Lab Automation · LIS/LIMS Software
How Laboratory Automation Improves Clinical Lab Workflows
What does laboratory automation include?
Laboratory automation includes equipment and software that support specimen handling, testing, review, and reporting. An LIS connects information across those stages. The useful starting point is a specific bottleneck, followed by validation and measurement of the effect on the lab’s own workflow.
Automation spans the sample’s entire journey
Laboratory automation combines equipment, interfaces, and software to reduce repetitive work and make information easier to track. It can apply before testing, during analysis, and after results are available. The right approach depends on the lab’s volume, test menu, space, staffing, and budget.
Pre-analytic automation: identify and prepare the specimen
Consider receipt, accessioning, labeling, routing, and preparation. Some laboratories use automated handling equipment; others begin by connecting ordering and barcode workflows. Start by identifying where staff repeat data entry, search for information, or resolve labeling and routing problems.
Analytic automation: connect the work and the results
Analyzers perform the testing, while interfaces connect the instrument’s information to the LIS. Confirm whether each supported connection receives results only or also transmits orders. Test order identifiers, result mapping, units, flags, and exception handling with the actual equipment involved.
Post-analytic automation: review and deliver information
Review, reporting, and provider delivery are part of the same workflow. Ask how the system handles results that require attention, report release, corrections, and delivery to an EMR or portal. Any automatic review or release behavior needs to be configured and validated for the laboratory’s procedures.
How does an LIS support automation?
The LIS connects orders, specimens, results, and reports to the lab’s identifiers and worklists. Useful tools may include instrument interfaces, barcodes, pending lists, QC, dashboards, and management reports. The value comes from how those tools fit together in the lab’s daily work.
Stratus DX supports instrument connections, HL7 interfaces, and reporting workflows. Review the exact models, data exchange, modules, and responsibilities in your project scope.
Measure the effect in your own laboratory
Choose a baseline before making a change. Track relevant measures such as turnaround time, manual result entry, repeat work, pending samples, and staff workload. Compare the same workflow and time period after validation and training.
Published results from another laboratory are not a guaranteed outcome for yours. Evaluate the cost of equipment, interfaces, maintenance, training, and implementation alongside any expected efficiency gains.
Start with a bounded implementation
Select a clear bottleneck, involve the staff who use the workflow, and agree on success criteria. Test both normal samples and exceptions. Expand when the first change is stable and its effect is understood. A practical automation plan can be incremental; it does not need to replace every manual task at once.
Frequently asked questions
Does laboratory automation mean replacing every manual task?
No. Start with specific repetitive steps or bottlenecks, then decide which equipment or software changes are practical for your lab. Some tasks still require trained staff to review exceptions and validate results.
How does an LIS support laboratory automation?
An LIS connects orders, specimen identifiers, instrument data, review, and reporting. The details depend on the analyzers, interfaces, modules, and workflow included in the implementation.
How should a lab measure an automation project?
Compare the lab’s own baseline and post-implementation measures, such as turnaround time, rework, manual entry, and staff workload. Include validation, training, maintenance, and support in the evaluation.