How to Automate LigoLab

A specimen becomes a result inside the LIS

LigoLab is a laboratory information system and revenue cycle platform built for diagnostic laboratories: anatomic pathology practices, clinical labs, reference laboratories and hospital lab departments.

The LIS is the lab. A specimen arrives in a bag with a requisition, gets accessioned, and from that point every physical step has a digital twin: the cassette at the grossing bench, the block, the slide printed at the microtome, the stain, the case assembled for the pathologist, the sign-out, the report that goes back to the ordering physician, and the claim that follows it.

LigoLab covers both halves of that on one platform. Anatomic pathology, clinical modules from haematology through microbiology to molecular, specimen handling, document management, outreach and the billing that turns a signed report into money are the same system rather than three that have to be reconciled.

The lab's day is shaped by people outside the lab

A laboratory is a service business whose customers are other practices, and whose suppliers include other laboratories.

So a great deal of the day is spent in somebody else's system. A requisition arrives without a diagnosis code and somebody phones the ordering clinic, then chases it again. A case is sent out to a reference lab and the result comes back in that lab's own web portal, where a person has to go and look for it. A courier was supposed to collect from three draw sites this morning and only two are logged. A claim was denied and the reason sits on a payer's website with a countdown running on the appeal.

Then the client side. A referring practice that used to send a steady volume and has quietly stopped. A new account waiting on credentialing paperwork. A physician asking where a case is, because nobody told them it was still in decalcification.

None of that is bench work, and all of it is somebody's whole day.

LigoLab

Sendout results collected each morning Reference laboratory portals checked for every referred case, so a pending case moves the day the outside result appears.

Appeal windows sorted by what closes first Denials pulled from payer portals with their deadlines attached and ranked by value and by how little time is left.

Referring practices that went quiet Clients whose volume has dropped, named with what they used to send and when the last case arrived.

The rule engine already carries the case to sign-out

LigoLab automates a great deal of this internally, and it is one of the more configurable systems in the category.

The Rule and Automation engines let a lab build conditions and actions, chain rules into decision support trees and add conditional fields without a developer, which is how reflex testing, routing and validation are handled without anyone touching code. The Interface Engine connects the LIS to instruments, EHRs, billing services and reporting agencies, and supports HL7, FHIR, X12, ASTM and Restful API. Reporting and Distribution builds the lab's own report formats, including CAP cancer protocols, and delivers them in the format each client prefers. Specimen Handling assigns identifiers and automates cassette assignment and slide printing, while Sendout Tracking runs referral queues with turnaround times set per client. On the money side, auto coding, eligibility and pre-authorisation checks and automated statements take care of routine billing.

All of that runs where an interface exists or a rule can be written.

The gaps are the places where neither is true: a payer portal, a reference lab that publishes results only through its own website, a small referring clinic that will never fund an interface, a courier's tracking page.

Pending lists that include what other people's systems know

Extend the same reading to those sites and the pending list stops ending at the lab's own walls.

Sendout results checked on each reference laboratory's portal every morning, so a case waiting on an outside result is flagged the day it appears rather than the day somebody thinks to look. Courier pickups reconciled against what the collection sites recorded, so a missed route is a message at nine rather than a specimen found at four.

Denials pulled from payer portals with the appeal window attached and sorted by how soon each one closes. Eligibility rechecked on the payer's own site for the accounts where the feed has never been reliable. Referring practices whose volume has dropped, named with what they used to send and when the last case arrived, which is the list an outreach team never has an afternoon to build.

Every one of those is reading, and reading is the safe half. Anything that touches a case, a result, a report or a patient record is prepared and held for a qualified person to review and release. In a CLIA laboratory that is not a preference, it is the shape of the job.

Turnaround time is mostly waiting

Very little of a slow case is bench time. It is a case sitting because a diagnosis code never arrived, a reference result nobody went and looked for, a claim nobody appealed before the window shut.

WebRun is an AI agent that works a real Chrome browser, signed in the way your staff are. It opens the reference lab's portal, the payer site or the courier's tracking page, reads what is on the screen, and puts it in front of the person who can act on it.

It runs on your schedule in your own private environment, sessions are not shared between tools, and a workflow can be restricted to an explicit list of domains. You can watch a run and stop it part way through.

The workflows below are already built, and each names exactly what it opens.