Where this started
In 2019, a multi-site pain management organization in Tampa, Florida had a surgical cancellation rate of 30%. The COO stopped all other analytical work and directed everything toward one question: why, and how do we get it under 10%?
Answering that question required building something that did not exist. The scheduling data was in Integy. The surgical records were in HST Pathways. The lab data was in Telcor. Every system assigned a different patient ID to the same person. Nobody had ever mapped them together.
We built the patient identity bridge across all three systems, constructed the scheduled-to-perform funnel from scratch, and decomposed every cancellation by window, location, referral source, payer, and prior authorization status. For the first time, leadership could see not just the rate — but the cause.
When we ran the same reconciliation logic against their payer contracts — which existed only as PDFs with legal and had never been compared against actual payments — the underpayment gap exceeded $2M in revenue the organization had no visibility into.
The pattern we kept seeing
The data exists
Every organization we worked with had the data. Scheduling records, surgical logs, billing history, auth timelines. The problem was never a lack of data.
The systems do not connect
EMR, ASC platform, and billing system each have their own patient ID for the same person. Cross-system analysis — the kind that answers why the cancellation rate is what it is — requires a bridge nobody had built.
The questions go unanswered
Leadership can see the rate. They cannot see the cause. They know revenue is leaking. They cannot trace it to a source. The gap is not in the data — it is in the connective layer.
The same problem in GI
A PE-backed MSO that had acquired multiple gastroenterology practices — needed unified reporting across all acquired practices. Each came in on a different system. Prexisio built the integration layer, delivered three recurring monthly reports, and managed annual MIPS.
The gap we exist to fill
Specialty surgical practices have tried to solve this problem before. Here is why it has not held.
Hiring an analyst
The analyst rebuilds the connection logic in their own way — if they understand the systems at all. The first three months are archaeology. By month six they may have the first answer. When they leave, the logic leaves with them.
Using EHR or billing reports
Single-system views show what happened inside one platform. They cannot tell you what happened across your EMR and your ASC and your billing system for the same patient on the same case. The cross-system question requires a cross-system layer.
Hiring a management consultant
Strategy-level insights from external observation. They do not work in your data, they do not build the patient identity bridge, and they do not deliver a quantified dollar amount from your actual records. The report is delivered. Then they leave.
What we believe
A 28% surgical cancellation rate is not a people problem. It is a data layer problem. The information to explain it exists — in your scheduling system, your prior auth records, your referral data. It has just never been connected.
Prexisio does not give you dashboards and walk away. We build the connective layer, verify every field against your live systems, run the cross-system correlations that your tools cannot run alone, and deliver findings with a dollar amount attached — monthly, connected to last month's decisions every time.
We do not produce insights. We produce answers.
The principles we operate by
- Specificity beats generality. A diagnostic built for pain management is more useful than one built for all of healthcare.
- The dollar amount matters. Every finding Prexisio delivers has a quantified revenue number attached. Insights without numbers are observations.
- The connective layer is the product. Not a dashboard. Not a report. The patient identity bridge and the cross-system SQL that makes the diagnostic possible.
- Recurring delivery compounds. The intelligence gets sharper every month because it is connected to what you actually did with last month's findings.
What we will not do
- Build something and hand it off without staying responsible for it
- Deliver a generic healthcare analytics product and call it a diagnostic
- Work from a distance — we work in your systems, with your actual data
- Call an insight a finding without a dollar amount attached
Who this is for
Multi-site specialty surgical practices with 3 to 20 locations — where the cancellation rate is above 12%, the data is in systems that do not communicate, and leadership is asking questions the current setup cannot answer.
PE-backed and MSO-managed practices
Multiple acquired practices on different systems, with different patient IDs and different payer contracts under one roof. The acquirer needs cross-portfolio performance and cannot get it. We build that view.
Independent mid-market practices
3 to 15 locations. Physician-owned or administrator-led. Growing fast enough that the data infrastructure has not kept pace. The cancellation rate is tolerated because nobody has ever decomposed it.
Diagnose. Deliver. Stay.
The diagnostic sprint gives you answers in 30 days. The ongoing engagement keeps those answers current every month. Every delivery is connected to the prior month's decisions.
Phase 1
Diagnose
Data access established. Patient identity bridge built. Cross-system correlations run. First findings — with dollar amounts — delivered to your leadership team within 30 days. Three prioritized interventions.
Phase 2
Deliver
Every diagnostic module refreshed monthly. Prior auth risk updated weekly. Biweekly advisory calls. Quarterly strategic review. The intelligence layer connected to what you actually did with last month's findings.
Phase 3
Stay
You own the system. We stay responsible for what it produces. A departure is an HR event — not a reporting crisis. When something breaks upstream, you hear from us, not from leadership.
Find out what your cancellation rate is costing you.One call. One number. No obligation.
Forty-five minutes. Eleven questions. A specific monthly dollar amount from your actual data. We will tell you within one business day if we are the right fit — or if we are not.