Achieving large-scale clinician adoption of AI-enabled decision support.
BMJ Health Care Inform
; 31(1)2024 May 30.
Article
en En
| MEDLINE
| ID: mdl-38816209
ABSTRACT
Computerised decision support (CDS) tools enabled by artificial intelligence (AI) seek to enhance accuracy and efficiency of clinician decision-making at the point of care. Statistical models developed using machine learning (ML) underpin most current tools. However, despite thousands of models and hundreds of regulator-approved tools internationally, large-scale uptake into routine clinical practice has proved elusive. While underdeveloped system readiness and investment in AI/ML within Australia and perhaps other countries are impediments, clinician ambivalence towards adopting these tools at scale could be a major inhibitor. We propose a set of principles and several strategic enablers for obtaining broad clinician acceptance of AI/ML-enabled CDS tools.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Sistemas de Apoyo a Decisiones Clínicas
Límite:
Humans
País/Región como asunto:
Oceania
Idioma:
En
Revista:
BMJ Health Care Inform
Año:
2024
Tipo del documento:
Article
País de afiliación:
Australia