Using Analytics to Detect Diversion

This is the eighth in a series of posts about drug diversion.

Analytics software tied to automated medication dispensing systems is often used to detect drug diversion in hospitals. It can reduce the time needed to audit clinician transactions at the cabinets, and facilitates documentation of suspected diversion. By shortening the time it takes to detect a diversion incident, analytics tools help reduce risks to patients and the institution that can be caused by diverters.

Of course using analytics is only one component of a robust diversion prevention program. Future diversion posts will discuss ways to develop a comprehensive diversion program at your institution. In this post we provide an overview of how Omnicell Pandora® analytics software works as a diversion monitoring tool.

Analyzing Anomalous Usage

The Anomalous Usage report that appears on the Pandora dashboard is the starting point for diversion monitoring. It shows statistical outliers for usage. You can quickly see if some clinicians have removed a significantly higher quantity of a particular medication compared with their peers on the unit.

DiversionBlog8-AnomUsage-Vertical bar graph

By clicking on the graph, individual names associated with the quantities removed appear.

DiversionBlog8-AnomUsage-Horizontal bar graph

From here, the Pandora user can click on a person’s name to see a User Detail report, which shows transactions by medication during a specific time period, organized by unit.

To further aid in analyzing the situation, an Activity Report shows all of a user’s transactions for a particular medication during a specified time period. This aids the reviewer in spotting unusual activity.

For example, you may notice that users have high dispenses for a particular medication and that they try to cover it up by dispensing smaller doses frequently, or by switching between cabinets for doses administered.  For other examples of diversion tactics to look out for, see our previous posts covering the Top 10 Tricks Diverters Use to Steal Medications Part 1 and Part 2.

DiversionBlog8-Activity Report-Cropped-1600px

Witness Buddy Report

Another Pandora tool is the Witness Buddy report, which aids in identifying nurses who are frequently witnessing waste with a particular colleague. In some cases the witness is participating in the diversion scheme unwittingly. For example, a diverter intent on stealing waste may choose a newer staff member or a more submissive individual who will sign off on waste without actually witnessing the waste process.

New Diversion Course

Omnicell has recently introduced a new online course called “Reading Pandora Surveillance Reports – Anomalous Usage Report Workflow.” The online module is available to Omnicell customers via our customer portal and is also available via HealthStream. It takes about 30 minutes to complete. (Current Omnicell customers can register for myOmnicell here.)

The course includes a brief overview of drug diversion, covering topics such as the physical and behavioral signs of drug misuse, and red flags to look out for based on some common methods used to divert drugs. The remainder of the course guides the user through interpreting the Anomalous Usage and related reports.

Additional Diversion Resources

Diversion Management Webinars: To learn more about diversion, view our series of Diversion Management webinars presented by diversion consultant and educator Kimberly New, JD, BSN, RN.

Training—Omnicell is launching a new two-and-a-half-day classroom course on building a diversion program using OmniCenter® reports and Pandora analytics. The first course launches in June. Learn more on, the customer portal.

Website—Visit our new diversion resource web page:

If you are a Pandora user, share your thoughts on how you use it to monitor diversion at your facility.

Learn what to do when you suspect drug diversion in your facility.

View the previous post on diversion here

2 thoughts on “Using Analytics to Detect Diversion

  1. Data analytics will need to be paired with waste stream verification to close the loop. See


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