Abstract
Background
Clinical decision support software (CDSS) solutions can automatically identify drug interactions and thereby aim to improve drug safety. However, data on the comparative performance of different CDSS to detect and appropriately classify interactions in real-life prescription datasets is limited.
Objective
The aim of this study was to compare the results from two different CDSS analysing the pharmacotherapy of a large population of psychiatric inpatients for drug interactions.
Methods
We performed mass analyses of cross-sectional patient-level prescriptions from 84,625 psychiatric inpatients using two CDSS – MediQ and ID PHARMA CHECK®. Interactions with the highest risk ratings and the most frequent ratings were reclassified according to the Zurich Interaction System (ZHIAS), a multidimensional classification that incorporates the OpeRational ClassificAtion of Drug Interactions (ORCA) and served as a reference standard.
Results
MediQ reported 6,133 unique interacting combinations responsible for 270,617 alerts affecting 63,454 patients. ID PHARMA CHECK® issued 5,400 interactions and 157,489 alerts in 48,302 patients. Only 2,154 unique interactions were identified by both programmes, but overlap increased with higher risk rating. MediQ reported high-risk interactions in 2.5 % of all patients, compared with 5 % according to ID PHARMA CHECK®. The positive predictive value for unique major alerts to be (provisionally) contraindicated according to ORCA was higher for MediQ (0.63) than for either of the two ID PHARMA CHECK® components (0.42 for hospINDEX and 0.30 for ID MACS). MediQ reported more interactions, and ID PHARMA CHECK® tended to classify interactions into a higher risk class, but overall both programmes identified a similar number of (provisionally) contraindicated interactions according to ORCA criteria. Both programmes identified arrhythmia as the most frequent specific risk associated with interactions in psychiatric patients.
Conclusions
CDSS can be used for mass-analysis of prescription data and thereby support quality management. However, in clinical practice CDSS impose an overwhelming alert burden on the prescriber, and prediction of clinical relevance remains a major challenge. Only a small subset of yet to be determined alerts appears suitable for automated display in clinical routine.
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Acknowledgments
The authors would like to thank Eveline Jaquenoud Sirot, MediQ, Aargau, Switzerland, and ID Berlin GmbH & Co. KGAA, Berlin, Germany/ID Suisse AG, St. Gallen, Switzerland, for their support of mass analyses for interactions using MediQ and ID PHARMA CHECK®. The current study was supported by unrestricted grants to Stefan Russmann from the Swiss Society of Drug Safety in Psychiatry (SGAMSP) and the Hartmann-Müller Foundation for Medical Research, Zurich, Switzerland. Stefan Russmann provided financial compensation to MediQ and ID Berlin for the use of their software and services. The manuscript was made available to MediQ and ID Berlin before submission, but neither MediQ nor ID PHARMA CHECK® had any influence on the study design, analysis or interpretation of the results. After completion of the presented study Stefan Russmann negotiated research support with ID Berlin for the conduct of future studies using ID PHARMA CHECK®, but the current study was not funded by ID Berlin. All authors declare that no conflicts of interest influenced the present study. Renate Grohmann is a member of the project management team of AMSP. The AMSP Drug Safety Programme is organized by non-profit associations in Germany, Austria and Switzerland. Almost all pharmaceutical companies involved in CNS research contribute financial support to the three associations.
Educational and Research Grants Since 1993
Austrian companies: Astra Zeneca Österreich GmbH, Boehringer Ingelheim Austria, Bristol Myers Squibb GmbH, CSC Pharmaceuticals GmbH, Eli Lilly GmbH, Germania Pharma GmbH, GlaxoSmithKline Pharma GmbH, Janssen-Cilag Pharma GmbH, Lundbeck GmbH, Novartis Pharma GmbH, Pfizer Med Inform, Wyeth Lederle Pharma GmbH.
German companies: Abbott GmbH & Co. KG, AstraZeneca GmbH, Aventis Pharma Deutschland GmbH GE-O/R/N, Bayer Vital GmbH & Co. KG, Boehringer Mannheim GmbH, Bristol-Myers-Squibb, Ciba Geigy GmbH, Desitin Arzneimittel GmbH, Duphar Pharma GmbH & Co. KG, Eisai GmbH, Esparma GmbH Arzneimittel, GlaxoSmithKline Pharma GmbH & Co. KG, Hoffmann-La Roche AG Medical Affairs, Janssen-Cilag GmbH, Janssen Research Foundation, Knoll Deutschland GmbH, Lilly Deutschland GmbH Niederlassung Bad Homburg, Lundbeck GmbH & Co. KG, Novartis Pharma GmbH, Nordmark Arzneimittel GmbH, Organon GmbH, Otsuka-Pharma Frankfurt, Pfizer GmbH, Pharmacia & Upjohn GmbH, Promonta Lundbeck Arzneimittel, Rhone-Poulenc Rohrer, Sanofi-Synthelabo GmbH, Sanofi-Aventis Deutschland, Schering AG, SmithKline Beecham Pharma GmbH, Solvay Arzneimittel GmbH, Synthelabo Arzneimittel GmbH, Dr. Wilmar Schwabe GmbH & Co., Thiemann Arzneimittel GmbH, Troponwerke GmbH & Co. KG, Upjohn GmbH, Wander Pharma GmbH, Wyeth-Pharma GmbH.
Swiss companies: AHP (Schweiz) AG, AstraZeneca AG, Bristol-Myers, Squibb AG, Desitin Pharma GmbH, Eli Lilly (Suisse) S.A., Essex Chemie AG, GlaxoSmithKline AG, Janssen-Cilag AG, Lundbeck (Suisse) AG, Mepha Pharma AG, Organon AG, Pfizer AG, Pharmacia, Sanofi-Aventis (Suisse) S.A., Sanofi-Synthélabo SA, Servier SA, SmithKlineBeecham AG, Solvay Pharma AG, Wyeth AHP (Suisse) AG, Wyeth Pharmaceuticals AG.
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Zorina, O.I., Haueis, P., Greil, W. et al. Comparative Performance of Two Drug Interaction Screening Programmes Analysing a Cross-Sectional Prescription Dataset of 84,625 Psychiatric Inpatients. Drug Saf 36, 247–258 (2013). https://doi.org/10.1007/s40264-013-0027-9
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DOI: https://doi.org/10.1007/s40264-013-0027-9