AccAnalysisAccAnalysis
Revenue Cycle & Financial Operations

Thirty legacy reports, rebuilt as one governed reporting layer

Hospital clients were receiving static reports from a legacy reporting platform — inconsistent between facilities, not interactive, and impossible to tailor. We rebuilt them, then automated their production and delivery.

At a glance
Status
Delivered
Region
United States
Engagement model
Dedicated team

Status: Delivered. Described from our own delivery records. Client identity, brand and commercial terms are withheld. Figures, where given, cover the period stated and nothing beyond it.

The organisation

Context

A revenue-cycle operation producing reporting for a large number of hospital client facilities.

The reports had been built over years on a legacy reporting platform and an enterprise application's native reporting. They worked, but each facility's requirements had been met by producing another variant, and the set had fragmented.

The brief

The problem

  • Reports were static, so any question beyond the printed answer meant a new request.
  • The same measure was defined differently in different reports, which made comparison between facilities unreliable.
  • Producing and distributing the set was manual and recurring.
  • Facility-specific requirements had been handled by proliferation rather than by parameterisation.
The work

What we built

Thirty-plus reports rebuilt

On a modern BI stack — financial, batch performance, stair-step recovery, invoice summary, detailed invoices, month-end, ACH, aging and acknowledgement reporting — each tailored to the requirements of the facilities that use it.

A single definition per measure

So a number means the same thing across the set.

Automated refresh, export and distribution

With output emailed and placed in shared document storage on schedule.

Method

How we delivered it

  1. 1

    Inventory the existing set

    Every report, its consumers, and what it actually answers.

  2. 2

    Reconcile the definitions

    Which is where most of the real work sat, and record the decisions.

  3. 3

    Rebuild in waves

    Grouped by consumer so a facility's set changes once rather than repeatedly.

  4. 4

    Parallel-run old and new

    For a cycle, comparing outputs before retiring anything.

  5. 5

    Automate production and delivery

    Once the content was agreed.

Sequence

How it was phased

PhaseDurationWhat happens
1Inventory
2 wks

Every report, consumer and measure catalogued

2Definition reconciliation
2–3 wks

One agreed definition per measure, decisions logged

3Rebuild waves
8–12 wks

Reports rebuilt in consumer groups

4Parallel run
2–4 wks

Old and new compared for a full cycle

5Automation
2–3 wks

Scheduled refresh, export, email and document-store delivery

Indicative phasing for work of this shape. Actual duration varies with data quality, access and decision speed.

Hand-over

What the client keeps

  • The report definitions
  • The semantic model and metric dictionary
  • Refresh and distribution configuration
  • The reconciliation decision log from the rebuild
Stack
Power BI DesktopPower BI Report BuilderSQLSharePointScheduled distribution
Keep reading

Related

Related case studies

Tell us what your current system can't do, and we'll tell you what it would take to change that.