(P-IG-15) Efficacy Of Computer Automation To Improve Donor Selection For Platelet Crossmatching

Blood centers (BC) require a multitude of different software and programs for daily operations. The local Immunohematology Reference Laboratories (IRL) utilize various component modules of an electronic application system (EAS) in order to view testing history, product manufacturing steps, and donation information. With the utilization of scripts and automation, a leaner process can be created. The platelet crossmatch process at the IRL involves scanning donor samples to view donation details, blood type, and product information. This information is needed to select appropriate specimens for testing. Some factors that make samples ineligible are incompatible bloodtype, donations without a platelet product, and products that are shipped prior to crossmatching. Each sample scanned that does not meet testing criteria is unusable and expends turnaround time. To improve efficiency, a program was developed to automate the selection process. This study evaluated the difference in time performing platelet crossmatch unit selection between the data filtering program and manual selection.

Study

Design/Methods:

The program was designed to utilize available data in a way that is more attuned to the platelet crossmatch process. After scanning available samples, data is pulled from the EAS and is filtered by location, products available, and user selected ABO type. Only acceptable specimens are shown to the user. We compared the time it took to process the sample selection manually and with the aid of the designed program.

Results/Findings:

Table 1 compares the time it took to select donor samples manually and with the program.

Conclusions:

Overall, the selection process was reduced by an average of 38% with the use of the data filtering program. The program was able to save 8 minutes of technical time that can be utilized to execute other regulated duties.  The use of automation has a great advantage as it can decrease clerical errors and improve turnaround time for product delivery. This is essential when searching through large amounts of specimens. These findings illustrate the advantages of developing time-saving scripts targeting specific processes in the laboratory.