TY - JOUR
T1 - The price of artificial intelligence
AU - Coiera, Enrico
N1 - Copyright the Publisher 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Introduction: Whilst general artificial intelligence (AI) is yet to appear, today's narrow AI is already good enough to transform much of healthcare over the next two decades. Objective: There is much discussion of the potential benefits of AI in healthcare and this paper reviews the cost that may need to be paid for these benefits, including changes in the way healthcare is practiced, patients are engaged, medical records are created, and work is reimbursed. Results: Whilst AI will be applied to classic pattern recognition tasks like diagnosis or treatment recommendation, it is likely to be as disruptive to clinical work as it is to care delivery. Digital scribe systems that use AI to automatically create electronic health records promise great efficiency for clinicians but may lead to potentially very different types of clinical records and workflows. In disciplines like radiology, AI is likely to see image interpretation become an automated process with diminishing human engagement. Primary care is also being disrupted by AI-enabled services that automate triage, along with services such as telemedical consultations. This altered future may necessarily see an economic change where clinicians are increasingly reimbursed for value, and AI is reimbursed at a much lower cost for volume. Conclusion: AI is likely to be associated with some of the biggest changes we will see in healthcare in our lifetime. To fully engage with this change brings promise of the greatest reward. To not engage is to pay the highest price.
AB - Introduction: Whilst general artificial intelligence (AI) is yet to appear, today's narrow AI is already good enough to transform much of healthcare over the next two decades. Objective: There is much discussion of the potential benefits of AI in healthcare and this paper reviews the cost that may need to be paid for these benefits, including changes in the way healthcare is practiced, patients are engaged, medical records are created, and work is reimbursed. Results: Whilst AI will be applied to classic pattern recognition tasks like diagnosis or treatment recommendation, it is likely to be as disruptive to clinical work as it is to care delivery. Digital scribe systems that use AI to automatically create electronic health records promise great efficiency for clinicians but may lead to potentially very different types of clinical records and workflows. In disciplines like radiology, AI is likely to see image interpretation become an automated process with diminishing human engagement. Primary care is also being disrupted by AI-enabled services that automate triage, along with services such as telemedical consultations. This altered future may necessarily see an economic change where clinicians are increasingly reimbursed for value, and AI is reimbursed at a much lower cost for volume. Conclusion: AI is likely to be associated with some of the biggest changes we will see in healthcare in our lifetime. To fully engage with this change brings promise of the greatest reward. To not engage is to pay the highest price.
UR - http://www.scopus.com/inward/record.url?scp=85068553385&partnerID=8YFLogxK
U2 - 10.1055/s-0039-1677892
DO - 10.1055/s-0039-1677892
M3 - Article
C2 - 31022746
SN - 0943-4747
VL - 28
SP - 14
EP - 15
JO - Yearbook of Medical Informatics
JF - Yearbook of Medical Informatics
IS - 1
ER -