Improving escalation of deteriorating patients through cognitive task analysis: Understanding differences between work-as-prescribed and work-as-done.

BACKGROUND: Appropriate care escalation requires the detection and communication of in-hospital patient deterioration. Although deterioration in the ward environment is common, there continue to be patient deaths where problems escalating care have occurred. Learning from the everyday work of health care professionals (work-as-done) and identifying performance variability may provide a greater understanding of the escalation challenges and how they overcome these. The aims of this study were to i) develop a representative model detailing escalation of care ii) identify performance variability that may negatively or positively affect this process and iii) examine linkages between steps in the escalation process. METHODS: Thirty Applied Cognitive Task Analysis interviews were conducted with clinical experts (>4 years' experience) including Ward Nurses (n = 7), Outreach or Sepsis Nurses (n = 8), Nurse Manager or Consultant (n = 6), Physiotherapists (n = 4), Advanced Practitioners (n = 4), and Doctor (n = 1) from two National Health Service hospitals and analysed using Framework Analysis. Task-related elements of care escalation were identified and represented in a Functional Resonance Analysis Model. FINDINGS: The NEWS2's clinical escalation response constitutes eight unique tasks and illustrates work-as-prescribed, but our interview data uncovered an additional 24 tasks (n = 32) pertaining to clinical judgement, decisions or processes reflecting work-as-done. Over a quarter of these tasks (9/32, 28 %) were identified by experts as cognitively challenging with a high likelihood of performance variability. Three out of the nine variable tasks were closely coupled and interdependent within the Functional Resonance Analysis Model ('synthesising data points', 'making critical decision to escalate' and 'identifying interim actions') so representing points of potential escalation failure. Data assimilation from different clinical information systems with poor usability was identified as a key cognitive challenge. CONCLUSION: Our data support the emphasis on the need to retain clinical judgement and suggest that future escalation protocols and audit guidance require in-built flexibility, supporting staff to incorporate their expertise of the patient condition and the clinical environment. Improved information systems to synthesise the required data surrounding an unwell patient to reduce staff cognitive load, facilitate decision-making, support the referral process and identify actions are required. Fundamentally, reducing the cognitive load when assimilating core escalation data allows staff to provide better and more creative care. Study registration (ISRCTN 38850) and ethical approval (REC Ref 20/HRA/3828; CAG-20CAG0106).