Difference between revisions of "Long-term effect of computer-assisted decision support for antibiotic treatment in critically ill patients: a prospective ‘before/after’ cohort study"
| Line 13: | Line 13: | ||
| − | The authors in this article performed a prospective cohort study to determine whether a CDSS can have positive adherence in an ICU surgical setting. The team hypothesized that implementation of the CDSS for antibiotic therapy should decrease antibiotic use over time and improve clinical outcome. | + | The authors in this article performed a prospective cohort study to determine whether a CDSS can have positive adherence in an [http://en.wikipedia.org/wiki/Intensive_care_unit ICU] surgical setting. The team hypothesized that implementation of the CDSS for antibiotic therapy should decrease antibiotic use over time and improve clinical outcome. |
== Methods == | == Methods == | ||
| − | This prospective cohort study was conducted as a clinical prospective pre-intervention/post-intervention study over four evaluation time periods within 5 years totaling 12,965 patient days in the ICU. <ref name=" Nachtigall et al 2014"></ref> | + | This prospective cohort study was conducted as a clinical prospective pre-intervention/post-intervention study over four evaluation time periods within 5 years totaling 12,965 patient days in the [http://en.wikipedia.org/wiki/Intensive_care_unit ICU]. <ref name=" Nachtigall et al 2014"></ref> |
During the pre-intervention period, every ward physician was given paper-based guidelines for antibiotic therapy. In contrast, during the post-intervention period, the CDSS for antibiotic therapy was implemented as a tool on every hospital computer. For every infection included in the CDSS, there is one main five-step algorithm. <ref name=" Nachtigall et al 2014"></ref> | During the pre-intervention period, every ward physician was given paper-based guidelines for antibiotic therapy. In contrast, during the post-intervention period, the CDSS for antibiotic therapy was implemented as a tool on every hospital computer. For every infection included in the CDSS, there is one main five-step algorithm. <ref name=" Nachtigall et al 2014"></ref> | ||
Revision as of 05:40, 24 February 2015
This is a review of Nachtigall, Tafelski, Deja, Halle, Grebe, Tamarkin and Spies 2014 article, Long-term effect of computer-assisted decision support for antibiotic treatment in critically ill patients: a prospective ‘before/after’ cohort study.[1]
Introduction
Antibiotic resistance has become a major health concern all over the world. Much of the problem can be traced back to misuse and wrong administration of antibiotics.
When antibiotics don’t work, the result can be:[2]
- Longer illnesses
- More complicated illnesses
- More doctor visits
- The use of stronger and more expensive drugs
- More deaths caused by bacterial infections
The authors in this article performed a prospective cohort study to determine whether a CDSS can have positive adherence in an ICU surgical setting. The team hypothesized that implementation of the CDSS for antibiotic therapy should decrease antibiotic use over time and improve clinical outcome.
Methods
This prospective cohort study was conducted as a clinical prospective pre-intervention/post-intervention study over four evaluation time periods within 5 years totaling 12,965 patient days in the ICU. [1]
During the pre-intervention period, every ward physician was given paper-based guidelines for antibiotic therapy. In contrast, during the post-intervention period, the CDSS for antibiotic therapy was implemented as a tool on every hospital computer. For every infection included in the CDSS, there is one main five-step algorithm. [1]
References
- ↑ 1.0 1.1 1.2 Nachtigall, I., Tafelski, S., Deja, M., Halle, E., Grebe, M. C., Tamarkin, A., … Spies, C. (2014). Long-term effect of computer-assisted decision support for antibiotic treatment in critically ill patients: a prospective “before/after” cohort study. BMJ Open, 4(12), e005370. doi:10.1136/bmjopen-2014-005370
- ↑ http://www.fda.gov/ForConsumers/ConsumerUpdates/ucm092810.htm
