In emergency departments (EDs), demand for care often exceeds the available resources. Triage addresses this problem by sorting patients into categories of urgency. The Interagency Integrated Triage Tool (IITT) is a novel triage system designed for resource-limited emergency care (EC) settings. The system was piloted by two EDs in Papua New Guinea as part of an EC capacity development program. Implementation involved a five-hour teaching program for all ED staff, complemented by training resources including flowcharts and reference guides. Clinical redesign helped optimise flow and infrastructure, and development of simple electronic registries enabled data collection. Local champions were identified, and experienced EC clinicians from Australia acted as mentors during system roll-out. Evaluation data suggests the IITT, and the associated change management process, have high levels of acceptance amongst staff. Subject to validation, the IITT may be relevant to other resource-limited EC settings.

Background:The Interagency Integrated Triage Tool (IITT) is a three-tier triage system designed for resource-limited emergency care (EC) settings. This study sought to assess the validity and reliability of a pilot version of the tool in an urban emergency department (ED) in Papua New Guinea.Methods: A pragmatic observational study was conducted at Gerehu General Hospital in Port Moresby, commencing eight weeks after IITT implementation. All ED patients presenting within the subsequent two-month period were included. Triage assessments were performed by a variety of ED clinicians, including community health workers, nurses and doctors. The primary outcome was sensitivity for the detection of time-critical illness, defined by ten pre-specified diagnoses. The association between triage category and ED outcomes was examined using Cramer's V correlation coefficient. Reliability was assessed by inter-rater agreement between a local and an experienced, external triage officer.Findings: Among 4512 presentations during the study period, 58 (1.3%) were classified as category one (emergency), 967 (21.6%) as category two (priority) and 3478 (77.1%) as category three (non-urgent). The tool's sensitivity for detecting the pre-specified set of time-sensitive conditions was 70.8% (95%CI 58.2-81.4%), with negative predictive values of 97.3% (95%CI 96.7 -97.8%) for admission/transfer and 99.9% (95%CI 99.7 -100.0%) for death. The admission/transfer rate was 44.8% (26/58) among emergency patients, 22.9% (223/976) among priority patients and 2.7% (94/3478) among non-urgent patients (Cramer's V = 0.351, p = 0.00). Four of 58 (6.9%) emergency patients, 19/976 (2.0%) priority patients and 3/3478 (0.1%) non-urgent patients died in the ED (Cramer's V = 0.14, p = 0.00). The under-triage rate was 2.7% (94/3477) and the over-triage rate 48.2% (28/58), both within pre-specified limits of acceptability. On average, it took staff 3 minutes 34 seconds (SD 1:06) to determine and document a triage category. Among 70 observed assessments, weighted κ was 0.84 (excellent agreement).

Objective: The Interagency Integrated Triage Tool (IITT) is a novel, three-tier triage system recommended by the World Health Organization. The present study sought to assess the validity and reliability of a pilot version of the tool in a resource-limited ED in regional Papua New Guinea. Methods: This pragmatic prospective observational study, conducted at Mount Hagen Provincial Hospital, commenced 1 month after IITT implementation. The facility did not have a pre-existing triage system. All ED patients presenting within a 5-month period were included. The primary outcome was sensitivity for the detection of time-critical illness, defined by 10 pre-specified diagnoses. The association between triage

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Introduction Stroke remains a primary source of functional disability and inpatient mortality in the United States (US). Recent evidence reveals declining mortality associated with stroke hospitalizations in the US. However, data updating trends in inpatient mortality is lacking. This study aims to provide a renewed inpatient stroke mortality rate in a national sample and identify common predictors of inpatient stroke mortality. Methods In this cross-sectional study, we analyzed data from a nationwide database between 2010 and 2017. We included patient encounters for both ischemic (ICD9 433–434, ICD10 I630–I639) and hemorrhagic stroke (ICD9 430–432, ICD10 I600–I629). We performed an annual comparison of in-hospital stroke mortality rates, and a cross-sectional analytic approach of multiple variables identified common predictors of inpatient stroke mortality. Results Between 2010 and 2017, we identified 518,185 total stroke admissions (86.6% ischemic stroke and 13.4% hemorrhagic strokes). Stroke admissions steadily increased during the studied period, whereas we observed a steady decline in in-hospital mortality during the same time. The inpatient stroke mortality rate gradually declined from 4.8% in 2010 (95% CI 4.6–5.1) to 2.1% in 2017 (95% CI 2.0–2.1). Predictors of higher odds of dying from ischemic stroke were female (OR 1.059, 95% CI 1.015–1.105, p = 0.008), older age (OR 1.028, 95% CI 1.026–1.029, p < 0.001), and sicker patients (OR 1.091, 95% CI 1.089–1.093, p < 0.001). Predictors of higher odds of dying from hemorrhagic stroke were Hispanic ethnicity (OR 1.459, 95% CI 1.084–1.926, p < 0.001), older age (OR 1.021, 95% CI 1.019–1.023, p < 0.001), and sicker patients (OR 1.042, 95% CI 1.039–1.045, p < 0.001). All census regions and hospital types demonstrated improvements in in-hospital mortality. Conclusion This study identified a continuous declining rate in in-hospital mortality due to stroke in the United States, and it also identified demographic and hospital predictors of inpatient stroke mortality.