title: Performance of the maximum modified early warning score to predict the need for higher care utilization among admitted emergency department patients.
abstract: BACKGROUND
  It is uncertain whether ED-calculated risk scores can predict required intensity of care upon hospital admission. This investigation examines whether versions of the Modified Early Warning Score (MEWS) predict high level of care utilization among patients admitted from the ED.
  
  
  METHODS
  A retrospective chart review of 299 admissions was implemented. Exclusions prior to abstraction included pediatrics, cardiology, or trauma admissions. Using a data-gathering instrument, abstractors recorded physiologic parameters and clinical variables. Risk scores were calculated electronically. In contrast to the original MEWS, the MEWS Max was calculated using data from the entire ED visit. The primary outcome composite included all-cause mortality and higher care utilization within 24 hours.
  
  
  RESULTS
  The final analysis contained 280 participants. 76 (27%) met the composite endpoint of death (n = 1) or higher care utilization (n = 76). The MEWS Max was associated with the composite outcome (OR=l.6 [95% CI 1.3-1.8] for each one point increase). The MEWS Max had moderate predictive ability (C statistic: MEWS Max 0.73 [0.66-0.79]) but classified 82% of participants as intermediate (10-40%) risk. Inclusion of additional variables slightly improved the predictive ability (C statistic 0.76 [0.69-0.82]) and correctly reclassified 17% of patients as <10% risk.
  
  
  CONCLUSIONS
  The MEWS Max has moderate ability to predict the need for higher level of care. Addition of ED length of stay and other variables to MEWS Max may identify patients at both low and high risk of requiring a higher level of care.
authors.affiliation: Department of Emergency Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina 27157, USA.
authors.forename: Corey R
authors.initials: CR
authors.lastname: Heitz
authors.forename: John P
authors.initials: JP
authors.lastname: Gaillard
authors.forename: Howard
authors.initials: H
authors.lastname: Blumstein
authors.forename: Doug
authors.initials: D
authors.lastname: Case
authors.forename: Catherine
authors.initials: C
authors.lastname: Messick
authors.forename: Chadwick D
authors.initials: CD
authors.lastname: Miller
mesh_terms: D000046:Academic Medical Centers; D000328:Adult; D000368:Aged; D004636:Emergency Service, Hospital; D005260:Female; D005544:Forecasting; D006296:Health Services / Q000706:statistics & numerical data*; D006801:Humans; D007297:Inpatients; D008297:Male; D008485:Medical Audit; D008875:Middle Aged; D011237:Predictive Value of Tests; D015397:Program Evaluation; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D017751:Safety Management; D014218:Triage / Q000379:methods*