Observational studyBMC emergency medicine2013
Optimizing triage and hospitalization in adult general medical emergency patients: the triage project.
Observational study in BMC emergency medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01768494 (Optimizing Triage and Hospitalisation In Adult General Medical Emergency Patients), which is not on this map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Optimizing Triage and Hospitalisation In Adult General Medical Emergency Patients: the TRIAGE Study
Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 67 citations in OpenAlex.
- Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections.Respiratory research · 2015Pooled it
- Biomarkers from distinct biological pathways improve early risk stratification in medical emergency patients: the multinational, prospective, observational TRIAGE study.Critical care (London, England) · 2015Trial
- An Effective Triage Education Method for Triage Nurses: An Overview and Update.Open access emergency medicine : OAEM · 2025Review
- Alleviating the medical strain: a triage method via cross-domain text classification.Frontiers in computational neuroscience · 2024Article
- Risk assessment of sepsis through measurement of proAVP (copeptin): a secondary analysis of the TRIAGE study.Endocrine connections · 2021Article
- Quality of life after hospitalization predicts one-year readmission risk in a large Swiss cohort of medical in-patients.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021Article
- Outcomes of Hospitalized Patients with Glucocorticoid-Induced Hyperglycemia-A Retrospective Analysis.Journal of clinical medicine · 2020Article
- Comparison of deep learning models for natural language processing-based classification of non-English head CT reports.Neuroradiology · 2020Article
- What Are They Worth? Six 30-Day Readmission Risk Scores for Medical Inpatients Externally Validated in a Swiss Cohort.Journal of general internal medicine · 2020Article
- Evaluation of a modified South African Triage Score as a predictor of patient disposition at a tertiary hospital in Rwanda.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2020Article
- A Gradient Boosting Machine Learning Model for Predicting Early Mortality in the Emergency Department Triage: Devising a Nine-Point Triage Score.Journal of general internal medicine · 2020Article
- Observational
- Validation of a Prediction Rule forOpen forum infectious diseases · 2019Article
- Observational
- Observational
- Improving the post-acute care discharge score (PACD) by adding patients' self-care abilities: A prospective cohort study.PloS one · 2019Observational
- Article
- Predictive factors of intracranial bleeding in head trauma patients receiving antiplatelet therapy admitted to an emergency department.Scandinavian journal of trauma, resuscitation and emergency medicine · 2018Article
- Prediction of post-acute care demand in medical and neurological inpatients: diagnostic assessment of the post-acute discharge score - a prospective cohort study.BMC health services research · 2018Observational
- Peripheral monocytosis as a predictive factor for adverse outcome in the emergency department: Survey based on a register study.Medicine · 2017Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
24 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients presenting to the emergency department (ED) currently face inacceptable delays in initial treatment, and long, costly hospital stays due to suboptimal initial triage and site-of-care decisions. Accurate ED triage should focus not only on initial treatment priority, but also on prediction of medical risk and nursing needs to improve site-of-care decisions and to simplify early discharge management. Different triage scores have been proposed, such as the Manchester triage system (MTS). Yet, these scores focus only on treatment priority, have suboptimal performance and lack validation in the Swiss health care system. Because the MTS will be introduced into clinical routine at the Kantonsspital Aarau, we propose a large prospective cohort study to optimize initial patient triage. Specifically, the aim of this trial is to derive a three-part triage algorithm to better predict (a) treatment priority; (b) medical risk and thus need for in-hospital treatment; (c) post-acute care needs of patients at the most proximal time point of ED admission. METHODS/
designProspective, observational, multicenter, multi-national cohort study. We will include all consecutive medical patients seeking ED care into this observational registry. There will be no exclusions except for non-adult and non-medical patients. Vital signs will be recorded and left over blood samples will be stored for later batch analysis of blood markers. Upon ED admission, the post-acute care discharge score (PACD) will be recorded. Attending ED physicians will adjudicate triage priority based on all available results at the time of ED discharge to the medical ward. Patients will be reassessed daily during the hospital course for medical stability and readiness for discharge from the nurses and if involved social workers perspective. To assess outcomes, data from electronic medical records will be used and all patients will be contacted 30 days after hospital admission to assess vital and functional status, re-hospitalization, satisfaction with care and quality of life measures. We aim to include between 5000 and 7000 patients over one year of recruitment to derive the three-part triage algorithm. The respective main endpoints were defined as (a) initial triage priority (high vs. low priority) adjudicated by the attending ED physician at ED discharge, (b) adverse 30 day outcome (death or intensive care unit admission) within 30 days following ED admission to assess patients risk and thus need for in-hospital treatment and (c) post acute care needs after hospital discharge, defined as transfer of patients to a post-acute care institution, for early recognition and planning of post-acute care needs. Other outcomes are time to first physician contact, time to initiation of adequate medical therapy, time to social worker involvement, length of hospital stay, reasons for discharge delays, patient's satisfaction with care, overall hospital costs and patients care needs after returning home. DISCUSSION: Using a reliable initial triage system for estimating initial treatment priority, need for in-hospital treatment and post-acute care needs is an innovative and persuasive approach for a more targeted and efficient management of medical patients in the ED. The proposed interdisciplinary , multi-national project has unprecedented potential to improve initial triage decisions and optimize resource allocation to the sickest patients from admission to discharge. The algorithms derived in this study will be compared in a later randomized controlled trial against a usual care control group in terms of resource use, length of hospital stay, overall costs and patient's outcomes in terms of mortality, re-hospitalization, quality of life and satisfaction with care.
trial registrationClinicalTrials.gov Identifier, NCT01768494.
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