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Observational Study
. 2014 Dec 22;4(12):e005370.
doi: 10.1136/bmjopen-2014-005370.

Long-term effect of computer-assisted decision support for antibiotic treatment in critically ill patients: a prospective 'before/after' cohort study

I Nachtigall  1 , S Tafelski  1 , M Deja  1 , E Halle  2 , M C Grebe  1 , A Tamarkin  1 , A Rothbart  1 , A Uhrig  3 , E Meyer  4 , L Musial-Bright  5 , K D Wernecke  6 , C Spies  1
Affiliations
Observational Study

Long-term effect of computer-assisted decision support for antibiotic treatment in critically ill patients: a prospective 'before/after' cohort study

I Nachtigall et al. BMJ Open. .

Abstract

Objectives: Antibiotic resistance has risen dramatically over the past years. For individual patients, adequate initial antibiotic therapy is essential for clinical outcome. Computer-assisted decision support systems (CDSSs) are advocated to support implementation of rational anti-infective treatment strategies based on guidelines. The aim of this study was to evaluate long-term effects after implementation of a CDSS.

Design: This prospective 'before/after' cohort study was conducted over four observation periods within 5 years. One preinterventional period (pre) was compared with three postinterventional periods: directly after intensive implementation efforts (post1), 2 years (post2) and 3 years (post3) after implementation.

Setting: Five anaesthesiological-managed intensive care units (ICU) (one cardiosurgical, one neurosurgical, two interdisciplinary and one intermediate care) at a university hospital.

Participants: Adult patients with an ICU stay of >48 h were included in the analysis. 1316 patients were included in the analysis for a total of 12,965 ICU days.

Intervention: Implementation of a CDSS.

Outcome measures: The primary end point was percentage of days with guideline adherence during ICU treatment. Secondary end points were antibiotic-free days and all-cause mortality compared for patients with low versus high guideline adherence.

Main results: Adherence to guidelines increased from 61% prior to implementation to 92% in post1, decreased in post2 to 76% and remained significantly higher compared with baseline in post3, with 71% (p=0.178). Additionally, antibiotic-free days increased over study periods. At all time periods, mortality for patients with low guideline adherence was higher with 12.3% versus 8% (p=0.014) and an adjusted OR of 1.56 (95% CI 1.05 to 2.31).

Conclusions: Implementation of computerised regional adapted guidelines for antibiotic therapy is paralleled with improved adherence. Even without further measures, adherence stayed high for a longer period and was paralleled by reduced antibiotic exposure. Improved guideline adherence was associated with reduced ICU mortality.

Trial registration number: ISRCTN54598675.

Keywords: Antibiotic therapy; Computer-assisted decision support systems; Evidence based medicine; Stewardship program.

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Figures

Figure 1
Figure 1
Presentation of different user interfaces in the computerised decision support program (available at http://www.dgai-abx.de/en/). (A) Summary of infection characteristics; (B) selection menu in the module resistance patterns and targeted therapy; (C) selection menu in the antibiotic agents module. BAL, bronchoalveolar lavage; CPIS, Clinical Pulmonary Infection Score; MRSA, methicillin-resistant Staphylococcus aureus; VAP, ventilator-associated pneumonia.
Figure 1
Figure 1
Continued.
Figure 2
Figure 2
Adherence to guideline and percentage of antibiotic free days over study periods. MSSA, methicillin-susceptible Staphylococcus aureus; MRSA, methicillin-resistant Staphylococcus aureus; S. epidermidis Staphylococcus epidermidis.
See this image and copyright information in PMC

References

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