title: Predicting Appropriate Admission of Bronchiolitis Patients in the Emergency Department: Rationale and Methods.
abstract: BACKGROUND
  In young children, bronchiolitis is the most common illness resulting in hospitalization. For children less than age 2, bronchiolitis incurs an annual total inpatient cost of $1.73 billion. Each year in the United States, 287,000 emergency department (ED) visits occur because of bronchiolitis, with a hospital admission rate of 32%-40%. Due to a lack of evidence and objective criteria for managing bronchiolitis, ED disposition decisions (hospital admission or discharge to home) are often made subjectively, resulting in significant practice variation. Studies reviewing admission need suggest that up to 29% of admissions from the ED are unnecessary. About 6% of ED discharges for bronchiolitis result in ED returns with admission. These inappropriate dispositions waste limited health care resources, increase patient and parental distress, expose patients to iatrogenic risks, and worsen outcomes. Existing clinical guidelines for bronchiolitis offer limited improvement in patient outcomes. Methodological shortcomings include that the guidelines provide no specific thresholds for ED decisions to admit or to discharge, have an insufficient level of detail, and do not account for differences in patient and illness characteristics including co-morbidities. Predictive models are frequently used to complement clinical guidelines, reduce practice variation, and improve clinicians' decision making. Used in real time, predictive models can present objective criteria supported by historical data for an individualized disease management plan and guide admission decisions. However, existing predictive models for ED patients with bronchiolitis have limitations, including low accuracy and the assumption that the actual ED disposition decision was appropriate. To date, no operational definition of appropriate admission exists. No model has been built based on appropriate admissions, which include both actual admissions that were necessary and actual ED discharges that were unsafe.
  
  
  OBJECTIVE
  The goal of this study is to develop a predictive model to guide appropriate hospital admission for ED patients with bronchiolitis.
  
  
  METHODS
  This study will: (1) develop an operational definition of appropriate hospital admission for ED patients with bronchiolitis, (2) develop and test the accuracy of a new model to predict appropriate hospital admission for an ED patient with bronchiolitis, and (3) conduct simulations to estimate the impact of using the model on bronchiolitis outcomes.
  
  
  RESULTS
  We are currently extracting administrative and clinical data from the enterprise data warehouse of an integrated health care system. Our goal is to finish this study by the end of 2019.
  
  
  CONCLUSIONS
  This study will produce a new predictive model that can be operationalized to guide and improve disposition decisions for ED patients with bronchiolitis. Broad use of the model would reduce iatrogenic risk, patient and parental distress, health care use, and costs and improve outcomes for bronchiolitis patients.
authors.affiliation: School of Medicine, Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States. gangluo@cs.wisc.edu.
authors.forename: Gang
authors.identifier: http://orcid.org/0000-0001-7217-4008
authors.initials: G
authors.lastname: Luo
authors.forename: Bryan L
authors.identifier: http://orcid.org/0000-0002-0912-5227
authors.initials: BL
authors.lastname: Stone
authors.forename: Michael D
authors.identifier: http://orcid.org/0000-0001-5483-5933
authors.initials: MD
authors.lastname: Johnson
authors.forename: Flory L
authors.identifier: http://orcid.org/0000-0002-8954-8288
authors.initials: FL
authors.lastname: Nkoy
keywords: Decision support techniques; computer simulation; forecasting; machine learning