A Clinical Decision Support System Powered by EHR Data Analysis Could Improve PONV Outcomes

Incorporating data analysis from their institution’s electronic health records (EHRs), researchers at the University of California, Los Angeles Medical Center developed a clinical decision support (CDS) system that helped improve perioperative outcomes for patients who experience postoperative nausea and vomiting (PONV), according to a poster presentation.

John Shin, MD, an anesthesiologist at UCLA Medical Center, and his colleagues found that a decision analysis support system based on EHR data allowed for a better patient-specific feedback reporting system. The system, which uses data from the center’s own EHR, empowered providers to improve perioperative management of PONV by providing intraoperative real-time guidance for high-risk patients.

Using two years of data from UCLA’s anesthesiology perioperative records, the researchers created a CDS system that provided four primary steps: PONV-specific questions on preoperative forms, preoperative PONV risk alerts, a real-time intraoperative pathway compliance indicator and individualized emailed reports sent to clinical providers on a weekly basis.

The research, presented at the Young Investigators showcase at ANESTHESIOLOGY 2017 (abstract YI01-8), showed that use of the system led to a relative reduction in PONV of 16.1% (95% CI, 12.2%-20%; P<0.001) in all patients and a reduction of 19.7% (95% CI, 15.6%-30.1%; P<0.001) in high-risk patients with three or more Apfel risk factors. In the post-intervention period, a reduction of 10.2 minutes (95% CI, 6.32-14.05; P<0.001) was reported in length of time in the PACU in high-risk inpatient cases.

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