title: Clinical decision support systems differ in their ability to identify clinically relevant drug interactions of immunosuppressants in kidney transplant patients.
abstract: OBJECTIVE
  In kidney transplant patients, clinically relevant drug-drug interactions (DDIs) with immunosuppressants potentially lead to serious adverse drug events (ADEs). The aim of this study was (i) to show that five clinical decision support systems (CDSSs) differ in their ability to identify clinically relevant potential DDIs (pDDIs) of immunosuppressants in kidney transplant patients and (ii) to compare CDSSs in terms of their ability to identify clinically relevant pDDIs in this context.
  
  
  METHODS
  All pDDIs being possible between nine immunosuppressants and 234 comedication drugs were identified for 264 intensive care unit (ICU) kidney transplant patients from 1999 to 2010. For pDDI identification, five CDSSs were used: DRUG-REAX®, ID PHARMA CHECK®, Lexi-Interact, mediQ and Meona. PDDIs from high severity categories were defined as clinically relevant. Classification of pDDIs as clinically relevant/non-clinically relevant by a clinical pharmacist using Stockley's Drug Interactions was employed as benchmark. We analysed inter-rater agreement, sensitivity, specificity, positive predictive value and negative predictive value.
  
  
  CONCLUSIONS
  Clinical decision support systems generated a total of 759 pDDI alerts. A total of 240 pDDI alerts were in high severity categories. A total of 391 different pDDIs were identified. Only 5% (n = 35) of different pDDIs were identified by all CDSSs. A total of 49 pDDIs were classified as clinically relevant by clinical pharmacists' rating using Stockley's Drug Interactions. Meona (0·72) has the highest inter-rater agreement with the benchmark for clinically relevant pDDIs. ID PHARMA CHECK®and mediQ show highest sensitivities (0·74, respectively). Meona has the highest specificity (0·99) and positive predictive value (0·89).
  
  
  CONCLUSIONS
  Five CDSSs differ in their ability to identify clinically relevant pDDIs of immunosuppressants in kidney transplant patients. Data may assist in selecting CDSSs for kidney transplant patients in the ICU. Using CDSSs to identify clinically relevant pDDIs could prevent ADEs and contribute to the overall goal of avoiding patient harm and increasing patient safety.
authors.affiliation: Hospital Pharmacy, University Hospital RWTH Aachen, Aachen, Germany.|Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
authors.forename: J
authors.initials: J
authors.lastname: Amkreutz
authors.affiliation: Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Koch
authors.affiliation: Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
authors.forename: L
authors.initials: L
authors.lastname: Buendgens
authors.affiliation: Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.
authors.forename: C
authors.initials: C
authors.lastname: Trautwein
authors.affiliation: Hospital Pharmacy, University Hospital RWTH Aachen, Aachen, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Eisert
mesh_terms: D020000:Decision Support Systems, Clinical; D004347:Drug Interactions; D006801:Humans; D007166:Immunosuppressive Agents / Q000008:administration & dosage / Q000009:adverse effects*; D007362:Intensive Care Units; D016030:Kidney Transplantation / Q000379:methods*; D010595:Pharmacists; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
chemical_list: D007166:Immunosuppressive Agents
keywords: computerized decision support; drug-drug interactions; evidence-based pharmacotherapy; polypharmacy; renal transplantation