title: Real-Time Risk Prediction on the Wards: A Feasibility Study.
abstract: Failure to detect clinical deterioration in the hospital is common and associated with poor patient outcomes and increased healthcare costs. Our objective was to evaluate the feasibility and accuracy of real-time risk stratification using the electronic Cardiac Arrest Risk Triage score, an electronic health record-based early warning score.
  
  
  
  We conducted a prospective black-box validation study. Data were transmitted via HL7 feed in real time to an integration engine and database server wherein the scores were calculated and stored without visualization for clinical providers. The high-risk threshold was set a priori. Timing and sensitivity of electronic Cardiac Arrest Risk Triage score activation were compared with standard-of-care Rapid Response Team activation for patients who experienced a ward cardiac arrest or ICU transfer.
  
  
  
  Three general care wards at an academic medical center.
  
  
  
  A total of 3,889 adult inpatients.
  
  
  
  The system generated 5,925 segments during 5,751 admissions. The area under the receiver operating characteristic curve for electronic Cardiac Arrest Risk Triage score was 0.88 for cardiac arrest and 0.80 for ICU transfer, consistent with previously published derivation results. During the study period, eight of 10 patients with a cardiac arrest had high-risk electronic Cardiac Arrest Risk Triage scores, whereas the Rapid Response Team was activated on two of these patients (p < 0.05). Furthermore, electronic Cardiac Arrest Risk Triage score identified 52% (n = 201) of the ICU transfers compared with 34% (n = 129) by the current system (p < 0.001). Patients met the high-risk electronic Cardiac Arrest Risk Triage score threshold a median of 30 hours prior to cardiac arrest or ICU transfer versus 1.7 hours for standard Rapid Response Team activation.
  
  
  
  Electronic Cardiac Arrest Risk Triage score identified significantly more cardiac arrests and ICU transfers than standard Rapid Response Team activation and did so many hours in advance.
authors.affiliation: 1Pritzker School of Medicine, University of Chicago, Chicago, IL. 2Department of Medicine, University of Chicago, Chicago, IL.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Kang
authors.forename: Matthew M
authors.initials: MM
authors.lastname: Churpek
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Zadravecz
authors.forename: Richa
authors.initials: R
authors.lastname: Adhikari
authors.forename: Nicole M
authors.initials: NM
authors.lastname: Twu
authors.forename: Dana P
authors.initials: DP
authors.lastname: Edelson
mesh_terms: D000046:Academic Medical Centers / Q000706:statistics & numerical data; D000328:Adult; D000368:Aged; D057286:Electronic Health Records; D005240:Feasibility Studies; D005260:Female; D006323:Heart Arrest / Q000175:diagnosis*; D057209:Hospital Rapid Response Team / Q000706:statistics & numerical data*; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011446:Prospective Studies; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012720:Severity of Illness Index; D013997:Time Factors; D055986:Vital Signs