J E Anderson1, A J Ross2, J Back1, M Duncan3, P Snell4, A Hopper5, P Jaye6. 1. Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care, King's College London, London, UK. 2. Dental School, School of Medicine, University of Glasgow, Glasgow, UK. 3. Department of Psychology, IOPPN, King's College London, London, UK. 4. Patricia Snell Healthcare Consulting, London, UK. 5. Guy's and St. Thomas' NHS Foundation Trust, London, UK. 6. Simulation and Interactive Learning (SaIL) Centre, St Thomas' Hospital, King's Health Partners, London, UK.
Abstract
OBJECTIVE: The aim was to develop a method based on resilient healthcare principles to proactively identify system vulnerabilities and quality improvement interventions. DESIGN: Ethnographic methods to understand work as it is done in practice using concepts from resilient healthcare, the Concepts for Applying Resilience Engineering model and the four key activities that are proposed to underpin resilient performance-anticipating, monitoring, responding and learning. SETTING: Accident and Emergency Department (ED) and the Older People's Unit (OPU) of a large teaching hospital in central London. PARTICIPANTS: ED-observations 104 h, and 14 staff interviews. OPU-observations 60 h, and 15 staff interviews. RESULTS: Data were analysed to identify targets for quality improvement. In the OPU, discharge was a complex and variable process that was difficult to monitor. A system to integrate information and clearly show progress towards discharge was needed. In the ED, patient flow was identified as a complex high-intensity activity that was not supported by the existing data systems. The need for a system to integrate and display information about both patient and organizational factors was identified. In both settings, adaptive capacity was limited by the absence of systems to monitor the work environment. CONCLUSIONS: The study showed that using resilient healthcare principles to inform quality improvement was feasible and focused attention on challenges that had not been addressed by traditional quality improvement practices. Monitoring patient and workflow in both the ED and the OPU was identified as a priority for supporting staff to manage the complexity of the work.
OBJECTIVE: The aim was to develop a method based on resilient healthcare principles to proactively identify system vulnerabilities and quality improvement interventions. DESIGN: Ethnographic methods to understand work as it is done in practice using concepts from resilient healthcare, the Concepts for Applying Resilience Engineering model and the four key activities that are proposed to underpin resilient performance-anticipating, monitoring, responding and learning. SETTING: Accident and Emergency Department (ED) and the Older People's Unit (OPU) of a large teaching hospital in central London. PARTICIPANTS: ED-observations 104 h, and 14 staff interviews. OPU-observations 60 h, and 15 staff interviews. RESULTS: Data were analysed to identify targets for quality improvement. In the OPU, discharge was a complex and variable process that was difficult to monitor. A system to integrate information and clearly show progress towards discharge was needed. In the ED, patient flow was identified as a complex high-intensity activity that was not supported by the existing data systems. The need for a system to integrate and display information about both patient and organizational factors was identified. In both settings, adaptive capacity was limited by the absence of systems to monitor the work environment. CONCLUSIONS: The study showed that using resilient healthcare principles to inform quality improvement was feasible and focused attention on challenges that had not been addressed by traditional quality improvement practices. Monitoring patient and workflow in both the ED and the OPU was identified as a priority for supporting staff to manage the complexity of the work.
Authors: Rita Forde; Olubunmi Abiola; Janet Anderson; Debra Bick; Anna Brackenridge; Anita Banerjee; Mark Chamley; Kia-Chong Chua; Lily Hopkins; Katharine Hunt; Helen R Murphy; Helen Rogers; Renee Romeo; James Shearer; Kirsty Winkley; Angus Forbes Journal: BMC Prim Care Date: 2022-04-13
Authors: Natalie Sanford; Mary Lavelle; Ola Markiewicz; Gabriel Reedy; Anne Marie Rafferty; Ara Darzi; Janet E Anderson Journal: BMC Health Serv Res Date: 2022-09-06 Impact factor: 2.908