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.
ABSTRACT
Introduction: Arriving at a C. difficile infection (CDI) diagnosis, treating patients and dealing with recurrences is not straightforward, but a comprehensive and well-rounded understanding of what is needed to improve patient care is lacking. This manuscript addresses the paucity of multidisciplinary perspectives that consider clinical practice related and healthcare system-related challenges to optimizing care delivery. Methods: We draw on narrative review, consultations with clinical experts and patient representatives, and a survey of 95 clinical and microbiology experts from the UK, France, Italy, Australia and Canada, adding novel multi-method evidence to the knowledge base. Results and discussion: We examine the patient pathway and variations in clinical practice and identify, synthesize insights on and discuss associated challenges. Examples of key challenges include the need to conduct multiple tests for a conclusive diagnosis, treatment side-effects, the cost of some antibiotics and barriers to access of fecal microbiota transplantation, difficulties in distinguishing recurrence from new infection, workforce capacity constraints to effective monitoring of patients on treatment and of recurrence, and ascertaining whether a patient has been cured. We also identify key opportunities and priorities for improving patient care that target both clinical practice and the wider healthcare system. While there is some variety across surveyed countries' healthcare systems, there is also strong agreement on some priorities. Key improvement actions seen as priorities by at least half of survey respondents in at least three of the five surveyed countries include: developing innovative products for both preventing (Canada, Australia, UK, Italy, and France) and treating (Canada, Australia, and Italy) recurrences; facilitating more multidisciplinary patient care (UK, Australia, and France); updating diagnosis and treatment guidelines (Australia, Canada, and UK); and educating and supporting professionals in primary care (Italy, UK, Canada, and Australia) and those in secondary care who are not CDI experts (Italy, Australia, and France) on identifying symptoms and managing patients. Finally, we discuss key evidence gaps for a future research agenda.