Modified Early Warning System as a Predictor for Hospital Admissions and Previous Visits in Emergency Departments.
This study addresses the development of a modified early warning system (MEWS) to predict hospital admissions from emergency departments (EDs) using the 2010 National Hospital Ambulatory Medical Care Survey (NHAMCS). A MEWS score was created for each patient in the NHAMCS data set using the vital signs recorded at admission. Multiple logistic regression analyses indicated that for every 1 unit increase in the MEWS score, patients were 33% more likely to be admitted to the hospital for further care even after controlling for demographics. Females were 19% less likely to be admitted and older persons were more likely to be admitted. A MEWS score of 13 resulted in almost 90% chance of admission to the hospital. Results indicate that an early warning system may be used to identify signs of physiological decline in many health care settings. Use of MEWS in EDs could be a helpful predictor of the need for hospitalization and could serve as a focus for early decision making and as a point of comparison for efficacy of interventions both in the emergency department and if the patient is admitted to the hospital.
College of Nursing and Health Innovation, University of Texas at Arlington.
Regina W
RW
Urban
Mercy
M
Mumba
Shirley D
SD
Martin
Janet
J
Glowicz
Daisha J
DJ
Cipher
D000293:Adolescent; D000328:Adult; D000368:Aged; D016529:Emergency Nursing; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006305:Health Status Indicators; D006760:Hospitalization; D006801:Humans; D008297:Male; D008875:Middle Aged; D009730:Nursing Assessment; D011237:Predictive Value of Tests; D012307:Risk Factors; D011795:Surveys and Questionnaires; D014481:United States