Initial observations on the impact of implementation of automated dispensing cabinets for Human Normal Immunoglobulin on data and inventory management
Authors: Pinfield A , Lai K , Jones S 
Published: November 2023

Abstract

Introduction
Human Normal Immunoglobulin (HNIg) is a plasma-derived blood product used to treat a variety of diseases. Global supply problems1 have increased focus on HNIg stewardship, including mandatory recording of HNIg usage on the National Immunoglobulin Database2 (NIgD). This is a dispensary-based process and determines HNIg stock allocation and remuneration. Departmental audits identified significant delays and inconsistencies in data uploaded to NIgD. Inventory management issues caused a number of stock losses in the last financial year. A paper-based HNIg recording system was replaced with the use of Automated Dispensing Cabinets (ADCs). This enabled the development of an electronic ADC batch number report, from dispensing data, that matched fields required for electronic upload to NIgD, making the process more robust and proficient.

Aim
To measure the impact of implementation of ADCs for HNIg on data and inventory management. Objectives included identifying: Percentage of HNIg dispensed uploaded accurately to NIgD within one month of dispensing; Number of HNIg stock adjustments; Staff time required for activities associated with HNIg management.

Methods
Approval was obtained from the Trust Pharmacy Research and Audit Committee. The need for ethical submission was waived. Pre-implementation (May-July 2022) and post-implementation (February-April 2023) HNIg dispensing data was compared to the data uploaded to the NIgD for discrepancies. Electronic inventory reports were generated to identify the number of unexplained stock adjustments made. Time and motion methods were used to observe staff time associated with dispensing, stock management of HNIg in ADCs and data upload activities.

Results
Pre-implementation: 20.7% (3762.5g/18,217g) of HNIg (23.7% of dispensing episodes; 66/279) were inaccurately uploaded or absent on the NIgD and three stock adjustments were made. Post-implementation: 12% (2325g/19,347g) of HNIg (10.8% of dispensing episodes; 31/286) were inaccurately uploaded or absent on the NIgD and zero stock adjustments were observed; Mean time for dispensing HNIg reduced from 17 minutes/prescription to 8 minutes/prescription; Time spent uploading data to NIgD reduced from 5 hours to 1.75 hours/month.

Discussion/Conclusion
The use of ADCs has improved accuracy and completeness of data upload to NIgD. Direct observations have cited unregistered or finished patient episodes, dispensing procedural compliance, and user familiarity with the system as common reasons for incomplete data uploads to NIgD. Training is vital in assuring data quality and completeness. The new ADC process had unexpected consequences of forcing dispensing procedure compliance to improve uploads, whilst reducing dispensing times. It led to improved stock control and removed upload burden from dispensers. ADC stock discrepancy alerts allowed staff to proactively resolve discrepancies in real time. Time taken for additional processes to support management of stocks in ADCs, including monthly cycle counts, were important considerations for implementation.
The key advantage of using ADC batch number reports is being able to upload as a single batch monthly without having to log into individual patient records on the system. It facilitates early identification of failed upload attempts, supporting resolution. Further work focusing on fully aligning naming conventions to NIgD should deliver additional efficiencies; minimising manipulations currently required prior to upload.

References
1. Solís-Díez G, Turu-Pedrola M, Roig-Izquierdo M, Zara C, Vallano A, Pontes C. Dealing With Immunoglobulin Shortages: A Rationalization Plan From Evidence-Based and Data Collection. Front Public Health. 2022, 10:893770.
2. NHS England, The National Immunoglobulin Database, Medical Data Services and Solutions, 2023, Available at: https://igd.mdsas.com/ig-database/