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Electronic Algorithmic Prediction of Central Vascular Catheter Use

Published online by Cambridge University Press:  02 January 2015

Bala Hota ,
Brian Harting ,
Robert A. Weinstein ,
Rosie D. Lyles ,
Susan C. Bleasdale ,
William Trick  and
Centers for Disease Control and Prevention Epicenters
Bala Hota*
Affiliation:
John H. Stroger, Jr, Hospital of Cook County, Illinois Rush University Medical Centers, Illinois
Brian Harting
Affiliation:
Rush University Medical Centers, Illinois
Robert A. Weinstein
Affiliation:
John H. Stroger, Jr, Hospital of Cook County, Illinois Rush University Medical Centers, Illinois
Rosie D. Lyles
Affiliation:
John H. Stroger, Jr, Hospital of Cook County, Illinois
Susan C. Bleasdale
Affiliation:
Chicago, and Northwest Suburban Medical Associates, Arlington Heights, Illinois
William Trick
Affiliation:
John H. Stroger, Jr, Hospital of Cook County, Illinois
*
1900 S Polk, Room 1248, Chicago, IL, 60612 (bhota@rush.edu)
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Extract

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.

Design.

Criterion standard.

Setting.

John H. Stroger, Jr, Hospital of Cook County, a 464-bed public hospital in Chicago, Illinois.

Participants.

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.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 31 , Issue 1 , January 2010 , pp. 4 - 11
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2010

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