At HIMSS23 European Health Conference and Exhibition (7-9 June), expert speakers will share innovative examples of population health interventions harnessing the power of artificial intelligence (AI). 

A highlight of the session will be insights from an AI project which has analysed electronic health record (EHR) data from Turkish citizens between 2015 and the present day to identify unnecessary c-sections. It has shown promising results in reducing the number c-sections performed unnecessarily, helping to promote safe deliveries for mothers and babies.

The project made use of the Robson classification system, a global standard for assessing, monitoring and comparing c-section rates both within healthcare facilities and between them. 

WHY IT MATTERS 

Applying machine learning to health data has the potential to reduce health inequalities, identify populations at risk and enable preventative interventions to reduce adverse events, ill health and disease.

Moderating the session on ‘Improving the Population’s Health Through AI’ on 8 June is Ifan Evans, executive director of digital strategy at Digital Health and Care Wales. Joining him is Yasemin Sahin, CEO and co-founder of business intelligence software firm Turboard, Jukka Lähesmaa, senior advisor at the Ministry of Social Affairs and Health in Finland, and Dr Stefan Buttigieg, resident public health specialist at the department of public health at the Ministry of Health in Malta. 

THE LARGER CONTEXT

There has been explosion in the use of AI to tackle a variety of healthcare challenges in Europe and across the globe – especially with the advent of tools such as ChatGPT, which impact patient engagement and communication. 

Last month the World Health Organization (WHO) said it is important for "caution to be exercised" in the use of AI in clinical and other healthcare settings to "protect and promote human well-being, human safety and autonomy". In a statement, WHO called for "clear evidence of benefit be measured" before widespread and routine use of large language models (LLMs) and other AI models in healthcare delivery.

ON THE RECORD 

Speaking to HIMSS TV, Yasemin Sahin, said: “Business intelligence and data analytics are really important for the healthcare sector to solve different data-related problems. Doing simple dashboarding or reporting no longer makes sense. We need to go further and do some more complicated analytics. We need to find out the reasons behind deaths and behind uncontrolled c-sections etc.”