Study to assess the impact of analytics software on operating room controlled substance management and drug diversion

Dominic S Carollo; Andrew P Mullet; Amanda J Hays; Stacey A Fitzgibbons; Heather D Nelkin; Alexandre P Raymond

doi:10.1093/ajhp/zxae013

Study to assess the impact of analytics software on operating room controlled substance management and drug diversion

Am J Health Syst Pharm. 2024 Mar 8:zxae013. doi: 10.1093/ajhp/zxae013. Online ahead of print.

Authors

Dominic S Carollo¹, Andrew P Mullet², Amanda J Hays³, Stacey A Fitzgibbons³, Heather D Nelkin³, Alexandre P Raymond²

Affiliations

¹ Ochsner Clinic Foundation, New Orleans, LA, and The University of Queensland Medical School-Ochsner Clinical School, New Orleans, LA, USA.
² Ochsner Clinic Foundation, New Orleans, LA, USA.
³ Becton, Dickinson, and Company, San Diego, CA, USA.

PMID: 38456350
DOI: 10.1093/ajhp/zxae013

Abstract

Disclaimer: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

Purpose: This study investigated the impact of an advanced analytics software solution in the operating room (OR) on tracking and evaluating controlled substance discrepancies. The authors hypothesized that the software would increase identification of these discrepancies and improve the efficiency of the preexisting manual process.

Methods: In this evaluation comparing data from before to after implementation of the software, data were collected using the preexisting manual process for 50 days before implementation, followed by a 25-day period for acclimation to the new software, and ending with a 49-day postimplementation review period. Data collected included the total number of medication discrepancies, time required for discrepancy review and reconciliation by an OR analyst, types of discrepancies, and number of discrepancies leading to provider audits.

Results: Before implementation of the analytics software, there were 7,635 OR cases with a total of 674 charting discrepancies (8.83 discrepancies per 100 total OR cases) discovered across 439 OR cases. After implementation, there were 7,454 OR cases with a total of 930 charting discrepancies (12.48 discrepancies per 100 total OR cases; P < 0.0001) discovered across 680 OR cases. While discrepancies increased by 38%, the median review time for the OR analyst per case decreased (P < 0.0001) and the percentage of incidents resolved by the OR analyst increased by 14% while the number of cases requiring additional documentation by the provider decreased by 10%.

Conclusion: Implementation of advanced analytics software in the OR significantly increased the number of controlled substance charting discrepancies identified compared to the preimplementation review process while increasing the efficiency of the OR analyst.

Keywords: anesthesiology; controlled substances; drug diversion prevention; operating room; pharmacy analytics.