Cube vs. Mosaic for Consolidating a Multi-Location DSO

A location can have a strong production month, meaning providers booked and performed a lot of billable work, while collections lag because insurance claims take weeks to adjudicate and pay. A forecast built only on collections will look artificially soft in a location that's actually growing its provider capacity, while a forecast built only on production ignores the real cash-timing risk of insurance reimbursement.

Track both, with a clear reconciliation between production booked and cash actually collected against it, so a slow month can be diagnosed as a production problem or a collections-timing problem rather than treated as one undifferentiated issue, which changes what corrective action actually makes sense.

When providers are paid a percentage of their own production or collections, that compensation cost scales with each location's specific provider mix, not with a company-wide average. A model that applies one blended compensation percentage across every location will misstate margin at any location whose provider comp structure differs from the average, which is common when a DSO has a mix of associate dentists and specialists on different comp schedules, and it tends to get worse as the group adds locations through acquisition rather than organic growth over time.

If your team already builds per-location P&Ls in a spreadsheet that correctly splits production, collections, and provider comp, Cube's approach of syncing that spreadsheet against your practice management and payroll data keeps the model where it's understood, with less manual export from each location's system each month.

Once you're consolidating enough locations that a private equity sponsor, a lender, or a multi-location owner wants a dashboard rather than a spreadsheet handed to them each month, Mosaic's consolidated view can save real time. Confirm in a demo that it can track production separately from collections at the location level, and that provider compensation can vary by location rather than assuming one company-wide formula.

Each location's payer mix, the split between different insurance plans and cash-pay patients, drives its effective reimbursement rate even before considering collections timing. A forecast that ignores payer mix differences across locations will misjudge which location's production actually converts to the most cash, so track payer mix by location and update it when a location's patient base shifts meaningfully.

Jirav's driver-based approach fits a DSO planning to add a location or bring on additional providers at existing locations, since that growth needs to be modeled against realistic ramp-up assumptions, a new location or provider rarely produces at full capacity immediately, rather than a flat revenue bump applied on day one.

The gap between a location's fee schedule and what insurance actually reimburses, the contractual write-off, varies by payer and by procedure, and a model that ignores it will overstate expected collections against booked production. Track write-offs by payer at each location so a shift in payer mix, say more of a location's patients moving onto a lower-reimbursing plan, shows up as a specific, explainable change rather than an unexplained dip in collections.

Export a quarter of production, collections, and comp data from two or three representative locations and see how cleanly it maps into the tool you're considering, since practice management exports vary enough between systems that a location running on an older or discontinued practice management system may need real extra work before it integrates cleanly with either platform. Ask specifically whether the platform can handle a location that changed practice management systems mid-year, since that transition point is where historical consolidation most often breaks, and it's a fairly common scenario for a DSO that's still actively integrating recently acquired locations rather than a rare edge case.

Test these points before consolidating locations:

• Export a quarter of production, collections, and comp data from two or three representative locations and test how it maps.
• Ask how the tool handles a location running on an older or discontinued practice management system.
• Confirm production can be tracked separately from collections at each location.
• Check that provider compensation can vary by location instead of using one blended percentage.
• Verify that insurance write-offs can be tracked by payer at each location.