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Medication stewardship using computerized clinical decision support: A case study on intravenous immunoglobulins
Author(s) -
Tsapepas Demetra,
Der-Nigoghossian Caroline,
Patel Khilna,
Berger Karen,
Vawdrey David K,
Salmasian Hojjat
Publication year - 2019
Publication title -
pharmacology research and perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.975
H-Index - 27
ISSN - 2052-1707
DOI - 10.1002/prp2.508
Subject(s) - medicine , dosing , clinical decision support system , computerized physician order entry , schedule , intensive care medicine , health care , decision support system , computer science , pharmacology , data mining , economics , economic growth , operating system
Background Healthcare delivery organizations face increasing pressure to manage the use of medications in terms of safety, waste reduction, and cost containment. Objective To describe a computerized provider order entry (CPOE) system intervention to optimize use of a commonly ordered, high‐cost therapeutic: intravenous immune globulin (IVIG). Design Description of IVIG order configuration, medication use patterns, and subsequent order set configuration development in a CPOE system. Measurements IVIG orders were extracted from the CPOE system before and after the implementation of a specialty orderset to determine the indications for use, dosing, and duration of therapy. Orders were compared to a theoretical dosing schedule created from published evidence and data from a prior medication use evaluation. Results During 36 months before the implementation of the IVIG order set, 1965 IVIG orders were reviewed. The prescribed IVIG dose varied considerably from the expected dose (mean = −1.8, range = −4.9‐1.5). In the 27 months after order set implementation, 848 IVIG orders were reviewed. The prescribed IVIG dose was closer to the expected dose (mean = −1.2, range = −3.9‐2.6, P  < .0001). Conclusions Order configuration processes are cumbersome and time‐consuming, but can be streamlined to enhance a medication’s usage in the healthcare system. A better understanding of institution‐specific ordering patterns may facilitate more efficient and effective order configuration and optimize drug use.

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