and covert in AI systems, then we risk a shift back to more paternalistic medical care. However, if designed and used in an ethically informed way, AI could offer a potentially powerful way of supporting shared decision making. It could be used to incorporate explicit value reflection, promoting patient autonomy. In the context of medical treatment, we need value-flexible AI that can both respond to the values and treatment goals of individual patients and support clinicians to engage in shared decision making.







2017 ◽  
Vol 13 (2) ◽  
pp. 169-184 ◽  
Author(s):  
Shuya Kushida ◽  
Takeshi Hiramoto ◽  
Yuriko Yamakawa

In spite of increasing advocacy for patients’ participation in psychiatric decision-making, there has been little research on how patients actually participate in decision-making in psychiatric consultations. This study explores how patients take the initiative in decision-making over treatment in outpatient psychiatric consultations in Japan. Using the methodology of conversation analysis, we analyze 85 video-recorded ongoing consultations and find that patients select between two practices for taking the initiative in decision-making: making explicit requests for a treatment and displaying interest in a treatment without explicitly requesting it. A close inspection of transcribed interaction reveals that patients make explicit requests under the circumstances where they believe the candidate treatment is appropriate for their condition, whereas they merely display interest in a treatment when they are not certain about its appropriateness. By fitting practices to take the initiative in decision-making with the way they describe their current condition, patients are optimally managing their desire for particular treatments and the validity of their initiative actions. In conclusion, we argue that the orderly use of the two practices is one important resource for patients’ participation in treatment decision-making.



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