Pending Log Monitors: Implementation for Improved Lab Efficiency

Abstract

Abstract Hospital labs are increasingly consolidating into larger hospital systems with centralized testing locations. Specimens collected at disparate sites need to be transported to different locations for testing. Our LIS (Sunquest FlexiLab) does not provide a real-time display of specimens in need of transport to other locations. The current system lists pending specimens in paper printouts. The printouts have a difficult-to-read format, fail to account for certain add-on tests, and leave room for human error. In addition, IT staff must maintain test groups that are specific to each sending and receiving facility pair. This is a costly use of IT resources and is error prone due to test menu differences at each facility. In the current study, we evaluated the current system of batching specimens for transport and then designed a web-based application to provide a dynamic display of transport batches. The web-based application that we developed is called a “transport batch monitor” (TBM). The TBM displays specimens that need to be sent to another location for testing. This application was implemented in Python using the Flask microframework. Data are transferred in JSON format from Sunquest every 3 minutes using custom Caché ObjectScript routines. The application can be accessed with a secure login from any computer with Internet access and is displayed on large, fixed monitors in locations where transport batches are assembled. The display shows pertinent information for lab techs to be able to locate specimens that need to be sent out and is color-coded for ease of use. Metrics used to evaluate the current system included timing studies, surveys of lab staff performing the task, and paper usage. The process of collecting and batching specimens for transport to another facility took on average 24 minutes and required on approximately 22 sheets of paper. Anecdotally, specimens had historically been missed, especially when clinicians ordered add-on tests on specimens from days prior due to the way the LIS generated the printouts. Although 74% of techs surveyed reported that the task was somewhat easy or very easy, 32% were somewhat dissatisfied with the current system, and 40% said that the current paper printouts were either very unclear or somewhat unclear. Postimplementation metrics will be collected once the TBM has been implemented. We hypothesize that the transport batch monitor is a simple, inexpensive web-based tool that can greatly improve the day-to-day functioning of the lab. We hope it will improve efficiency and tech satisfaction, and reduce errors.