Real healthcare integration problems I've helped solve.

Complex integration problems rarely have purely technical causes. These examples show how I work across systems, data, clinical workflows, vendors and delivery teams to understand what is actually going wrong and determine what to do about it.

From problem to working solution

The examples below describe the problem, why it was difficult, what I actually did and what changed as a result.

01

Message queue blocking: when the error blocks the fix

A message rejection caused subsequent messages for the same patient to be blocked, including the messages needed to create the patient and encounter.

The problem

The inbound message processor for the hospital billing system was rejecting messages from an electronic document management system, because the required encounter did not yet exist. It then blocked subsequent messages for the same patient, including the messages needed to create the patient and encounter.

In other words, the message with the error was blocking the message needed to fix the error.

Why it was difficult

The integration crossed six components. Investigation also identified delays in the middleware path, but the precise source of that performance problem could not be conclusively established.

What I did

I was responsible for investigating the integration and recommending a fix. I traced the message flow and examined integration logs, message timing and the behaviour of the downstream systems.

I also assessed alternative solutions, including allowing the inbound message processor to create encounters, routing all messages through a common path, and introducing message-skipping capability.

The selected approach was to change the document management system message primary key from the patient identifier to the encounter number. This removed the dependency that allowed a failed message to block the messages needed to create the encounter.

Result

The permanent workaround removed the failure mechanism and there were no further incidents after implementation. A manual business as usual replay step remained for the small number of cases where the inbound message processor reported that an encounter could not be created.

The systems involved

PBRC-IE — Power Billing Revenue Collection, the hospital billing system.
IMM — Inbound Message Module, PBRC-IE's inbound message processor.
Paperlite — the electronic document management system generating the messages.
MuleSoft, JCAPS and eGate — the integration middleware components.
02

ADT integration queue blocking

A data-contract mismatch caused h-trak to reject ADT messages. The rejected messages then blocked the queue and prevented valid messages from being processed.

The problem

Following a change to the integration between the electronic medical record and h-trak, certain ADT messages were rejected. The resulting queue blockage affected the integration used by h-trak handheld scanners to match patient wristbands.

Why it was difficult

The problem appeared during go-live and was significant enough to require an emergency rollback. The interaction between invalid messages and queue behaviour made the operational impact much greater than a simple bad-data error.

What I did

I led the investigation and coordinated the immediate response, establishing the data-contract mismatch and queue-blocking behaviour. I recommended and coordinated a rollback, then worked with the vendor and project stakeholders on remediation and replay of affected messages.

Result

The four-hospital feed was restored successfully and the backlog of missed messages was replayed.

03

Financial Class reconciliation

More than 1,200 billing errors appeared after go-live because Financial Class and bed type did not match. The underlying problem involved both integration and staff workflow.

The problem

PBRC-IE would not raise invoices for affected encounters, creating revenue leakage and frustration among processing teams.

Why it was difficult

The apparent integration error was influenced by the way staff were using WebPAS workflows. Retrospective Financial Class changes were particularly problematic because the new workflow was more cumbersome than the previous one.

What I did

I coordinated the relevant revenue, finance, clinical administration, technical and vendor stakeholders. I investigated examples in PBRC-IE and examined the Financial Class and change date/time fields in messages from WebPAS, establishing that the integration was correctly transmitting the retrospective Financial Class when the correct workflow was followed.

Result

The investigation established that the integration itself was working as designed and identified the operational changes required to address the source of the errors. The number of errors was reduced from more than 1,200 to approximately 100 within three months.

04

Patient identity across two hospitals

Two independent hospitals needed to identify the same patient to enable safe and efficient care of patients moving between the two hospitals.

The problem

Two independent hospitals needed to identify the same patient to enable safe and efficient care of patients moving between the two hospitals.

Why it was difficult

Three information systems needed to be integrated in a coordinated way and there was no established pattern to do so. A private operator was to run one of the hospitals and they used a different patient administration system and workflow to the government hospital.

What I did

I worked with the public and private hospital subject matter experts to establish the available integration options and the implications of each approach.

I presented the options and analysis to project stakeholders and secured approval for the selected integration architecture.

I then directed and coordinated the technical implementation, working across the relevant public hospital, middleware and external development teams. I supported testing, production deployment and resolution of issues following go-live.

I directed the configuration of the information systems and developed the message transformation scripts.

Result

The four related integrations went live on schedule with very few defects. The integration created over 29,000 new patients in the first six months of operation.

The systems and concepts involved

Cerner eMR and WebPAS — the patient administration systems.
Oracle OHMPI — the master patient index.
05

SCHN eMR integration

A transformation project needed to merge the electronic medical records of two children's hospitals while retaining separate surrounding systems.

The problem

One hospital needed to use the other hospital's eMR while continuing to operate its own PAS, radiology, pathology, diet and billing systems.

Why it was difficult

The hospitals retained separate patient administration systems, creating two sources of new patients and patient updates feeding a combined eMR.

What I did

I specified the integration architecture for person identity and departmental integrations, implemented Cerner components, oversaw middleware work, supported testing and coordinated production deployment.

Result

The integration deliverables were no longer at risk and the resulting architecture addressed the difficult problem of managing person identity across distributed systems.

06

Enterprise Imaging / RIS-PACS integration

Integration architecture was required to synchronise patient, encounter and imaging information across multiple clinical systems and eMR environments.

The problem

NSW Health needed integration between Patient Administration Systems, electronic medical records, Radiology Information Systems, PACS and Enterprise Imaging platforms.

Why it was difficult

The environments contained different identifiers, message formats and system configurations.

What I did

I designed integration solutions to synchronise patient and encounter information, addressing identifier conflicts and message-format variations through transformation and standardisation.

What this demonstrates

This work required understanding how clinical systems, identifiers, messages and enterprise imaging services interact across a complex healthcare environment.

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