Automated screening system helps identify cases of unexpected drug diversions

Electronic data from automated drug dispensing carts can help to identify drug diversion by anesthesia care providers, according to a report in the July issue of Anesthesia & Analgesia, official journal of the International Anesthesia Research Society (IARS).

With appropriate follow-up, the automated screening system can help to identify cases of unexpected drug diversion and abuse, reports the paper by Dr. Richard H. Epstein and colleagues of Thomas Jefferson University, Philadelphia.

Automated Data Help Identify Suspicious Activity

The researchers describe their experience with the automated system to detect drug diversions in their anesthesia department over the past four years. The system uses data from automated drug dispensing carts, which record all drugs removed by authorized, logged-in staff members. Each month, transactions involving controlled drugs by anesthesia care providers were downloaded and cross-checked.

The automated system focused on "atypical transactions" by each staff member—for example, drugs withdrawn for patients who had left the operating room. If the number of atypical transactions was unusually high (more than two standard deviations), the records were manually reviewed to assess the likelihood that drug diversion was taking place.

The automated system and subsequent follow-up led to the detection of two anesthesia staff members who were diverting drugs. In both cases, the abuse was previously unsuspected. In one case, the staff member was able to exploit a weakness in the software for the drug dispensing cart. Both staff members eventually admitted to drug diversion and abuse, and entered treatment.

In another two cases, the system was used to assess the likelihood of drug diversion by staff members determined to be using recreational drugs outside of work (for example, after being cited for driving under the influence). In both cases, investigation found no evidence that these personnel were diverting anesthesia drugs. Those staff members also entered substance abuse treatment.

In a fifth case, the automated system found a high rate of atypical transactions by another staff member not previously suspected of substance abuse. Further investigation concluded that the problem was not drug diversion and abuse but part of a pattern of careless recordkeeping. The staff member received counseling on the need to improve recordkeeping habits. This was the only "false positive" result, and the only case in which a problem flagged by the automated system could not be explained by a quick review of the records.

Though relatively uncommon, diversion and abuse of drugs by staff is a major problem for health care institutions. Electronic drug dispensing carts and other technology provide new approaches to detecting possible diversion of controlled substances in anesthesia departments.

The new experience validates the use of the automated screening approach for detecting drug diversion, the researchers conclude. The system performs well in identifying unsuspected drug diversion, or in investigating diversion by staff members found to have substance abuse problems outside the workplace.

Dr. Epstein and coauthors emphasize that the system is only a screening tool, "and should not be used as the sole indicator for an intervention." As illustrated by the "case in which an apparent problem was related to recordkeeping rather than drug diversion, a graded response is indicated—based on the strength of the evidence after formal investigation.