The output of clinical pathology laboratory testing informs more than 70 percent of all medical treatment decisions and therefore greatly impacts patients. Total laboratory automation (TLA) workflow solutions have begun to appear in modern laboratories with automated enablers entering laboratories’ workflows. Many modern clinical laboratories use laboratory information systems (LIS) to manage and create data from their workflows, as a LIS improves a lab’s ability to adhere to guidelines set by regulatory agencies and associations.
Every step of the pathology workflow in the modern automated LIS workflow has the potential to create operational and clinical data that could be used for descriptive and predictive data analysis, informing decisions that contribute to continuous workflow improvements. Leveraging big data and predictive analytics can also help improve operational and strategic market advantages, as well as improve revenue prospects for clinical labs.
As part of my doctoral dissertation at Northcentral University, I am conducting a study about on the adoption of automated clinical pathology workflows to help innovators understand what barriers exist toward the adoption of big data technologies and workflows in clinical pathology labs.
The COVID-19 pandemic
Lengthy laboratory turnaround times for diagnostic testing were listed as a critical failure in the global response to the COVID-19 pandemic. For many patients, convenient access to clinical laboratory services impacts their likelihood of following through with diagnostic tests ordered by their doctors, making quick and accessible testing a critical part of patient care.
The challenges of adopting total lab automation
Inconsistencies in how data is stored, as well as incompatibilities between automated modules, can result in a large amount of unusable data for analytics. Experts recommend first conducting a thorough assessment of a clinical pathology lab’s existing manual workflows to create the most optimal automated workflow system. However, fully automating a laboratory can be a significant financial and operational challenge. Thus, investing in a TLA system, in addition to the constraints of finding space to house its components, can deter smaller labs from adopting these solutions. A smaller organization may need to carefully plan their budget for such an undertaking and consider grouping an upgrade to automated workflows with other lab improvements.
The gap in existing knowledge
The literature around clinical labs has focused on access to resources and technical expertise as barriers to adopting TLA, while resistance to TLA by end users in health care settings needs further exploration. To fill this need, I am conducting a research study out of Northcentral University on the adoption of automated clinical pathology workflows and invite all clinical managers to share their insights by completing the study survey!
Please share this information with your fellow clinical laboratory managers and leaders. By helping us increase awareness of the study, you’ll be a part of this significant effort to better understand and reduce work stress in the clinical lab.
Thia Denae is a doctoral candidate in the School of Technology at Northcentral University who is working on her dissertation toward a doctor of technology and innovation management degree with a specialization in data science. Thia is also a senior software development leader within the pathology laboratory industry.