Electronic algorithmic prediction of central vascular catheter use.
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.
Hota
Bala
B
John H. Stroger, Jr, Hospital of Cook County, Chicago, Illinois, USA. bhota@rush.edu
Harting
Brian
B
Weinstein
Robert A
RA
Lyles
Rosie D
RD
Bleasdale
Susan C
SC
Trick
William
W
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