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Service Improvement Needs an Understanding of Complex Environments: Causal Diagrams Help Elucidate Causes and Patient
Gillian E Francis1, Mark Leaning1,2, Barbara Cleaver1,3
1Sort-ED Partnership LLP, Reading, UK.
Rationale:
Triage frequently fails to identify critically ill patients and needs improved methods. Limited understanding, or errors in multivariable models are likely to impede progress in service improvement.
Aims:
(1) to reveal a complex web of potential causal pathways stemming from nurses' decisions at triage and patient flow. (2) to add to the understanding of, and research methodology for triage.
Methods:
Secondary data analysis of records from a 91 month convenience sample of all patients attending a general Emergency Department (ED) was used to pose new questions about the functioning of triage systems. A conceptual model of the impact of patient flow on triage decisions and subsequent events was developed. Directed Acyclic Graphs (DAGs) were constructed to assist in the understanding of results and future research.
Results:
Analysis showed a pivotal role for collection of vital signs data with far-reaching and surprisingly marked consequences. The response of triage nurses to time pressure revealed a complex 'web' of interactions and some unexpected findings. Safety and outcomes for patients were measurably affected and even the risky decisions some patients took to leave ED were influenced.
Conclusion:
Triage is failing patients, ED staff and hospitals in complex ways and needs improvement. DAGs are useful for preventing mistakes in statistical analyses and improving research studies. By combining these with informal diagrams we hope to bridge communication barriers, since improving quality of care needs a multidisciplinary effort. Implications for the profession and patient care are outlined.
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