Abstract
BackgroundAdverse drug events are responsible for up to 7% of all admissions to acute care hospitals. At least 58% of these are preventable, resulting from incomplete drug information, prescribing or dispensing errors, and overuse or underuse of medications. Effective implementation of medication reconciliation is considered essential to reduce preventable adverse drug events occurring at transitions between community and hospital care. An electronically enabled discharge reconciliation process represents an innovative approach to this problem.Methods/DesignParticipants will be recruited in Quebec and are eligible for inclusion if they are using prescription medication at admission, covered by the Quebec drug insurance plan, admitted from the community, 18 years or older, admitted to a general or intensive care medical or surgical unit, and discharged alive. A sample size of 3,714 will be required to detect a 5% reduction in adverse drug events. The intervention will comprise electronic retrieval of the community drug list, combined with an electronic discharge reconciliation module and an electronic discharge communication module. The primary outcomes will be adverse drug events occurring 30 days post-discharge, identified by a combination of patient self-report and chart abstraction. All emergency room visits and hospital readmission during this period will be measured as secondary outcomes. A cluster randomization approach will be used to allocate 16 medical and 10 surgical units to electronic discharge reconciliation and communication versus usual care. An intention-to-treat approach will be used to analyse data. Logistic regression will be undertaken within a generalized estimating equation framework to account for clustering within units.DiscussionThe goal of this prospective trial is to determine if electronically enabled discharge reconciliation will reduce the risk of adverse drug events, emergency room visits and readmissions 30 days post-discharge compared with usual care. We expect that this intervention will improve adherence to medication reconciliation at discharge, the accuracy of the community-based drug history and effective communication of hospital-based treatment changes to community care providers. The results may support policy-directed investments in computerizing and training of hospital staff, generate key requirements for future hospital accreditation standards, and highlight functional requirements for software vendors.Trial registrationNCT01179867
Highlights
Adverse drug events are responsible for up to 7% of all admissions to acute care hospitals
The goal of this prospective trial is to determine if electronically enabled discharge reconciliation will reduce the risk of adverse drug events, emergency room visits and readmissions 30 days post-discharge compared with usual care
We expect that this intervention will improve adherence to medication reconciliation at discharge, the accuracy of the community-based drug history and effective communication of hospital-based treatment changes to community care providers
Summary
A major challenge in this study will be to ensure that attending physicians or residents have sufficient training, motivation and support to use the medication reconciliation module for the discharge prescription. If we find that the intervention reduces ADEs, it will support policy-directed quality investments in computerization and training hospital staff to use pharmacy-based records and a discharge reconciliation module to improve medication reconciliation. It will generate key requirements for medication reconciliation that can be applied in future hospital accreditation standards, as well as highlight functional requirements for software vendors. Author details 1Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1020 Pine Avenue West, Montreal, QC H3A 1A2, Canada. Author details 1Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1020 Pine Avenue West, Montreal, QC H3A 1A2, Canada. 2Clinical and Health Informatics Research Group, McGill University, 1140 Pine Avenue West, Montreal, QC H3A 1A3, Canada. 3Department of Medicine, Royal Victoria Hospital, McGill University, 687 Pine Avenue West, Room A3.09, Montreal, QC H3A 1A1, Canada. 4Ottawa Hospital Research Institute, 725 Parkdale Avenue, Ottawa, ON K1Y 4E9, Canada. 5Collège des Médecins du Québec, 2170 Réné-Lévesque Boulevard West, Montreal, QC H3H 2T8, Canada
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