This is what happens when an RCM vendor quotes a collection rate target before reading the data. The number is set to win the contract, not to match the math. Three months in, the target drifts. Six months in, the SOW gets renegotiated. The hospital is asked to deliver a number that the payer mix structurally cannot support. We do the opposite. Before any commitment, we model the realistic ceiling on the client's actual data and present three scenarios. This is the story of one of those engagements.
01 / The starting pointA 15 percent target on an 80 percent government book.
The client is a rural critical access hospital in the Western United States. Annual gross charges sit in the low $200 millions. Their payer mix is heavily government weighted, dominated by Medicaid managed care, with Medicare fee for service second, Medicare Advantage layered in, and a thin commercial slice.
A competing RCM vendor had pitched a 15 percent gross collection rate target in year one. The hospital's leadership knew that number sounded high but did not have the analytical infrastructure to disprove it cell by cell. They needed math, not a counter pitch.
On this mix, the dominant Medicaid MCO pays roughly 24 percent of inpatient DRG charges per the hospital's posted machine readable file. That single contract sets the structural ceiling on what the book can collect.
02 / DiagnosisWhat we found in the data.
The hospital had previously commissioned a chargemaster pricing study from a respected third-party consultant. That study modeled an 8 percent CDM lift and projected $1.49 million in incremental cash. The consultant's own Revenue Stream Summary, when fully unpacked, carried an implied gross collection rate of 8.04 percent. The vendor pitching 15 percent had not opened that workbook.
We ran the audit. Five findings made page one of the data audit log.
03 / The waterfallThe math the previous vendor never showed.
The single most useful slide in the deliverable was the collections waterfall as a cohort matrix. Rows are service month. Columns are collection month. The diagonal is the zero-month collection, off-diagonal cells are the tail. The pattern shows realization velocity, contractual writeoffs, and the still-open AR all in one view. Most "waterfalls" in vendor decks are bar bridges that hide this.
The mature cohorts plateaued at roughly 93 percent cumulative collection of charges by month 5, then continued tailing for another 6 to 9 months before settling at the structural GCR for the book. The gap from 100 percent to the cumulative ceiling is contractual writeoffs (driven by the Medicaid MCO contract) plus the still-open AR. That ceiling is what an RCM vendor can actually deliver. Anything above it requires changing the payer mix, not changing the operator.
04 / Three scenariosFloor, realistic commit, stretch.
The deliverable did not recommend a single target. It modeled three, with the data basis behind each, and let the CEO and CFO pick. This is the right shape for an RCM commitment conversation. It protects both sides. The hospital chooses how aggressive to be. The vendor signs a number the math can support.
The hospital picked the middle. The realistic commit translates to $21.6 to $22.8 million in annualized cash, depending on charges-vs-collections timing. The board accepted the number on the first review.
05 / The bonusThree compliance gaps we surfaced.
The DD was scoped to the collection rate question. While we were in the data, we ran the hospital's public machine readable file against the CMS Hospital Price Transparency rule and found three exposures the hospital did not know it had.
Outpatient CPT/HCPCS chargemaster not posted.
The MRF included the inpatient DRG file but omitted the outpatient CPT and HCPCS chargemaster. Direct violation of 45 CFR 180.50.
Up to $300/day CMP exposureMedicare FFS rates missing from MRF.
The standard payer rate columns did not include Medicare fee for service. CMS requires all payer-specific negotiated rates plus Medicare FFS rates.
Up to $300/day CMP exposurePublic contact field contained a development placeholder.
The hospital's MRF metadata contact field had been deployed with a placeholder name and example email. Live for months. Trivially detectable in a CMS spot check.
~$109K per year cumulativeUnfiltered AR aging was misreading the book.
The 47 percent "untouched" figure cited in the prior vendor's pitch came from an unfiltered aging report. Cross-tabulated with touch dates, the truly untouched aged AR was 2.3 percent.
Re-framing alone: clearer board view06 / The deliverableSix artifacts, all source-traced, all free.
HTML deck
43 slides, branded, self contained.
PDF version
Pixel-perfect render, board-ready.
Editable PPTX
Native text and charts, editable by the client team.
Pixel-perfect PPTX
Image-rendered fallback for presentations.
Excel workbook
8 tabs, 123 live formulas, native charts.
Data audit log
Every figure, formula, source cell traced.
One workbook tab per slide. Each tab holds the raw inputs at the top and the derived metrics as live formulas referencing those inputs. Charts are native Excel, not image embeds. If the client updates an input, every derived figure and chart recomputes. The Excel workbook is the audit trail and the working model in one file.
07 / Inside the deckWhat the 43 slides actually look like.
Six representative slides from the deliverable. Branded headers, source-attributed footers, ASP-RCM logo top-right and client logo top-left on every slide. Times New Roman throughout (FORVIS convention). All numbers traceable to the Excel workbook tab of the same number.
All numbers shown in these slide previews are from the actual engagement. Client name and identifying details are redacted per NDA.
08 / OutcomesSix months in.
The third-party charge master analysis said one thing. Our actual data, when fully modeled, said another. The audit gave our board math we could defend and three options to pick from. We picked the middle. We are hitting it.
09 / What stuckWhy the math holds at month 6.
The realistic commit was not a soft sell. Hitting 9.5 percent on this payer mix required three operational disciplines, sustained week over week.
Cohort-aware AR follow up
Aged AR triaged by overturn probability, not by dollar size. The 252 truly untouched aged accounts cleared first.
Credentialing recovery
Two payer enrollments had silently lapsed. Both re-credentialed inside 60 days. Timely-filing windows on recovered claims caught before lapse.
Front-end eligibility discipline
Real-time VOB on the largest Medicaid MCO contract reduced denials at intake. Authorization expirations tracked daily, not weekly.
None of these are clever. All three are operational discipline applied consistently. The audit was the conversation that got the engagement signed. The discipline is what is making the commit real.