Discussion Paper No. 324 of 2024 on Robotic Medical Services and the Future of Healthcare in Kenya

Abstract

With the Kenyan healthcare affected by challenges of availability, accessibility and affordability, there is a pressing need to examine how to adopt robotic medicine as a permanent solution. This study aimed to assess the adoption of robotic medical services (4IR technology) and the future of Kenyan healthcare. The specific objectives were to identify drivers of change in accelerating robotic medicine adoption and provide policy recommendations. The study employed a scenario planning approach methodology, focusing on four steps: defining the scenario question and time horizon, identifying drivers of change, and developing and applying scenarios, guided by diffusion innovation theory. The twelve key drivers of change are societal and expert acceptance of robotic medicine, compatibility with existing infrastructure, robustness of data and internet for AI, investment costs, national healthcare budget, recyclability and environmental impact of medical waste, legislative frameworks, global political collaboration, and AI-related intellectual property, liability, and ethical issues such as patient data privacy, transparency, and bias. The robustness of data and internet for AI and the level of societal acceptance were identified as driving forces. The plausible future scenarios, i.e. Successful Adoption, Low Adoption, Chaotic Change and Rejection of the Adoption were identified. The main opportunities were identified as rapid AI technological developments, medical tourism, and robotic medical innovations. Finally, the critical challenges in the plausible future were found to be regulatory uncertainty, ethical concerns, data privacy and public misconceptions from social acceptance levels. The study recommended the government to invest in AI infrastructure, develop an AI usage framework, create an enabling environment that encourages robotic medicine adoption, establish stringent data usage regulations, foster societal acceptance through targeted community engagement and education initiatives to robotic medicine adoption