The digital landscape in laboratory
medicine: Current systems, future possibilities

If we reflect on the role of clinical scientists and in particular the role of the Duty Biochemist it becomes clear how essential laboratory IT systems are to delivering an effective clinical service. Whilst there will always be a role for expert/ individual with a specialist interest, understanding of pathology IT processes, information flow, terminology and what can go wrong with these are vital for ALL clinical scientists. These areas will be to focus of the morning session of the meeting. Looking beyond laboratory IT systems, new AI and informatics technology have huge potential to influence data analysis and other aspects of laboratory practice. The afternoon session of the meeting will share case studies from LabMed members in this area and provide an opportunity for a panel discussion with attendees on any of the themes raised during the meeting.

This presentation provides a foundational overview of the pathology information network, tracing its journey from the data-processing origins of the 1960s "Six Labs Project" to the modern integration of robotics, cloud computing, and intelligent instrumentation. We will explore how "joining up" data sources creates synergistic value, improving both user satisfaction and clinical outcomes.

A key focus will be the critical role of interoperability and standardisation. As the NHS transitions from legacy EDIFACT messaging to modern FHIR-based integration and new reporting standards (DAPB4101), ensuring data "fits" the system becomes essential for patient safety. By providing a high-level look at the National Laboratory Medicine Catalogue (NLMC) and the move toward real-time, patient-centred records, this talk sets the stage for the day’s deeper technical discussions.

Finally, we will address the emerging frontiers of Machine Learning and Clinical Decision Support, confronting the professional challenges ahead: how we regulate these systems and evolve our roles to lead these technological advancements.

The interdependencies between LIMS and order comms

How the Order comms can be used to drive efficiencies within the laboratory and clinically

Considerations of Order Comms systems when deploying a new LIMS

Modern laboratories rely heavily on their Laboratory Information Management System (LIMS), yet it is all too easy for clinical authorisation services to operate within workflows shaped more by inherited rules than by intentional clinical design. This presentation explores how laboratories can reclaim control of their digital environment and build a flagship clinical authorisation service that is safe, efficient, equitable, and genuinely value adding.

The session examines how streamlined authorisation queues, well structured auto commenting frameworks, reflexive and reflective testing strategies, interim/ghost reporting, and other LIMS based tools can act as powerful enablers of clinical effectiveness. These features not only improve consistency and efficiency but also support equitable decision making by reducing unwarranted variation in practice.

Authorisation queues are presented not as passive repositories of results but as dynamic tools that should be intentionally engineered and optimised. Delegates will be encouraged to challenge historical assumptions, interrogating the purpose of each trap as a means to reduce surplus trapping that obscures genuine priorities. Practical methods for reviewing, restructuring, and decluttering trapping lists - particularly during key organisational change points such as team restructuring, service redesign, LIMS consolidation, or new system implementation - will be explored.

Throughout, the emphasis is on aligning LIMS configuration with standards, guidelines, and local data, ensuring that digital processes genuinely support clinical decision making rather than dictate it.

Ultimately, this presentation aims to empower attendees to be curious, to understand how their LIMS truly works, and to confidently reshape its rules, comments, and workflows. By doing so, laboratories can ensure that the LIMS serves the clinical team—rather than the other way around—and can build an authorisation service that is efficient, future ready and centred on patient safety.

Laboratory medicine is increasingly defined by how data are structured, coded, and reused across healthcare systems. For generalist pathologists, informatics decisions—often embedded within laboratory information systems—directly influence result interpretation, clinical safety, and downstream use of diagnostic data. This presentation explores why coding is a clinical responsibility rather than a purely technical task, using examples from laboratory medicine to illustrate how terminology, system configuration, and interoperability shape everyday practice. It highlights the risks associated with poorly defined or inconsistent coding, the opportunities enabled by standardised terminologies such as SNOMED CT, and the importance of professional clinical oversight. The session emphasises the critical role of generalist pathologists in safeguarding the clinical meaning of laboratory results as pathology transitions to increasingly digital, interoperable models of care.

Automation is the process of offloading routine, large-volume, and/or intricate but predictable tasks onto a machine. Near any tasks that does not require creativity or judgement can be automated.

This session outlines commonly-used automation frameworks (in programming languages such as Python, PowerShell, R, etc). Real-world automation projects are shown to demonstrate the potential of each framework to increase efficiency. Attendees could apply these design patterns and skills at their own places of work, or to their own duties.

The session further focuses on automating safely, with suggestions for patient-first design and implementation.

Leveraging big data to screen for laboratory medicine disparities related to age, sex, ethnicity and in relation to time and place.

Strategies derived from the data to mitigate these disparities.

Smart dashboards using big data for identifying patterns and monitoring the impact of mitigative strategies. I will include seasonal pseudohyperkalaemia/ dyskalaemia here.