Katoo M Muylle1, Kristof Gentens2, Alain G Dupont3, Pieter Cornu4. 1. Research Group Clinical Pharmacology & Clinical Pharmacy (KFAR), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Laarbeeklaan 103, 1090 Brussels, Belgium. Electronic address: Katoo.Muylle@vub.be. 2. Department of Medical Informatics, UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium. Electronic address: Kristof.Gentens@uzbrussel.be. 3. Research Group Clinical Pharmacology & Clinical Pharmacy (KFAR), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Laarbeeklaan 103, 1090 Brussels, Belgium. Electronic address: Alain.Dupont@vub.be. 4. Research Group Clinical Pharmacology & Clinical Pharmacy (KFAR), Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Laarbeeklaan 103, 1090 Brussels, Belgium; Department of Medical Informatics, UZ Brussel, Laarbeeklaan 101, 1090 Brussels, Belgium. Electronic address: Pieter.Cornu@vub.be.
Abstract
OBJECTIVE: Evaluation of the effect of six optimization strategies in a clinical decision support system (CDSS) for drug-drug interaction (DDI) screening on alert burden and alert acceptance and description of clinical pharmacist intervention acceptance. METHODS: Optimizations in the new CDSS were the customization of the knowledge base (with addition of 67 extra DDIs and changes in severity classification), a new alert design, required override reasons for the most serious alerts, the creation of DDI-specific screening intervals, patient-specific alerting, and a real-time follow-up system of all alerts by clinical pharmacists with interventions by telephone was introduced. The alert acceptance was evaluated both at the prescription level (i.e. prescription acceptance, was the DDI prescribed?) and at the administration level (i.e. administration acceptance, did the DDI actually take place?). Finally, the new follow-up system was evaluated by assessing the acceptance of clinical pharmacist's interventions. RESULTS: In the pre-intervention period, 1087 alerts (92.0 % level 1 alerts) were triggered, accounting for 19 different DDIs. In the post-intervention period, 2630 alerts (38.4 % level 1 alerts) were triggered, representing 86 different DDIs. The relative risk forprescription acceptance in the post-intervention period compared to the pre-intervention period was 4.02 (95 % confidence interval (CI) 3.17-5.10; 25.5 % versus 6.3 %). The relative risk for administration acceptance was 1.16 (95 % CI 1.08-1.25; 54.4 % versus 46.7 %). Finally, 86.9 % of the clinical pharmacist interventions were accepted. CONCLUSION: Six concurrently implemented CDSS optimization strategies resulted in a high alert acceptance and clinical pharmacist intervention acceptance. Administration acceptance was remarkably higher than prescription acceptance.
OBJECTIVE: Evaluation of the effect of six optimization strategies in a clinical decision support system (CDSS) for drug-drug interaction (DDI) screening on alert burden and alert acceptance and description of clinical pharmacist intervention acceptance. METHODS: Optimizations in the new CDSS were the customization of the knowledge base (with addition of 67 extra DDIs and changes in severity classification), a new alert design, required override reasons for the most serious alerts, the creation of DDI-specific screening intervals, patient-specific alerting, and a real-time follow-up system of all alerts by clinical pharmacists with interventions by telephone was introduced. The alert acceptance was evaluated both at the prescription level (i.e. prescription acceptance, was the DDI prescribed?) and at the administration level (i.e. administration acceptance, did the DDI actually take place?). Finally, the new follow-up system was evaluated by assessing the acceptance of clinical pharmacist's interventions. RESULTS: In the pre-intervention period, 1087 alerts (92.0 % level 1 alerts) were triggered, accounting for 19 different DDIs. In the post-intervention period, 2630 alerts (38.4 % level 1 alerts) were triggered, representing 86 different DDIs. The relative risk forprescription acceptance in the post-intervention period compared to the pre-intervention period was 4.02 (95 % confidence interval (CI) 3.17-5.10; 25.5 % versus 6.3 %). The relative risk for administration acceptance was 1.16 (95 % CI 1.08-1.25; 54.4 % versus 46.7 %). Finally, 86.9 % of the clinical pharmacist interventions were accepted. CONCLUSION: Six concurrently implemented CDSS optimization strategies resulted in a high alert acceptance and clinical pharmacist intervention acceptance. Administration acceptance was remarkably higher than prescription acceptance.
Authors: Greet Van De Sijpe; Charlotte Quintens; Karolien Walgraeve; Eva Van Laer; Jens Penny; Greet De Vlieger; Rik Schrijvers; Paul De Munter; Veerle Foulon; Minne Casteels; Lorenz Van der Linden; Isabel Spriet Journal: BMC Med Inform Decis Mak Date: 2022-02-22 Impact factor: 2.796
Authors: Arthur T M Wasylewicz; Britt W M van de Burgt; Thomas Manten; Marieke Kerskes; Wilma N Compagner; Erik H M Korsten; Toine C G Egberts; Rene J E Grouls Journal: Clin Pharmacol Ther Date: 2022-06-27 Impact factor: 6.903