Hire a data analyst or bring in Prexisio — how to decide
The conversation usually starts the same way. Leadership is asking questions the current setup cannot answer — why is our cancellation rate at 27%, which locations are driving it, are our payers paying what our contracts say they owe. The COO knows the data exists somewhere across the systems. The question is how to get to it.
The two paths that come up most often are hiring a data analyst and bringing in an outside firm. Here is a practical framework for deciding which one is right for your situation.
The question underneath the question
Before comparing options, it is worth getting precise about what you actually need.
Most COOs describe the problem as "we need better data" or "we need someone who can pull these reports." But the underlying need is almost always one of two things — and they require different solutions.
You need ongoing analytical work. Someone to answer ad-hoc questions from leadership, build models, explore the data, and adapt as the business changes. This is an analytical capability — it requires judgment, domain knowledge, and continuous iteration.
You need recurring operational intelligence. A specific set of deliverables — cancellation decomposition, prior auth risk dashboard, payer contract reconciliation — produced on a reliable schedule, connected to each other, and updated monthly. This is infrastructure — it requires building a cross-system diagnostic layer that runs reliably without depending on any one person.
Most multi-site specialty surgical practices that come to Prexisio need the second thing. They describe it as the first because "hire an analyst" is the more familiar framing. But the deliverable they actually need — cross-system patient identity resolution, a scheduled-to-perform funnel, a prior auth risk dashboard refreshed weekly — is infrastructure, not ad-hoc analysis.
Getting this distinction right determines which path makes sense.
Three questions to ask before deciding
1. Is the problem inside one system or across multiple systems?
If the data problem lives inside a single system — you need better reporting out of your EMR, or you want cleaner AR aging out of your billing platform — a data analyst with experience in that system can probably solve it.
If the problem requires connecting data across your EMR, your ASC platform, and your billing system — and the same patient has a different ID in each one — you are not looking at a reporting problem. You are looking at a patient identity resolution problem that has to be solved before any analysis is possible. That is a specific technical competency, not a general analytical skill.
Multi-site specialty surgical practices almost always face the second problem. The questions that matter most — cancellation decomposition by referral source, prior auth tracking mapped to the surgical schedule, payer contract vs. paid reconciliation — all require cross-system data that does not exist in a connected form anywhere in the current setup.
2. Do you need answers in weeks or months?
A new hire needs 60 to 90 days to learn your systems, your organization, and your specific operational context before they can produce anything reliable. Add 60 to 90 days for the recruiting process and you are looking at 4 to 6 months from decision to first useful output.
If your COO is asking questions that need answers now — because a leadership meeting is in 6 weeks, or because a PE board is asking for cross-portfolio performance data, or because a payer is sending a recoupment demand — 4 to 6 months is not a useful answer.
Prexisio delivers first findings within 30 days of data access. That is not a marketing claim — it is a structured delivery process: 2 weeks for data access and patient identity resolution, 2 weeks for the first diagnostic sprint. If your timeline requires answers faster than a hiring process can produce them, that is a relevant input to the decision.
3. What happens when the person leaves?
This is the question that most organizations do not ask until it is too late.
When a solo data analyst leaves a multi-site surgical practice, several things happen simultaneously: the reports stop running, the query logic lives in a single person's files that may or may not be documented, and the organization faces a 3-to-6-month gap before a replacement gets up to speed.
For organizations where the recurring reporting is critical — PE ownership expecting monthly financial reports, prior auth dashboard used by the auth team every Monday, payer reconciliation driving AR recovery — that gap is not tolerable.
Prexisio is designed so that a departure on our side is a process event, not a crisis. The query logic is documented. The patient identity bridge is versioned. The delivery cadence continues. You own the system. We stay responsible for what it produces.
When hiring an analyst makes sense
Hiring is the right call when:
- The data problem is primarily within a single system and does not require cross-system identity resolution
- You need ongoing exploratory analysis and strategic data questions answered continuously — not a fixed set of recurring deliverables
- Your organization is large enough and data-mature enough to manage a data function (typically 10+ locations, dedicated analytics budget, data leadership in place)
- You are building toward a full internal data team and this hire is the first of several
- The timeline is flexible — you can absorb a 4-to-6-month ramp before seeing output
When Prexisio makes sense
Prexisio is the right call when:
- The problem requires connecting data across your EMR, ASC platform, and billing system — which means patient identity resolution has to be solved first
- You need a specific set of recurring deliverables — cancellation decomposition, prior auth dashboard, payer reconciliation — produced on a reliable monthly schedule
- You need first findings within 30 days, not 4 to 6 months
- You cannot afford to have reporting stop if a key person leaves
- Your practice does not yet have the internal data infrastructure or data leadership to successfully hire, onboard, and direct an analyst
The hybrid path
The path that works well for many mid-market specialty surgical practices is sequenced:
Phase 1: Build the diagnostic layer with Prexisio. Patient identity bridge built and verified. Cross-system deliverables running. Monthly cadence established. The organization now has the data infrastructure it never had — and a clear picture of what it produces.
Phase 2: Run it with Prexisio ongoing. The recurring deliverables run monthly. The prior auth dashboard is refreshed weekly. Advisory calls keep findings connected to decisions. This phase runs indefinitely, or until the organization is ready for the next step.
Phase 3: Transfer if you want to. If your practice grows to the point where hiring a full-time analytics function makes sense, the infrastructure Prexisio built is already documented and inside your systems. We step back. Nothing migrates — it was built in your environment from day one. The hire inherits a working system instead of a blank slate.
The key difference from hiring first is the starting point. A hire who inherits a working cross-system diagnostic layer — with verified patient identity resolution, documented query logic, and a monthly delivery cadence already running — can be productive in weeks instead of months. A hire who has to build it from scratch will spend their first 6 months doing what Prexisio does in 30 days.
The diagnostic question
The simplest test for which path is right:
If you had a complete cross-system diagnostic running today — cancellation decomposition, prior auth risk dashboard, payer reconciliation, referral source intelligence, all connected and delivered monthly — would you still need to hire someone?
If yes — you need ongoing analytical capability beyond what a recurring diagnostic delivers. Hiring makes sense, ideally after the infrastructure is in place.
If no — you need the infrastructure, not the headcount. Prexisio makes sense.
Most COOs at multi-site specialty surgical practices who work through this question honestly land on the second answer. The questions they need answered are specific and recurring. The problem is not a lack of analytical talent. It is a lack of the connective layer that makes the analysis possible.
That is the problem worth solving first.
If you are working through this decision for your practice, the assessment is a useful starting point — it will tell you the specific dollar amount sitting in your current data gap, which makes the build-vs-hire math considerably more concrete.