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Utilization of computerized clinical decision support for potentially inappropriate medications

Authors Alagiakrishnan K, Ballermann M, Rolfson D, Mohindra K, Sadowski CA, Ausford A, Romney J, Hayward RS

Received 31 October 2018

Accepted for publication 6 March 2019

Published 29 April 2019 Volume 2019:14 Pages 753—762


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Richard Walker

K Alagiakrishnan,1 M Ballermann,2 D Rolfson,1 K Mohindra,3 CA Sadowski,4 A Ausford,5 J Romney,6 RS Hayward7

1Division of Geriatric Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada; 2Chief Medical Information Office, Alberta Health Services, Division of Critical Care Medicine, University of Alberta, Edmonton, Alberta, Canada; 3OpTime OR and Anesthesia, Connect Care, Information Systems, Alberta Health Services, Edmonton, Alberta, Canada; 4Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada; 5Department of Family Medicine, University of Alberta, Edmonton, Alberta, Canada; 6Division of Endocrinology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada; 7Division of Internal Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada

Background: Electronic medical record (EMR) alerts may inform point of care decisions, including the decision to prescribe potentially inappropriate medications (PIM) identified in the Beers criteria. EMR alerts may not be considered relevant or informative in the clinician context, leading to a phenomenon colloquially known as “alert fatigue.”
Objective: To assess the frequency of clinical interaction with EMR alerts and associated deprescribing behaviors in ambulatory settings.
Methods: This is a retrospective observational study in two ambulatory clinics (the Kaye Edmonton Clinic Senior’s Clinic and the Lynnwood Family Practice Clinic) in Edmonton over an observational period of 30 months. Statistical analysis was done using descriptive statistics, chi-square and regression analysis.
Results: The reminder performance for interactions with the alert was 17.2% across the two clinics. The Number Needed to Remind (NNR) or mean number of alerts shown on clinician screens prior to a single interaction of any kind with the alert was 5.8. When actions were defined as a deprescribing (ie discontinuation) event that was related to the alert and that particular interaction in the EMR, the reminder performance was 1.2%, for an NNR of 82.8.
Conclusion: The configuration of alerts in the EMR was not associated with a clinically detectable increase in the uptake of the Beers criteria for high hazard medications.

Keywords: polypharmacy, Beers Criteria, deprescribing, best practice advisory, alert fatigue, e-prescribing, prescribing

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