Objectives: To 1) assess consistency in triage disposition among pediatric telephone triage nurses using computer-based algorithms and 2) determine agreement between nurse dispositions and protocol dispositions.

Design/methods: Fifteen nurses from the After Hours Telephone Care Program in Denver were randomly selected to receive mock calls from standardized patients. Each nurse received the same 15 scenarios. Reliability in triage disposition was assessed using the kappa statistic. Audiotapes of cases were reviewed if an urgent referral was warranted by the protocol but not given 20% or more of the time.

Results: Mean agreement among nurses for individual cases was 83% (range, 64%-100%). Overall interrater reliability among nurses for triage disposition was 0.46 (95% confidence interval, 0.43-0.49). Mean agreement between nurses' dispositions and protocol dispositions was 81% (range, 33%-100%). Audio review revealed no differences in length of call or information elicited between cases receiving urgent and nonurgent dispositions. Reasons for incorrect dispositions were 1) information necessary to make the disposition directed by the protocol was given and ignored and 2) nurses did not elicit the necessary information prescribed by the protocol.

Conclusions: Agreement regarding disposition decisions among call center nurses and between nurses and protocols was close to 80%. Disagreement with protocol dispositions occurred when nurses 1) did not follow protocols or 2) did not act on information provided by the parent. Our data suggest a need for additional attention to communication skills and to protocol adherence in training and ongoing quality improvement practices.

Download full-text PDF

Source
http://dx.doi.org/10.1367/1539-4409(2002)002<0396:cotdbc>2.0.co;2DOI Listing

Publication Analysis

Top Keywords

triage disposition
12
nurses
9
consistency triage
8
decisions call
8
call center
8
center nurses
8
dispositions protocol
8
protocol dispositions
8
dispositions
6
protocol
6

Similar Publications

Introduction: Patients with blunt chest wall injuries and rib fractures are known to have high rates of atelectasis, pneumonia, pulmonary contusion, and can develop acute respiratory distress syndrome. This can lead to ventilator requirement and dependence, deconditioning secondary to uncontrolled pain, and increased hospital length of stay (LOS). Many studies in the literature have developed triage algorithms in patients with rib fractures to guide disposition and management, and several institutions have gone on to describe their institution-specific management protocols to decrease complications related to traumatic rib fractures.

View Article and Find Full Text PDF

In this study, we investigate the performance of computer vision AI algorithms in predicting patient disposition from the emergency department (ED) using short video clips. Clinicians often use "eye-balling" or clinical gestalt to aid in triage, based on brief observations. We hypothesize that AI can similarly use patient appearance for disposition prediction.

View Article and Find Full Text PDF

Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department.

BMC Emerg Med

December 2024

Department of Bioinformatics and Medical Engineering, Asia University, No. 500, Liufeng Rd., Wufeng Dist, Taichung City, 413305, Taiwan.

Background: Accurate triage is required for efficient allocation of resources and to decrease patients' length of stay. Triage decisions are often subjective and vary by provider, leading to patients being over-triaged or under-triaged. This study developed machine learning models that incorporated natural language processing (NLP) to predict patient disposition.

View Article and Find Full Text PDF

Background: The value of routine bedside lung ultrasound (LUS) for predicting patient disposition during visits to the Emergency Department (ED) is difficult to quantify. We hypothesized that a simplified scoring of bedside-acquired LUS images for the triage of acute respiratory symptoms in the ED would be associated with patient disposition.

Methods: For this observational pragmatic study, we reviewed prospectively-collected bedside LUS images from patients presenting to the ED with acute respiratory symptoms.

View Article and Find Full Text PDF

Objectives: Telemedicine is a growing field, with limited data around its utility supporting pediatric emergency care telephone triage. We instituted telemedicine physician support for nurse telephone triage decisions. When the nursing protocols recommended urgent or emergent care, a telemedicine physician reviewed and modified care urgency if appropriate.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!