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Int J Clin Pharm ; 40(5): 1225-1233, 2018 Oct.
Article in English | MEDLINE | ID: mdl-29785684

ABSTRACT

Background A clinical decision support system (CDSS) linked to the computerized physician order entry may help improve prescription appropriateness in inpatients with renal insufficiency. Objective To evaluate the impact on prescription appropriateness of a CDSS prescriber alert for 85 drugs in renal failure patients. Setting Before-after study in a 975-bed academic hospital. Method Prescriptions of patients with renal failure were reviewed during two comparable periods of 6 days each, before and after the implementation of the CDSS (September 2009 and 2010). Main outcome measure The proportion of inappropriate dosages of 85 drugs included in the CDSS was compared in the pre- and post-implementation group. Results Six hundred and fifteen patients were included in the study (301 in pre- and 314 in post-implementation periods). In the pre- and post-implementation period, respectively 2882 and 3485 prescriptions were evaluated, of which 14.9 and 16.6% triggered an alert. Among these, the dosage was inappropriate in respectively 25.4 and 24.6% of prescriptions in the pre- and post-implementation periods (OR 0.97; 95% CI 0.72-1.29). The most frequently involved drugs were paracetamol, perindopril, tramadol and allopurinol. Conclusion The implementation of a CDSS did not significantly reduce the proportion of inappropriate drug dosages in patients with renal failure. Further research is required to investigate the reasons why prescribers override alerts. Collaboration with clinical pharmacists might improve compliance with the CDSS recommendations.


Subject(s)
Decision Support Systems, Clinical , Inappropriate Prescribing/prevention & control , Medical Order Entry Systems , Renal Insufficiency/complications , Aged , Aged, 80 and over , Dose-Response Relationship, Drug , Drug Therapy, Computer-Assisted , Female , Humans , Male , Middle Aged , Pharmaceutical Preparations/administration & dosage , Practice Patterns, Physicians'/standards , Practice Patterns, Physicians'/statistics & numerical data
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