Decision support increases guideline adherence for prescribing postoperative nausea and vomiting prophylaxis

Department of Anesthesiology, Onze Lieve Vrouwe Gasthuis, Amsterdam, The Netherlands.
Anesthesia and analgesia (Impact Factor: 3.42). 04/2008; 106(3):893-8, table of contents. DOI: 10.1213/ane.0b013e31816194fb
Source: PubMed

ABSTRACT Guidelines for postoperative nausea and vomiting (PONV) prevention are implemented widely but their effectiveness may be limited by poor adherence. We hypothesized that the use of an electronic decision support (DS) system would significantly improve guideline adherence.
Medical information of all patients undergoing elective surgery in our regional teaching hospital is routinely entered in an anesthesia information management system at the preoperative screening clinic. Our departmental PONV prevention guidelines identifies patients as "high-risk" and thus eligible for PONV prophylaxis based on the presence of at least three of the following risk factors: female gender, history of PONV or motion sickness, nonsmoker status, and anticipated use of postoperative opioids. Using automated reminders, we studied the effect of DS on guidelines adherence using an off-on-off design. In these three study periods, we queried for all consecutive patients visiting the preoperative screening clinic who were eligible for PONV prophylaxis and studied how often it was prescribed correctly.
Between November 2005 and June 2006, 1340, 2715, and 1035 patients were included in the control, DS and post-DS periods, respectively. As a result of mandatory data entry of risk factors, the percentage of high-risk PONV patients increased from 28% in the control period to 32% and 31% in the DS and post-DS periods, respectively. During the control period, 38% of all high-risk patients were prescribed PONV prophylaxis. This increased to 73% during the DS period and decreased to 37% in the post-DS period.
Electronic DS increases guidelines adherence for the prescription of PONV prophylaxis in high-risk PONV patients.

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