“Trying to Find People to Fit the Tech…”: A Qualitative Exploration of the Lessons Learnt Introducing Artificial Intelligence-Based Technology into English Social Care

Abstract

Digital technology is expected to improve care and address significant service pressures within the National Health Service and social care though evidence on how their implementation might be optimised is lacking. This study explores how one such example, home-based sensors with artificial intelligence capabilities, was implemented in English social care to identify changes in behaviour that indicate the onset of potentially more serious issues. Its focus was staff perspectives on decision-making processes and implementation, to inform recommendations for others exploring the potential of new and emerging technology. Qualitative data were collected from 18 semistructured interviews conducted across three sites delivering social care, with senior decision makers, operational leads, and care staff. We identified several issues with the selection process and implementation of AI-based technology in social care, including a lack of consensus around what success would look like, problems identifying and evaluating alternatives, and technical challenges to implementation, as well as obstacles to developing a longer-term, more preventative approach in a system experienced as focused on responding to acute needs. Ultimately, the research confirmed a number of recognised implementation challenges associated with training, resource, and acceptability to staff and patients. It added particular insights around the anxieties experienced by frontline staff and the cultural shift required of preventative interventions in a system geared to meeting acute crises. That many barriers are familiar suggests a particular need to focus on helping policymakers/local leaders avoid similar pitfalls in the future.