Real-time Decision Support for Postoperative Nausea and Vomiting (PONV) Prophylaxis

The purpose of this study is to determine how automated recommendations are best presented to optimize the adherence to guidelines on prophylaxis for nausea and vomiting after surgery.

Nausea and vomiting after surgery (PONV) is a common side effect of the surgical procedure, general anesthesia and opioid use occurring in about one third of patients. In addition to being very unpleasant for patients, it is associated with longer recovery room stays and increased costs. Much research has been done on prophylactic interventions that may be applied during the surgical procedure to prevent PONV. Current national guidelines recommend that a risk score is used to decide on the number of prophylactic interventions to administer to a patient. Based on specific characteristics of individual patients and the procedures that they are about to undergo, such a risk score predicts the risk of PONV for each individual. According to the national guidelines, patients with higher risks of PONV should receive more prophylactic interventions. However, in a busy operating room where the anesthesia provider performs multiple patient care tasks, closely following the recommendations to minimize the risk of PONV is often difficult. Computers may help anesthesia providers to adhere to best practices for PONV prevention by providing so-called decision support. A decision support system for PONV automatically calculates the risk of PONV for an individual patient and presents this predicted risk to the anesthesia provider on the computer screen that is being used by the anesthesia team for record keeping. In recent studies, such decision support systems have been demonstrated to improve adherence to PONV guidelines, especially when a recommendation on the number of interventions is added to the predicted risk. However, in these studies there was still quite some room for improvement of the adherence to PONV guidelines. In general, implementation science is only beginning to understand how such decision support systems are best used to improve medical decision making and minimize practice variations among providers. Further study of how the design of decision support systems impacts the decision making of healthcare providers is therefore warranted. In this proposed study, the investigators will implement several decision support elements for PONV that aim to help anesthesia providers to adhere to the departmental PONV guidelines during the anesthetic case. The study consists of three phases. The first phase is the preintervention phase - i.e. before the decision support has been implemented. The second phase is the first intervention phase with one CDSS feature added. The third phase is the second intervention phase with another CDSS feature added. The decision support elements will provide information about the patient's predicted risk of PONV and the number of prophylactic interventions that the departmental guidelines recommend based on that risk. We will start with preoperative email notifications, followed by an element within the anesthesia information management system (AIMS) that are displayed around the start and end of the procedure. All forms of decision support only provide recommendations. The anesthesia provider is free to act on the message or ignore the notifications. The investigators will compare the adherence to PONV guidelines and the actual occurrence of PONV (both nausea and emetic events: vomiting and retching) in the post-anesthesia care unit (PACU) between all study phases and between the different interventions. The goal of the comparison is to evaluate which decision support elements have an added value to optimize guideline adherence for PONV prophylaxis.

Decision support, Prediction models, PONV, prophylaxis, Decision Support Systems, Clinical, Decision Support Techniques

Automated recommendations on PONV prophylaxis provided to anesthesia providers through the anesthesia information management system and email.

The first notification is the main notification that informs the anesthesia providers at the start of anesthesia of the risk score for that individual patient and the recommended number of prophylactic interventions. The notification occurs within the anesthesia information management system (AIMS)

The second notification within the AIMS will notify the anesthesia providers at the start of surgery when no prophylaxis has been given while three or more interventions were recommended.

A recommendation on PONV prophylaxis to anesthesia providers through email at the Vanderbilt University Medical Center.

A notification will remind anesthesia providers at the closing of surgery how many prophylactic interventions are required to adhere to the recommended number of interventions.

The data warehouse that is used to gather perioperative data and create user reports. In this instance the PDW will be used to send the preoperative emails.

PONV guideline adherence: percentage of patients who received the exact number of prophylactic interventions for PONV that were recommended by the decision support.

A specific time frame on the day of surgery: the start of admission at the holding room to the end of the anesthetic case

The occurrence of PONV, as defined by the administration of antiemetics in the PACU between admission to PACU and discharge from PACU.

the absolute number of prophylactic interventions applied between the admission of the patient in the holding room until admission to the PACU.

A specific time frame on the day of surgery: from the start of admission at the holding room to the end of the anesthetic case

A specific time frame on the day of surgery: from the start of admission to the PACU to discharge from the PACU

Inclusion Criteria: All adult patients (18 years and older) that are scheduled for an elective surgical procedure under general anesthesia Exclusion Criteria: Patients undergoing emergency surgery or organ transplantation Patients that are transferred directly to the Intensive Care Unit after the end of the procedure Patients that die intraoperatively Procedures that only require a sedative level of anesthesia