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Published on: August 1, 2019
The effect of requesting a reason for non-adherence to a guideline in a long running automated reminder system for
Fabian O Kooij1, Toni Klok, Benedikt Preckel
1Fabian O. Kooij, Academic Medical Centre, University of Amsterdam, Department of anaesthesia, PO Box 22660, 1100 DD Amsterdam, Phone: +31 20 566 2533, Fax: +31 20 697 9441,
Background:
Automated reminders are employed frequently to improve guideline adherence, but limitations of automated reminders are becoming more apparent. We studied the reasons for non-adherence in the setting of automated reminders to test the hypothesis that a separate request for a reason in itself may further improve guideline adherence.
Methods:
In a previously implemented automated reminder system on prophylaxis for postoperative nausea and vomiting (PONV), we included additional automated reminders requesting a reason for non-adherence. We recorded these reasons in the pre-operative screening clinic, the OR and the PACU. We compared adherence to our PONV guideline in two study groups with a historical control group.
Results:
Guideline adherence on prescribing and administering PONV prophylaxis (dexamethasone and granisetron) all improved compared to the historical control group (89 vs. 82% (p< 0.0001), 96 vs 95% (not significant) and 90 vs 82% (p<0.0001)) while decreasing unwarranted prescription for PONV prophylaxis (10 vs. 13 %). In the pre-operative screening clinic, the main reason for not prescribing PONV prophylaxis was disagreement with the risk estimate by the decision support system. In the OR/PACU, the main reasons for not administering PONV prophylaxis were: 'unintended non-adherence' and 'failure to document'.
Conclusions:
In this study requesting a reason for non-adherence is associated with improved guideline adherence. The effect seems to depend on the underlying reason for non-adherence. It also illustrates the importance of human factors principles in the design of decision support. Some reasons for non-adherence may not be influenced by automated reminders.
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