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Abstract Background Assessment and treatment of the acutely ill patient have improved by introducing systematic assessment and accelerated protocols for specific patient groups. Triage systems are widely used, but few studies have investigated the ability of the triage systems in predicting outcome in the unselected acute population. The aim of this study was to quantify the association between the main component of the Hillerød Acute Process Triage (HAPT) system and the outcome measures; Admission to Intensive Care Unit (ICU) and in-hospital mortality, and to identify the vital signs, scored and categorized at admission, that are most strongly associated with the outcome measures. Methods The HAPT system is a minor modification of the Swedish Adaptive Process Triage (ADAPT) and ranks patients into five level colour-coded triage categories. Each patient is assigned a triage category for the two main descriptors; vital signs, Tvitals, and presenting complaint, Tcomplaint. The more urgent of the two determines the final triage category, Tfinal. We retrieved 6279 unique adult patients admitted through the Emergency Department (ED) from the Acute Admission Database. We performed regression analysis to evaluate the association between the covariates and the outcome measures. Results The covariates, Tvitals, Tcomplaint and Tfinal were all significantly associated with ICU admission and in-hospital mortality, the odds increasing with the urgency of the triage category. The vital signs best predicting in-hospital mortality were saturation of peripheral oxygen (SpO2), respiratory rate (RR), systolic blood pressure (BP) and Glasgow Coma Score (GCS). Not only the type, but also the number of abnormal vital signs, were predictive for adverse outcome. The presenting complaints associated with the highest in-hospital mortality were 'dyspnoea' (11.5%) and 'altered level of consciousness' (10.6%). More than half of the patients had a Tcomplaint more urgent than Tvitals, the opposite was true in just 6% of the patients. Conclusion The HAPT system is valid in terms of predicting in-hospital mortality and ICU admission in the adult acute population. Abnormal vital signs are strongly associated with adverse outcome, while including the presenting complaint in the triage model may result in over-triage.

Abstract Background Management and care of the acutely ill patient has improved over the last years due to introduction of systematic assessment and accelerated treatment protocols. We have, however, sparse knowledge of the association between patient status at admission to hospital and patient outcome. A likely explanation is the difficulty in retrieving all relevant information from one database. The objective of this article was 1) to describe the formation and design of the 'Acute Admission Database', and 2) to characterize the cohort included. Methods All adult patients triaged at the Emergency Department at Hillerød Hospital and admitted either to the observationary unit or to a general ward in-hospital were prospectively included during a period of 22 weeks. The triage system used was a Danish adaptation of the Swedish triage system, ADAPT. Data from 3 different data sources was merged using a unique identifier, the Central Personal Registry number; 1) Data from patient admission; time and date, vital signs, presenting complaint and triage category, 2) Blood sample results taken at admission, including a venous acid-base status, and 3) Outcome measures, e.g. length of stay, admission to Intensive Care Unit, and mortality within 7 and 28 days after admission. Results In primary triage, patients were categorized as red (4.4%), orange (25.2%), yellow (38.7%) and green (31.7%). Abnormal vital signs were present at admission in 25% of the patients, most often temperature (10.5%), saturation of peripheral oxygen (9.2%), Glasgow Coma Score (6.6%) and respiratory rate (4.8%). A venous acid-base status was obtained in 43% of all patients. The majority (78%) had a pH within the normal range (7.35-7.45), 15% had acidosis (pH < 7.35) and 7% had alkalosis (pH > 7.45). Median length of stay was 2 days (range 1-123). The proportion of patients admitted to Intensive Care Unit was 1.6% (95% CI 1.2-2.0), 1.8% (95% CI 1.5-2.2) died within 7 days, and 4.2% (95% CI 3.7-4.7) died within 28 days after admission. Conclusions Despite challenges of data registration, we succeeded in creating a database of adequate size and data quality. Future studies will focus on the association between patient status at admission and patient outcome, e.g. admission to Intensive Care Unit or in-hospital mortality.