Clinical Laboratory Informatics: Practical Guides

Clinical laboratory informatics is the discipline of managing a lab’s data — how results are coded, validated, released, reported, and measured — as opposed to the bench work that produces them. It is where a clinical lab’s defensibility lives: an accurate result that is coded to the wrong LOINC, released past a failed control, or never called to the ordering provider is still a failed result. This section collects the practical articles behind that layer of the lab. For a structured overview of the system it runs on, start with the clinical LIS guide; the posts below go deeper on individual decisions.

The through-line is that informatics problems are rarely discovered at the bench. They surface at inspection, in a denied claim, or in a public health agency’s rejection queue — long after the specimen is gone. Getting them right up front means deciding how failed quality control is reviewed and documented before release, how your test catalog maps to national vocabularies, and what evidence the system keeps that a critical value actually reached a human. These articles work through those decisions with the configuration detail a lab director, LIS analyst, or QA manager needs, grounded in CLIA-regulated practice.

Where to start in this section

• Quality control before release — Westgard rules and failed-QC review in the LIS: Levey-Jennings charts, multirule evaluation, failed-QC alerts, and SOP-controlled sample holds.
• Coding results to a national vocabulary — a practical guide to LOINC mapping: the six-axis structure, the mapping pitfalls that produce silent mismatches, and how to maintain the map as the catalog changes.
• Critical value reporting — the callback workflow end to end: defining the list, time-to-call windows, read-back confirmation, and the audit trail an inspector will ask for.
• Reportable conditions and ELR — how a public health LIMS automates electronic laboratory reporting, from reportable-result detection through HL7 v2.5.1 messaging and agency routing.
• Chain of custody — what specimen tracking captures at every step and how custody is evidenced for forensic and regulated work.
• Billing data quality — stopping claim denials before they happen: eligibility at accessioning, validated codes, and clean-claim submission.
• Measuring the lab — the clinical lab KPIs that matter and how to surface turnaround time, QC performance, and volume in a dashboard people actually use.
• Reagent and probe lot control — FISH probe lot tracking and scoring QC in a cytogenetics workflow.

Related guides and platform pages

The topics above map onto specific parts of the platform: QC in the LIS, analytics for clinical labs, specimen tracking, LIS billing integration, and public health LIMS reporting. For evaluation-stage reading, see the lab analytics dashboard guide.

To see how these controls would be configured against your own test catalog, control rules, and interfaces, request a demo.