Oral quinolones in hospitalized patients: an evaluation of a computerized decision support intervention
T Hulgan, ST Rosenbloom, F Hargrove… - Journal of internal …, 2004 - Wiley Online Library
Journal of internal medicine, 2004•Wiley Online Library
Objective. To determine whether a computerized decision support system could increase the
proportion of oral quinolone antibiotic orders placed for hospitalized patients. Design.
Prospective, interrupted time‐series analysis. Setting. University hospital in the south‐
eastern United States. Subjects. Inpatient quinolone orders placed from 1 February 2001 to
31 January 2003. Intervention. A web‐based intervention was deployed as part of an
existing order entry system at a university hospital on 5 February 2002. Based on an …
proportion of oral quinolone antibiotic orders placed for hospitalized patients. Design.
Prospective, interrupted time‐series analysis. Setting. University hospital in the south‐
eastern United States. Subjects. Inpatient quinolone orders placed from 1 February 2001 to
31 January 2003. Intervention. A web‐based intervention was deployed as part of an
existing order entry system at a university hospital on 5 February 2002. Based on an …
Abstract
Objective. To determine whether a computerized decision support system could increase the proportion of oral quinolone antibiotic orders placed for hospitalized patients.
Design. Prospective, interrupted time‐series analysis.
Setting. University hospital in the south‐eastern United States.
Subjects. Inpatient quinolone orders placed from 1 February 2001 to 31 January 2003.
Intervention. A web‐based intervention was deployed as part of an existing order entry system at a university hospital on 5 February 2002. Based on an automated query of active medication and diet orders, some users ordering intravenous quinolones were presented with a suggestion to consider choosing an oral formulation.
Main outcome measure. The proportion of inpatient quinolone orders placed for oral formulations before and after deployment of the intervention.
Results. There were a total of 15 194 quinolone orders during the study period, of which 8962 (59%) were for oral forms. Orders for oral quinolones increased from 4202 (56%) before the intervention to 4760 (62%) after, without a change in total orders. In the time‐series analysis, there was an overall 5.6% increase (95% CI 2.8–8.4%; P < 0.001) in weekly oral quinolone orders due to the intervention, with the greatest effect on nonintensive care medical units.
Conclusions. A web‐based intervention was able to increase oral quinolone orders in hospitalized patients. This is one of the first studies to demonstrate a significant effect of a computerized intervention on dosing route within an antibiotic class. This model could be applied to other antibiotics or other drug classes with good oral bioavailability.
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