Age-adjusted interpretation of biomarkers of renal function and homeostasis, inflammation, and circulation in Emergency Department patients.

Appropriate interpretation of blood tests is important for risk stratification and guidelines used in the Emergency Department (ED) (such as SIRS or CURB-65). The impact of abnormal blood test values on mortality may change with increasing age due to (patho)-physiologic changes. The aim of this study was therefore to assess the effect of age on the case-mix adjusted association between biomarkers of renal function and homeostasis, inflammation and circulation and in-hospital mortality.

The association between vital signs and clinical outcomes in emergency department patients of different age categories.

Background: Appropriate interpretation of vital signs is essential for risk stratification in the emergency department (ED) but may change with advancing age. In several guidelines, risk scores such as the Systemic Inflammatory Response Syndrome SIRS) and Quick Sequential Organ Failure Assessment (qSOFA) scores, commonly used in emergency medicine practice (as well as critical care) specify a single cut-off or threshold for each of the commonly measured vital signs. Although a single cut-off may be convenient, it is unknown whether a single cut-off for vital signs truly exists and if the association between vital signs and in-hospital mortality differs per age-category.

The association between presenting complaints and clinical outcomes in emergency department patients of different age categories.

Background And Importance: Although aging societies in Western Europe use presenting complaints (PCs) in emergency departments (EDs) triage systems to determine the urgency and severity of the care demand, it is unclear whether their prognostic value is age-dependent.

Objective: To assess the frequency and association of PCs with hospitalization and mortality across age categories.

Methods: An observational multicenter study using all consecutive visits of three EDs in the Netherlands Emergency department Evaluation Database.

Machine learning for developing a prediction model of hospital admission of emergency department patients: Hype or hope?

Objective: Early identification of emergency department (ED) patients who need hospitalization is essential for quality of care and patient safety. We aimed to compare machine learning (ML) models predicting the hospitalization of ED patients and conventional regression techniques at three points in time after ED registration.

Methods: We analyzed consecutive ED patients of three hospitals using the Netherlands Emergency Department Evaluation Database (NEED).

Effects of a general practitioner cooperative co-located with an emergency department on patient throughput.

Background: In 2013 a General Practitioner Cooperative (GPC) was introduced at the Emergency Department (ED) of our hospital. One of the aims of this co-located GPC was to improve throughput of the remaining patients at the ED. To determine the change in patient flow, we assessed the number of self-referrals, redirection of self-referrals to the GPC and back to the ED, as well as ward and ICU admission rates and length of stay of the remaining ED population.

Emergency department crowding in The Netherlands: managers' experiences.

Background: In The Netherlands, the state of emergency department (ED) crowding is unknown. Anecdotal evidence suggests that current ED patients experience a longer length of stay (LOS) compared to some years ago, which is indicative of ED crowding. However, no multicenter studies have been performed to quantify LOS and assess crowding at Dutch EDs.

Diagnostic accuracy of emergency nurse practitioners versus physicians related to minor illnesses and injuries.

Introduction: Our objectives were to determine the incidence of missed injuries and inappropriately managed cases in patients with minor injuries and illnesses and to evaluate diagnostic accuracy of the emergency nurse practitioners (ENPs) compared with junior doctors/senior house officers (SHOs).

Methods: In a descriptive cohort study, 741 patients treated by ENPs were compared with a random sample of 741 patients treated by junior doctors/SHOs. Groups were compared regarding incidence and severity of missed injuries and inappropriately managed cases, waiting times, and length of stay.