BACKGROUND: Hospital at Night (H@N) is a Department of Health (England) driven programme being widely implemented across UK. It aims to redefine how medical cover is provided in hospitals during the out-of-hours period. AIM: To investigate whether the implementation of H@N is associated with significant change in system or clinical outcomes. DESIGN: An observational study for 14 consecutive nights before, and 14 consecutive nights after the implementation of H@N. Data were collected from the Combined surgical and medical Assessment Unit (CAU), the 18 medical/surgical wards (The Ward Arc) and the four High Dependency Units (The Critical Care corridor) within the Royal Infirmary of Edinburgh. METHODS: Following an overnight episode of clinical concern, data were gathered on response time, seniority of reviewing staff, patient outcome and the use of Standardized Early Warning Score (SEWS). RESULTS: Two hundred and nine episodes of clinical concern were recorded before the implementation of H@N and 216 episodes afterwards. There was no significant change in response time in the CAU, Ward Arc or Critical Care corridor. However, significant inter-speciality differences in response time were eradicated, particularly in the Critical Care corridor. Following the implementation of H@N, patients were reviewed more frequently by senior medical staff in CAU (28% vs. 4%, P < 0.05) and the Critical Care corridor (50% vs. 22%, P < 0.001). Finally there was a reduction in adverse outcome (defined as unplanned transfer to critical care/cardiac arrest) in the Ward Arc and CAU from 17% to 6% of patients reviewed overnight (P < 0.01). SEWS was more frequently and accurately recorded in CAU. CONCLUSION: This is the first study that we are aware of directly comparing out-of-hours performance before and after the implementation of H@N. Significant improvements in both patient and system outcomes were observed, with no adverse effects noted.
BACKGROUND: Hospital at Night (H@N) is a Department of Health (England) driven programme being widely implemented across UK. It aims to redefine how medical cover is provided in hospitals during the out-of-hours period. AIM: To investigate whether the implementation of H@N is associated with significant change in system or clinical outcomes. DESIGN: An observational study for 14 consecutive nights before, and 14 consecutive nights after the implementation of H@N. Data were collected from the Combined surgical and medical Assessment Unit (CAU), the 18 medical/surgical wards (The Ward Arc) and the four High Dependency Units (The Critical Care corridor) within the Royal Infirmary of Edinburgh. METHODS: Following an overnight episode of clinical concern, data were gathered on response time, seniority of reviewing staff, patient outcome and the use of Standardized Early Warning Score (SEWS). RESULTS: Two hundred and nine episodes of clinical concern were recorded before the implementation of H@N and 216 episodes afterwards. There was no significant change in response time in the CAU, Ward Arc or Critical Care corridor. However, significant inter-speciality differences in response time were eradicated, particularly in the Critical Care corridor. Following the implementation of H@N, patients were reviewed more frequently by senior medical staff in CAU (28% vs. 4%, P < 0.05) and the Critical Care corridor (50% vs. 22%, P < 0.001). Finally there was a reduction in adverse outcome (defined as unplanned transfer to critical care/cardiac arrest) in the Ward Arc and CAU from 17% to 6% of patients reviewed overnight (P < 0.01). SEWS was more frequently and accurately recorded in CAU. CONCLUSION: This is the first study that we are aware of directly comparing out-of-hours performance before and after the implementation of H@N. Significant improvements in both patient and system outcomes were observed, with no adverse effects noted.
Authors: Andrew D McInnes; Robert M Sutton; Alberto Orioles; Akira Nishisaki; Dana Niles; Benjamin S Abella; Matthew R Maltese; Robert A Berg; Vinay Nadkarni Journal: Resuscitation Date: 2011-03-29 Impact factor: 5.262