Dataset Information

ED RAPID: A Novel Children's Hospital Direct Admission Process Utilizing the Emergency Department.

ABSTRACT: Introduction:Direct hospital admission of children without evaluation in the emergency department (ED) is common, but few guidelines exist to maximize safety by assessing patient stability. This report describes a novel approach to support patient safety. Methods:An interdisciplinary children's hospital team developed a brief ED-based evaluation process called the ED Rapid Assessment of Patients Intended for Inpatient Disposition (ED RAPID). It entails a brief evaluation of vital signs and clinical stability by the ED attending physician and nurse. Children deemed stable are admitted to inpatient wards, whereas those requiring immediate intervention undergo full ED evaluation and disposition. We assessed outcomes for all children evaluated through this process from March 2013 through February 2015. Results:During the study period, we identified 715 patients undergoing ED RAPID evaluation. Of these, we directly admitted 691 (96.4%) to the hospital ward after ED RAPID evaluation; median ED treatment time was 4.0 minutes. We transitioned 24 (3.4%) to full ED evaluation, 14 (2.0%) because a ward bed was unavailable, and 10 (1.4%) for clinical reasons identified in the evaluation. We admitted four of the 10 stopped (40% of stops, 0.6% of total) to an intensive care unit, and 6 (60% of stops, 0.8% of total) to the hospital ward after ED care. Eight children (1.1%) admitted to the hospital ward after ED RAPID evaluation required a transfer to an intensive care unit within 12 hours. Conclusion:The ED RAPID evaluation process for children directly admitted to the hospital was feasible and effective in this setting.

SUBMITTER: Louie JP

PROVIDER: S-EPMC7190248 | biostudies-literature | 2020 Mar-Apr

REPOSITORIES: biostudies-literature

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ED RAPID: A Novel Children's Hospital Direct Admission Process Utilizing the Emergency Department.

Louie Jeffrey P JP Furnival Ronald A RA Roback Mark G MG Jacob Abraham K AK Marmet Jordan J Nerheim Daniel D Hendrickson Marissa A MA

Pediatric quality & safety 20200310 2

<h4>Introduction</h4>Direct hospital admission of children without evaluation in the emergency department (ED) is common, but few guidelines exist to maximize safety by assessing patient stability. This report describes a novel approach to support patient safety.<h4>Methods</h4>An interdisciplinary children's hospital team developed a brief ED-based evaluation process called the ED Rapid Assessment of Patients Intended for Inpatient Disposition (ED RAPID). It entails a brief evaluation of vital ...[more]

PMID: 32426634

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Project description:ObjectivesHospitalisation is frequently used as a marker of disease severity in observational Emergency Department (ED) studies. The comparison of ED admission rates is complex in potentially being influenced by the characteristics of the region, ED, physician and patient. We aimed to study variation in ED admission rates of febrile children, to assess whether variation could be explained by disease severity and to identify patient groups with large variation, in order to use this to reduce unnecessary health care utilization that is often due to practice variation.DesignMOFICHE (Management and Outcome of Fever in children in Europe, part of the PERFORM study, www.perform2020.org), is a prospective cohort study using routinely collected data on febrile children regarding patient characteristics (age, referral, vital signs and clinical alarming signs), diagnostic tests, therapy, diagnosis and hospital admission.Setting and participantsData were collected on febrile children aged 0-18 years presenting to 12 European EDs (2017-2018).Main outcome measuresWe compared admission rates between EDs by using standardised admission rates after adjusting for patient characteristics and initiated tests at the ED, where standardised rates >1 demonstrate higher admission rates than expected and rates <1 indicate lower rates than expected based on the ED patient population.ResultsWe included 38,120 children. Of those, 9.695 (25.4%) were admitted to a general ward (range EDs 5.1-54.5%). Adjusted standardised admission rates ranged between 0.6 and 1.5. The largest variation was seen in short admission rates (0.1-5.0), PICU admission rates (0.2-2.2), upper respiratory tract infections (0.4-1.7) and fever without focus (0.5-2.7). Variation was small in sepsis/meningitis (0.9-1.1).ConclusionsLarge variation exists in admission rates of febrile children evaluated at European EDs, however, this variation is largely reduced after correcting for patient characteristics and therefore overall admission rates seem to adequately reflect disease severity or a potential for a severe disease course. However, for certain patient groups variation remains high even after adjusting for patient characteristics.

Project description:ObjectiveTo predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.MethodsThis retrospective study included all adult ED visits between March 2014 and July 2017 from one academic and two community emergency rooms that resulted in either admission or discharge. A total of 972 variables were extracted per patient visit. Samples were randomly partitioned into training (80%), validation (10%), and test (10%) sets. We trained a series of nine binary classifiers using logistic regression (LR), gradient boosting (XGBoost), and deep neural networks (DNN) on three dataset types: one using only triage information, one using only patient history, and one using the full set of variables. Next, we tested the potential benefit of additional training samples by training models on increasing fractions of our data. Lastly, variables of importance were identified using information gain as a metric to create a low-dimensional model.ResultsA total of 560,486 patient visits were included in the study, with an overall admission risk of 29.7%. Models trained on triage information yielded a test AUC of 0.87 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.88) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on patient history yielded an AUC of 0.86 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.87) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on the full set of variables yielded an AUC of 0.91 for LR (95% CI 0.91-0.91), 0.92 for XGBoost (95% CI 0.92-0.93) and 0.92 for DNN (95% CI 0.92-0.92). All algorithms reached maximum performance at 50% of the training set or less. A low-dimensional XGBoost model built on ESI level, outpatient medication counts, demographics, and hospital usage statistics yielded an AUC of 0.91 (95% CI 0.91-0.91).ConclusionMachine learning can robustly predict hospital admission using triage information and patient history. The addition of historical information improves predictive performance significantly compared to using triage information alone, highlighting the need to incorporate these variables into prediction models.

Project description:BackgroundCompared with conventional hospitalization, admission to an acute geriatric care unit (AGU) is associated with better outcomes in elderly patients. In 2012, 50% of the hospitalizations of elderly patients were preceded by an emergency department (ED) visit. Hospital occupancy, access blocks and overcrowding experienced by patients during ED visits are associated with increased morbidity.ObjectiveOur aim was to evaluate the effect of direct admission (DA) to an AGU on both the hospital length of stay and morbidity of elderly patients.DesignThis study was a retrospective cohort study conducted using electronic medical records and administrative claims data from the Greater Paris University Hospitals (APHP) health data warehouse involving 19 different AGUs.ParticipantsWe included all patients ≥ 75 years old who were admitted to an AGU for more than 24 h between January 1, 2013, and December 31, 2018.InterventionDirect admission to the AGU compared to admission after an ED visit.Main measuresThe main outcome was hospital length of stay. Two outcomes were used to analyse morbidity: postacute care and rehabilitation ward transfer at the end of the index hospitalization and ED return visit within 30 days after the index hospitalization (for those who survived to hospitalization). We used an inverse probability of treatment weighting (IPTW) approach to balance the differences in patient baseline variables between the two groups. Univariate linear and logistic regression models were built to estimate the effect of DA on hospital length of stay and the likelihood of postacute care transfer and ED return visit.Key resultsAmong the 6583 patients included in the study, DA was associated with a lower hospital length of stay (estimate = -1.28; 95% CI = -1.76-0.80), and a lower likelihood of postacute care transfer (OR = 0.87; 95% CI = 0.77-0.97). It was not significantly associated with a lower risk of ED return visits (OR = 0.81; 95% CI = 0.60-1.08) in the following month.ConclusionDA should be prioritized, and reorganization of the geriatric pathway around DA should be encouraged due to the frailty of elderly individuals.

Dataset Information

ED RAPID: A Novel Children's Hospital Direct Admission Process Utilizing the Emergency Department.

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ED RAPID: A Novel Children's Hospital Direct Admission Process Utilizing the Emergency Department.

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