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Publication

Pilot evaluation of an optimized context-specific drug-drug interaction alerting system

Journal Contribution - Journal Article

Subtitle:A controlled pre-post study

OBJECTIVES: Clinical decision support (CDS) systems are frequently used to reduce unwanted drug-drug interactions (DDIs) but often result in alert fatigue. The main objective of this study was to investigate whether a newly developed context-specific DDI alerting system would improve alert acceptance.

METHODS: A controlled pre-post intervention study was conducted in 4 departments in a university hospital. After a 7-month pre-intervention period, the new system was activated in the intervention departments, while the old system remained activated in the control departments. Post-intervention data was collected for a 7-month period.

RESULTS: A significant increase of the overall acceptance rate was observed between the pre- and post-intervention period (2.2% versus 52.4%; p<0.001) for the intervention departments and between the intervention and control departments (2.5% versus 52.4%; p<0.001) in the post-intervention period. There were no significant differences in acceptance rates between the pre- and post-intervention period in the control departments and also not between the control and intervention departments in the pre-intervention period.

CONCLUSIONS: The improvement was probably related to several optimization strategies including the customization of the severity classification, the creation of individual screening intervals, the inclusion of context factors for risk assessment, the new alert design and the creation of a follow-up system. The marked increase in alert acceptance looks promising and should be further evaluated after hospital wide implementation. System aspects that require further optimization were identified and will be developed. Further research is warranted to develop context-aware algorithms for complex class-class interactions.

Journal: Int. J. Med. Inform.
ISSN: 1386-5056
Issue: 9
Volume: 84
Pages: 617-629
Publication year:2015
Keywords:Clinical decision support systems, Drug–drug interactions
CSS-citation score:2