Thomas Jun, Gyuchan, Gangadharan, Satheesh, Cosma, Georgina, Balatsoukas, Panos, Landa-Avila, Cecilia, Zaccardi, Francesco, O’Reilly, Michelle, Akbari, Ashley, Curcin, Vasa, Shankar, Rohit, Kiani, Reza, Sinclair, Neil and Knifton, Chris (2022) A Systemic Design Framework for AI-enabled Healthcare: Improving health and wellbeing of people with learning disabilities. In: Proceedings of Relating Systems Thinking and Design, RSD11, 3-16 Oct 2022, Brighton, United Kingdom.

Preview

Text Jun_SystemicDesign_Paper_2022.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (137kB) | Preview

Abstract

The aim of this presentation is to present a systemic design framework developed by a research team for a project funded by the UK National Institute for Health Research (NIHR), DECODE – Data-driven machine-learning aided stratification and management of multiple long-term conditions in adults with learning disabilities. DECODE will analyse healthcare data on people with learning disabilities from England and Wales to find out what multiple long-term conditions (MLTCs) are more likely to occur together and what happens to some of these MLTCs over time. The end goal of DECODE is to utilise the AI-enabled new knowledge and develop actionable insights for effective joined-up social and health care for people with learning disabilities. The framework we are proposing consists of four steps: i) context analysis to understand the context of AI application; ii) AI output visualisation to develop user-friendly visualisations to display the outputs of AI analysis in a meaningful and accessible way; iii) actionable insight exploration to explore leverage points to improve join-up care coordination; iv) change process planning to evaluate the feasibility and ethical/legal risk of the usage scenarios. This framework will be of interest to many systemic designers who aim to develop a safe, ethical and cost-effective AI in healthcare.

Item Type:	Conference/Workshop Item (Paper)
Uncontrolled Keywords:	artificial intelligence, health and social care, people with learning disabilities, systemic design
Divisions:	Faculty of Design
Date Deposited:	04 Apr 2024 14:40
Last Modified:	04 Apr 2024 14:40
URI:	https://openresearch.ocadu.ca/id/eprint/4262

Actions (login required)

Edit View