title: Electronic algorithmic prediction of central vascular catheter use.
abstract: OBJECTIVE
  To develop prediction algorithms for the presence of a central vascular catheter in hospitalized patients with use of data present in an electronic health record. Such algorithms could be used for measurement of device utilization rates and for clinical decision support rules.
  
  
  METHODS
  Criterion standard.
  
  
  METHODS
  John H. Stroger, Jr, Hospital of Cook County, a 464-bed public hospital in Chicago, Illinois.
  
  
  METHODS
  Patients admitted to the medical intensive care unit from May 31, 2005 through June 26, 2006 (derivation data set, May 31, 2005-September 28, 2005; validation data set, September 29, 2005-June 28, 2006).
  
  
  METHODS
  Covariates were collected from the electronic medical record for each patient; the outcome variable was presence of a central vascular device. Multivariate models were developed using the derivation set and the generalized estimating equation. Three models, each with increasing database requirements, were validated using the validation set. Device utilization ratios and performance characteristics were calculated.
  
  
  RESULTS
  Although Charlson score and duration of intensive care unit stay were significant predictors in all models, factors that indicated use or presence of a central line were also important. Device utilization rates derived from the algorithmic models were as accurate as those obtained using manual sampling.
  
  
  CONCLUSIONS
  Automated calculation of central vascular catheter use is both feasible and accurate, providing estimates statistically similar to those obtained using manual surveillance. Prediction modeling of central vascular catheter use may enable automated surveillance of bloodstream infections and enhance important prevention interventions, such as timely removal of unnecessary central lines.
authors.affiliation: John H. Stroger, Jr, Hospital of Cook County, Chicago, Illinois, USA. bhota@rush.edu
authors.forename: Bala
authors.initials: B
authors.lastname: Hota
authors.forename: Brian
authors.initials: B
authors.lastname: Harting
authors.forename: Robert A
authors.initials: RA
authors.lastname: Weinstein
authors.forename: Rosie D
authors.initials: RD
authors.lastname: Lyles
authors.forename: Susan C
authors.initials: SC
authors.lastname: Bleasdale
authors.forename: William
authors.initials: W
authors.lastname: Trick
mesh_terms: D000465:Algorithms; D016470:Bacteremia / Q000453:epidemiology / Q000517:prevention & control; D002405:Catheterization, Central Venous / Q000009:adverse effects / Q000706:statistics & numerical data*; D020000:Decision Support Systems, Clinical; D057286:Electronic Health Records; D006801:Humans; D007362:Intensive Care Units; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity