(Management Case Study) Implementation of Radio Frequency Identification (RFID) Technology to Optimize Intraoperative Medication Inventory Management

Purpose: Health systems are responsible for managing their medication inventory in a way that optimizes safety, complies with regulatory standards, and minimizes waste to ensure the delivery of high quality patient care. Manual restocking and tracking of medications in anesthesia (AWS) trays is complicated, time intensive, provides several opportunities for error, and lacks perpetual inventory transparency regarding expiration and lot number. This study aimed to determine the impact of RFID technology on restocking non-controlled medications in AWS related to workflow, patient safety from medication errors, restock accuracy and efficiency, and a cost estimation of manual tagging versus purchase of pre-tagged products.

Methods: This study was an experimental design with pre- and post-implementation groups. Interviews with key stakeholders and workflow observations were conducted to assess baseline processes. A stakeholder group including OR pharmacy staff and medication safety representatives identified risk points with the baseline processes. Meetings with OR staff occurred prior to implementation to share information and disseminate best practice for software use. Education sessions on utilizing RFID technology took place for OR pharmacy staff members. Process steps were mapped pre-post-implementation. Randomized AWS tray audits assessed patient safety. AWS tray restocking efficiency was measured through stopwatch studies. One stopwatch study was performed every weeknight spanning Monday through Friday, for a total of five occurrences. Following the stopwatch studies of the restocking process, a pharmacy intern returned to five ORs and audited the AWS trays for accuracy. The ORs were randomly selected using a computer generator prior to the stopwatch study. However, every AWS tray containing non-controlled medications involved in the stopwatch study was audited at least once during this period. The intern made note of outdated medications in addition to medications not stored in the correct locations. Time and costs associated with purchase of manufacturer RFID tagged medications versus manually tagging medications onsite were estimated.

Results: Prior to implementation, manual AWS restocking took 37.9 seconds +/- 24.7 (range 4.6 – 135.9 seconds) compared to 145.9 seconds +/- 50.6 (range 43.4 – 314.3 seconds) after post-implementation. The automated workflow took technicians an average of 108 seconds (1.8 minutes) longer than baseline but reduced the number of technicians required for the workflow from two to one. Restocking errors were reduced by 64.7%, and outdated and missing medication errors were eliminated. No medication errors were formally reported by individuals not involved as investigators for this study using the data collection sheet or the institution’s systems for reporting medication-related errors pre- or post-implementation. Manually applying tags to packages containing 25 vials took 174.8 +/- 19.8 seconds (range 131 to 218 seconds) for smaller vials, compared to 128.1 +/- 21.6 seconds (range 102 to 166 seconds) for larger vials. Manual tag application was also more expensive than pre-purchase of tagged vials.

Conclusion: The implementation of RFID technology in AWS trays decreased errors related to missing and expired non-controlled medications compared to manual processes, reduced the number of technicians needed for restocking trays, and introduced new tracking capabilities for expired or recalled dosage forms. Conversely, automation resulted in increased AWS tray restocking time and increased pharmacy staff and materials costs associated with manual application of RFID tags to individual medications.