title: Enrollment into a time sensitive clinical study in the critical care setting: results from computerized septic shock sniffer implementation.
abstract: OBJECTIVE
  Recruitment of patients into time sensitive clinical trials in intensive care units (ICU) poses a significant challenge. Enrollment is limited by delayed recognition and late notification of research personnel. The objective of the present study was to evaluate the effectiveness of the implementation of electronic screening (septic shock sniffer) regarding enrollment into a time sensitive (24 h after onset) clinical study of echocardiography in severe sepsis and septic shock.
  
  
  METHODS
  We developed and tested a near-real time computerized alert system, the septic shock sniffer, based on established severe sepsis/septic shock diagnostic criteria. A sniffer scanned patients' data in the electronic medical records and notified the research coordinator on call through an institutional paging system of potentially eligible patients.
  
  
  METHODS
  The performance of the septic shock sniffer was assessed.
  
  
  RESULTS
  The septic shock sniffer performed well with a positive predictive value of 34%. Electronic screening doubled enrollment, with 68 of 4460 ICU admissions enrolled during the 9&emsp14;months after implementation versus 37 of 4149 ICU admissions before sniffer implementation (p<0.05). Efficiency was limited by study coordinator availability (not available at nights or weekends).
  
  
  CONCLUSIONS
  Automated electronic medical records screening improves the efficiency of enrollment and should be a routine tool for the recruitment of patients into time sensitive clinical trials in the ICU setting.
authors.affiliation: Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA. herasevich.vitaly@mayo.edu
authors.forename: Vitaly
authors.initials: V
authors.lastname: Herasevich
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Pieper
authors.forename: Juan
authors.initials: J
authors.lastname: Pulido
authors.forename: Ognjen
authors.initials: O
authors.lastname: Gajic
mesh_terms: D000368:Aged; D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D057210:Delayed Diagnosis / Q000517:prevention & control*; D003936:Diagnosis, Computer-Assisted; D004452:Echocardiography; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008875:Middle Aged; D008910:Minnesota; D018579:Patient Selection; D011237:Predictive Value of Tests; D012772:Shock, Septic / Q000175:diagnosis* / Q000000981:diagnostic imaging; D013997:Time Factors