JMIR Publications

ABSTRACT

Background:

How to prepare the current and future health workforce for with the possibilities of using artificial intelligence (AI) in healthcare is a growing concern, as AI applications emerge in various care settings and specialisations. At present, there is no obvious consensus among educators about what needs to be learned, or how this learning may be supported or assessed.

Objective:

Our study aimed to explore healthcare educational experts’ ideas and plans for preparing the health workforce to work with AI, and identify critical gaps in curriculum and educational resources, across a national healthcare system.

Methods:

A survey canvassed expert views on AI education for the health workforce, in terms of educational strategies, subject matter priorities, meaningful learning activities, desired attitudes and skills. 39 senior people from different health workforce subgroups across Australia provided ratings and free-text responses, in late 2020.

Results:

Responses highlighted the importance of education about ethical implications, suitability of large datasets for use in AI clinical applications, principles of machine learning, specific diagnosis and treatment applications of AI, as well as alterations to cognitive load during clinical work and the interaction between human and machine in clinical settings. Respondents also outlined barriers to implementation, such as lack of governance structures and processes, resource constraints and cultural adjustment.

Conclusions:

Further work, around the world, of the kind reported in this survey can assist educators and education authorities who are responsible for preparing the health workforce to minimise the risks and realise benefits from implementing AI in healthcare.