A systematic review of triage-related interventions to improve patient flow in emergency departments

Background Overcrowding in emergency departments is a worldwide problem. A systematic literature review was undertaken to scientifically explore which interventions improve patient flow in emergency departments. Methods A systematic literature search for flow processes in emergency departments was followed by assessment of relevance and methodological quality of each individual study fulfilling the inclusion criteria. Studies were excluded if they did not present data on waiting time, length of stay, patients leaving the emergency department without being seen or other flow parameters based on a nonselected material of patients. Only studies with a control group, either in a randomized controlled trial or in an observational study with historical controls, were included. For each intervention, the level of scientific evidence was rated according to the GRADE system, launched by a WHO-supported working group. Results The interventions were grouped into streaming, fast track, team triage, point-of-care testing (performing laboratory analysis in the emergency department), and nurse-requested x-ray. Thirty-three studies, including over 800,000 patients in total, were included. Scientific evidence on the effect of fast track on waiting time, length of stay, and left without being seen was moderately strong. The effect of team triage on left without being seen was relatively strong, but the evidence for all other interventions was limited or insufficient. Conclusions Introducing fast track for patients with less severe symptoms results in shorter waiting time, shorter length of stay, and fewer patients leaving without being seen. Team triage, with a physician in the team, will probably result in shorter waiting time and shorter length of stay and most likely in fewer patients leaving without being seen. There is only limited scientific evidence that streaming of patients into different tracks, performing laboratory analysis in the emergency department or having nurses to request certain x-rays results in shorter waiting time and length of stay.

The uptake of an early warning system in an Australian emergency department : a pilot study

Objectives: To evaluate the uptake of an emergency department early warning system (ED EWS) for recognition of, and response to, clinical deterioration.

Design, setting and participants: A descriptive exploratory study conducted in an urban district hospital in Melbourne, Australia. Systematic sampling was used to identify every 10th patient for whom the ED EWS was activated from May 2009 to May 2011.

Main outcome measures: Patient characteristics, ED system data and ED EWS activation characteristics.

Results: ED EWS activation occurred in 1.5% of ED patients; 204 patients were included in this pilot study. The median age was 65.1 years (interquartile range [IQR], 47.8-77.5 years), 89.2% of patients were classified as triage category 2 or 3, and 82.4% of patients were seen by medical staff before ED EWS activation. Hypotension (27.7%) and tachycardia (23.7%) were the most common reasons for ED EWS activation. Median duration of clinical instability was 39 minutes (IQR, 5- 129 minutes). Nurses made 93.1% of ED EWS activations. Median time between documenting physiological abnormalities and ED EWS activation was 5 minutes (IQR, 0- 20). Most patients (57.8%) required hospital admission: 4.4% of patients required intensive care unit admission.

Conclusions: The ED EWS resulted in at least two formal reports of clinical deterioration in ED patients per day, indicating reasonable uptake by clinicians. A greater understanding of clinical deterioration in ED patients is warranted to inform an evidence-based approach to recognition of, and response to, clinical deterioration in ED patients.

Characteristics and outcomes of patients requiring rapid response system activation within 24 hours of emergency admission

Objectives: 

Model to predict inpatient mortality from information gathered at presentation to an emergency department: The Triage Information Mortality Model (TIMM)

OBJECTIVES: To derive and validate a mortality prediction model from information available at ED triage. METHODS: Multivariable logistic regression of variables from administrative datasets to predict inpatient mortality of patients admitted through an ED. Accuracy of the model was assessed using the receiver operating characteristic area under the curve (ROC-AUC) and calibration using the Hosmer-Lemeshow goodness of fit test. The model was derived, internally validated and externally validated. Derivation and internal validation were in a tertiary referral hospital and external validation was in an urban community hospital. RESULTS: The ROC-AUC for the derivation set was 0.859 (95% CI 0.856-0.865), for the internal validation set was 0.848 (95% CI 0.840-0.856) and for the external validation set was 0.837 (95% CI 0.823-0.851). Calibration assessed by the Hosmer-Lemeshow goodness of fit test was good. CONCLUSIONS: The model successfully predicts inpatient mortality from information available at the point of triage in the ED.

A community nurse referral system for HMRs: Can it work?

The HMR model contains a mechanism whereby anyone who is concerned about the risk of medication misadventure can request a HMR from the patient's GP. Since nurses are widely involved in a range of triage and gatekeeping roles, utilising their primary care skills to identify patients for a HMR is a logical extension of this role. Furthermore, community nurses visit their clients in the home situation and see many difficulties the client may be experiencing at first hand. They are therefore well placed to request specialist assistance for the client. Blue Care in Brisbane, a community nursing service, approached its local Division of General practice to determine how best to request HMRs for its clients. The Division contacted The University of Queensland which initiated this study to engage the health care team to tailor the established HMR request process to the needs of community nurses and test the system developed. (non-author abstract)

Morphology of breast cancer as a means of triage of patients for BRCA1 genetic testing

Background: Women who have germline mutations in the BRCA1 gene are at substantially increased lifetime risk of developing breast and ovarian cancer but are otherwise normal. Currently. early age of onset of cancer and a strong family history are relied upon as the chief clues as to who should be offered genetic testing. Certain morphologic and immunohistochemical features are overrepresented in BRCA1-associated breast cancers but these differences have not been incorporated into the current selection criteria for genetic testing. Design: Each of the 4 pathologists studied 30 known cases of BRCA1- and BRCA2-associated breast cancer from kConFab families. After reviewing the literature, we agreed on a semiquantitative scoring system for estimating the chances of presence of an underlying BRCA1 mutation, based on the number of the reported prototypic features present. After a time lag of 12 months, we each examined a series of 62 deidentified cases of breast cancer, inclusive of cases of BRCA1-associated breast cancer and controls. The controls included cases of BRCA2-associated breast cancer and sporadic cases. Results: Our predictions had a sensitivity of 92%, specificity of 86%, positive predictive value of 61%, and negative predictive value of 98%. For comparison the sensitivity of currently used selection criteria are in the range of 25% to 30%. Conclusion: The inclusion of morphologic and immunohistochemical features of breast cancers in algorithms to predict the likelihood of presence of germline mutations in the BRCA1 gene improves the accuracy of the selection process.

Clinical decision support system for point of care use: ontology driven design and software implementation

OBJECTIVES: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation. METHODS: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications' functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions. RESULTS: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical prostatectomy on the hospital ward) and implemented on two computing platforms-desktop and handheld computers. CONCLUSIONS: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system.