Implementing behavior change in healthcare epidemiology and antimicrobial stewardship: The worst that can happen is you fail

With the rapid advancement of artificial intelligence (AI), the field of infectious diseases (ID) faces both innovation and disruption. AI and its subfields including machine learning, deep learning and large language models can support ID clinician’s decision making and streamline their workflow. AI models may help ensure earlier detection of disease, more personalized empiric treatment recommendations, and allocation of human resources to support higher yield antimicrobial stewardship and infection prevention strategies. AI is unlikely to replace the role of ID experts, but instead augment it. However its limitations will need to be carefully addressed and mitigated to ensure safe and effective implementation. ID experts can be engaged in AI implementation by participating in training and education, identifying use cases for AI to help improve care for their patients, designing, validating and evaluating algorithms, and continuing to advocate for their vital role in patient care.

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Implementing behavior change in healthcare epidemiology and antimicrobial stewardship: The worst that can happen is you fail

Cited by 2 publications

References 31 publications

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