Risk of death within 7 days of discharge from emergency departments with different organizational models.

OBJECTIVE: The aim of this study is to investigate the association between emergency department (ED) organizational models and the risk of death within 7 days of ED discharge. PATIENTS AND METHODS: We included Danish ED discharges between 1 January 2011 and 24 December 2014 that led to death within 7 days of discharge. The inclusion criterion was age older than 18 years. The exclusion criterion was further in-hospital admission. First model (Virtual): other departments employ interns who perform ED tasks. They are responsible for ED patient care and prioritize their task order between their own department and the ED. Second model (Hybrid): the ED/other departments perform tasks; interns/consultants are employed by the ED/other departments. The ED/other departments have patient care responsibility. Third model (Independent): the ED performs all tasks; employs interns/consultants; and have patient care responsibility. Sex, age, Charlson Comorbidity Index score, and primary diagnosis were used to describe patient characteristics. We calculated the risk of death within 7 days of discharge using multiple logistic regression analysis. RESULTS: In 805 out of 201 299 discharges included in the study, the patient died within 7 days. Compared with the Virtual model, the odds ratio for death within 7 days of discharge was 0.72 (95% confidence interval: 0.59-0.92) for the Independent model and 0.75 (95% confidence interval: 0.61-0.92) for the Hybrid+Virtual model. Increased risk was associated with male sex, older age, and a medium or a high Charlson Comorbidity Index score. CONCLUSION: Compared with discharges from a Virtual model, the risk of death within 7 days of discharge was lower if the ED had an Independent or a Hybrid+Virtual model.

The organization of Danish emergency departments.

INTRODUCTION: Twenty-one new Danish emergency departments (EDs) were established following a 2007 policy reform that included ED autonomy to self-organize. The aim of this study was to describe the organization of the 21 departments and their organizational challenges. PARTICIPANTS AND METHODS: We used a qualitative design based on COREQ guidelines. All 21 EDs participated, and 123 semi-structured interviews with hospital and ED leaders, physicians, nurses, and secretaries were performed between 2013 and 2015. We used the framework matrix method to investigate the ED goals, setting, structure, staff, task coordination, and incentive structure. RESULTS: We identified three generic models (virtual, hybrid, and independent). All had goals of high quality of care and high efficiency. The virtual model was staffed by junior physicians and tasks were coordinated by other departments. The hybrid model was staffed by junior physicians and senior physicians according to other departments and the ED. The ED coordinated all activities. The independent model was staffed by junior physicians and senior physicians, and activities were coordinated by the ED. Of the EDs, 19 utilized different organizational models at different times during a 24-h period and on weekdays and weekends. The main challenge of the virtual and hybrid models was high dependency on other departments. The main challenge of the independent model was establishing a high level of quality of emergency medicine. DISCUSSION AND CONCLUSION: We identified three organizational ED models (virtual, hybrid, and independent). Nineteen EDs used more than one organizational model depending on the time of day or day of the week.

Is point-of-care ultrasound disruptive innovation? Formulating why POCUS is different from conventional comprehensive ultrasound.

BACKGROUND: Point-of-care ultrasound (PoCUS) is spreading throughout Emergency Medicine, Critical Care and Pre-hospital Care. However, there is an underlying inherited conflict with the established specialties performing comprehensive examinations. It has been stated that PoCUS is disruptive innovation. If this is true the definition might open up for a new perspective on differentiating comprehensive ultrasound from PoCUS. PoCUS in the light of disruptive innovation is a different perspective on ultrasound that has not before been academically scrutinized. METHODS: In this paper we investigate if PoCUS is in fact disruptive innovation. This is done by comparative analysis with the point of departure in disruptive innovation theory known from the business world. RESULTS: We find that a disruptive innovation process is happening. This new knowledge allows us to put forward advice for the stakeholders in the field of ultrasound. It also allows us to challenge the conventional pyramid of expertise used to describe different types of ultrasound. The perspective of this paper is mutual understanding of similarities and differences between conventional and point-of-care ultrasound. Only with this understanding the stakeholders can collaborate and use the full spectrum of ultrasound for the benefit of the patient.

Linking the severity of illness and the weekend effect: a cohort study examining emergency department visits.

BACKGROUND: Despite extensive research on the "weekend effect" i.e., the increased mortality associated with hospital admission during weekend, knowledge about disease severity in previous studies is limited. The aim of this study is to examine patient characteristics, including disease severity, 30-day mortality, and length of stay (LOS), according to time of admission to an emergency department. METHODS: Our study encompassed all patients admitted to a Danish emergency department in 2014-2015. Using data from electronic patient records, this study examines patient characteristics including age, gender, Charlson Comorbidity Index score, triage score, and primary diagnosis. Triage score and transfer to intensive care unit (ICU) were used as indicators of disease severity. LOS within the department and within the hospital was examined. Age- and sex-standardized 30-day mortality rates comparing patients with the same triage score admitted at daytime, evening, and nighttime on weekdays and on weekends were computed. To test differences, a Cox regression analysis was added. RESULTS: We included 35,459 patient visits, of which 10,435 (32%) started on a weekend. There were no large differences in baseline characteristics between patients admitted on weekdays and those admitted on weekends. The relative risk (RR) for being triaged orange or red was 1.16 (95% confidence interval (CI) 1.06-1.28, P = 0.0017) for weekend admissions as compared with weekday admissions. Weekend admissions were twice as likely as weekday admissions to be transferred to the ICU (RR, 1.96; 95% CI 1.53-2.52, P = 0.0000). No significant changes were found in LOS. The 30-day mortality rate increased with disease severity regardless of time of admission. When comparing the 30-day mortality rate for patients with the same triage score, the trend was toward a higher mortality when admission occurred during the weekend. Increasing mortality rate was significant for patients admitted at evening on weekends with a hazard ratio of 1.32 (95% CI 1.03-1.70, P = 0.027) when compared with patients admitted on daytime on weekdays. CONCLUSIONS: When comparing weekday and weekend admissions, the 30-day mortality rate increased for patients admitted at evening on weekends after adjusting for comorbidity and triage score, indicating that the weekend effect was independent of changes in illness severity.