The allure of having devices and tasks assisted by artificial intelligence is that they will help overcome some of the natural limits of human cognition with regards to working memory and attention. And in helping with the mundane tasks, AI can buy clinicians back time to spend with the complex patients who really need it. But the way all this pans out will really depend on how seamlessly the machine learning devices fit in with the clinical workflow. Which aspect of clinical decision-making do they support and how are the consequences of error mitigated? Only a small fraction of research projects make it all the way to implementation, and in this podcast we discuss the ergonomic factors that need to be solved to effectively use AI in clinical decision support.
 
Guests
Associate Professor Clair Sullivan MBBS FRACP FACHI FAIDH CHIA (Director, Queensland Digital Health Centre; University of Queensland)
Professor Enrico Coiera MBBS PhD FACMI, FACHI (Director, Centre for Health Informatics, Australian Institute of Health Innovation; Macquarie University).

Production
Produced by Mic Cavazzini DPhil. Music licenced from Epidemic Sound includes ‘Alienated’ by ELFL and ‘Little Liberty’ by Paisely Pink. Image by Da Kuk licenced from Getty Images.

Editorial feedback kindly provided by physicians; Rhiannon Mellor, David Arroyo, Aidan Tan, Joseph Lee, Rachel Murdoch, Michelle Chong, Phillipa Wormald and digital health academics; Paul Cooper and Natasa Lazarevic.

Key References
The Last Mile: Where Artificial Intelligence Meets Reality [Coiera, J Med Internet Res. 2019]
We need to chat about artificial intelligence [Coiera, MJA. 2023]
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices [Coiera, BMJ Health Care Inform. 2021]

Please visit the Pomegranate Health web page for a transcript and supporting references. Login to MyCPD to record listening and reading as a prefilled learning activity. Subscribe to new episode email alerts or search for ‘Pomegranate Health’ in Apple Podcasts, Spotify, Castbox, or any podcasting app.