PURPOSE: The purpose of the paper is to investigate the potential relationships between emergency-care flow, patient mortality and healthcare costs using a patient-flow model. DESIGN/METHODOLOGY/APPROACH: The researchers used performance data from one UK NHS trust collected over three years to identify periods where patient flow was compromised. The delays' root causes in the entire emergency care system were investigated. Event time-lines that disrupted patient flow and patient mortality statistics were compared. FINDINGS: Data showed that patient mortality increases at times when accident and emergency (A&E) department staff were struggling to admit patients. Four delays influenced mortality: first, volume increase and mixed admissions; second, process delays; third, unplanned hospital capacity adjustments and finally, long-term capacity restructuring downstream. RESEARCH LIMITATIONS/IMPLICATIONS: This is an observational study that uses process control data to find times when mortality increases coincide with other events. It captures contextual background to whole system issues that affect patient mortality. PRACTICAL IMPLICATIONS: Managers must consider cost-decisions and flow in the whole system. Localised, cost-focused decisions can have a detrimental effect on patient care. Attention must also be paid to mortality reports as existing data-presentation methods do not allow correlation analysis. ORIGINALITY/VALUE: Previous studies correlate A&E overcrowding and mortality. This method allows the whole system to be studied and increased mortality root causes to be understood.
PURPOSE: The purpose of the paper is to investigate the potential relationships between emergency-care flow, patient mortality and healthcare costs using a patient-flow model. DESIGN/METHODOLOGY/APPROACH: The researchers used performance data from one UK NHS trust collected over three years to identify periods where patient flow was compromised. The delays' root causes in the entire emergency care system were investigated. Event time-lines that disrupted patient flow and patient mortality statistics were compared. FINDINGS: Data showed that patient mortality increases at times when accident and emergency (A&E) department staff were struggling to admit patients. Four delays influenced mortality: first, volume increase and mixed admissions; second, process delays; third, unplanned hospital capacity adjustments and finally, long-term capacity restructuring downstream. RESEARCH LIMITATIONS/IMPLICATIONS: This is an observational study that uses process control data to find times when mortality increases coincide with other events. It captures contextual background to whole system issues that affect patient mortality. PRACTICAL IMPLICATIONS: Managers must consider cost-decisions and flow in the whole system. Localised, cost-focused decisions can have a detrimental effect on patient care. Attention must also be paid to mortality reports as existing data-presentation methods do not allow correlation analysis. ORIGINALITY/VALUE: Previous studies correlate A&E overcrowding and mortality. This method allows the whole system to be studied and increased mortality root causes to be understood.