Managed Services · Business Consulting · Custom Software & AI Development
Entered once, not three times — 70% faster RCM workflows and 35% off licensing
A healthcare provider's technology estate had grown by addition, with every business unit solving its own problem. We took over running it, then rebuilt what duplication had made expensive.
~70%
Faster revenue cycle workflows
35%
Reduction in licensing costs
40%
Smaller data warehouse
3 → 1
Manual entries removed
The problem
What they were dealing with
Nobody designs an estate like this. It accumulates.
A business unit needs a report, so it gets its own dataset. Another needs access to the same underlying data, so rather than working out permissions, someone copies it. Sales runs on a marketing platform, operations on a CRM, finance on an ERP, and clinical on the EMR — and between each pair sits a person retyping information from one screen into another. Every one of those decisions was reasonable when it was made. Collectively they produce a technology estate that costs more than it should, moves slower than it should, and that nobody can see the whole of.
In healthcare this compounds, because the systems that do not talk to each other are the ones the revenue cycle runs through. A single patient was entered by hand into the marketing platform, then again into the CRM, then again into the clinical system when they were scheduled. Same person, same details, three keyboards. Every re-entry is another opportunity for a name, a date of birth or an insurance number to differ between systems, and mismatches in revenue cycle management are expensive to unpick.
Constraints
What made it hard, and what we did about it
- Challenge
- Cost had to come down without touching compliance. In a regulated healthcare environment, the fastest licensing savings are usually the ones that quietly remove a control
- What we did
- Three levers — negotiation, right-sizing the license count against actual usage, and moving users to the correct tier — with anything carrying a security, compliance or regulatory function ruled out of scope
- Result
- 35% licensing reduction with controls intact
- Challenge
- Access was being solved by copying. Each business unit had its own dataset built on the same underlying data, because duplicating was easier than governing
- What we did
- Consolidated the architecture and applied row-level security, so one governed dataset serves every unit
- Result
- Smaller warehouse, fewer licenses, one version of the data
- Challenge
- Nobody sat between the business units. Each team understood its own system and the handoffs belonged to no one
- What we did
- Put technologists in a liaison role across units, specifically to find gaps, risks and integration opportunities
- Result
- The integration opportunities became visible, and then buildable
- Challenge
- The same patient was entered three times. Marketing platform, then CRM, then the clinical system at scheduling — each re-entry a chance for the systems to disagree about a name, a date of birth or an insurance number
- What we did
- Built integrations across the marketing, CRM, ERP and clinical systems, with data moving on status values rather than on somebody remembering
- Result
- ~70% improvement across those revenue cycle stages, and one record instead of three
- Challenge
- Healthcare does not close. A support model built around business hours does not match how the organization runs
- What we did
- Round-the-clock technology support for the business units
- Result
- Interruptions handled when they happen, not the next morning
How it ran
The sequence
We took over running the estate first, then set about changing it. That order matters: you cannot sensibly redesign something you are not yet responsible for.
01
Support, before anything else
We stood up a technology support team covering the business units, running round the clock. In a healthcare operation, systems that are down are patients who are not being seen, and a support model built around business hours does not fit the way the organization runs.
02
Licensing, on three levers
Negotiation across the major platform agreements; right-sizing the license count against actual usage rather than seat allocation; and correcting the tiers, again from usage. Nothing carrying a security, compliance or regulatory function could be cut or downgraded, whatever the usage data said.
03
The duplication underneath
The estate had accumulated multiple dataset instances built on the same underlying data, each created so a different business unit could have its own view. We consolidated the architecture and applied row-level security, so one governed dataset serves every unit with each seeing only what it should.
04
The manual work between systems
Our technologists worked as liaisons across business units, finding where a process crossed a boundary and became a person retyping. The clearest was the patient record itself.
05
Integrations that move on status
Rather than a person deciding it is time to copy a record into the next system, the status value on the record drives it — a patient reaching a given stage is what moves their data, not somebody remembering to.
06
Compliance throughout, not at the end
Which data can move, where it can rest, who can see it, what gets logged. Those constraints shaped the architecture from the start rather than arriving as a review comment after the design was finished.
Results
What it produced
~70%
Faster revenue cycle workflows
End-to-end time: revenue cycle workflows run about 70% faster after manual processes were replaced with automated workflows, in the stages where patient data crosses systems.
35%
Reduction in licensing costs
Across total licensing spend, from negotiation, right-sizing by usage and tier correction combined. Separate from the dataset consolidation saving.
40%
Smaller data warehouse
After consolidating 32 duplicate datasets and collapsing 28 built on the same metadata
3 → 1
Manual entries removed
A patient was entered into three separate systems before reaching the clinical record
Revenue cycle workflows run about 70% more efficiently in the stages where patient data crosses systems — the handoffs that used to be somebody retyping. Overall licensing costs came down 35%. The data warehouse is smaller, which reduced storage cost alongside the license saving. And the business units have support that answers around the clock rather than during office hours.
The three effects are related, which is the point worth taking from this. The licensing saving was mostly not a negotiation — two of its three levers were usage analysis, which only becomes possible once somebody is responsible for the whole estate and can see who is actually using what. The workflow gains came from integrations that were only obvious to someone sitting across business units rather than inside one. Taking over the estate is what made the rest visible.
What the client gained
Beyond the numbers
One party responsible for the estate
The same team running it and improving it, which is what made the improvements findable.
Savings that did not cost coverage
35% off licensing — negotiated, right-sized against real usage, and re-tiered — with every security, compliance and regulatory function preserved.
Duplication removed at the root
Dataset consolidation and row-level security, cutting license count, warehouse size and storage cost together.
One entry instead of three
Patient data now flows on status across the marketing, CRM, ERP and clinical systems, in the revenue cycle stages where a mismatch is most expensive.
Compliance built in, not reviewed in
Regulatory constraints shaping the architecture from the start, from experience implementing for healthcare organizations.
Support that matches the operation
Round-the-clock cover for business units that do not stop.
Reference
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