By the Medicodio HIM team · Reviewed 2026-09-15
A demo proves a vendor can perform under ideal conditions: a clean chart, a controlled pace, no ambiguity. It doesn't prove the tool will hold up on the charts that actually make your queue miserable. That's what a short, coder-led trial — scored against a simple rubric — is built to answer, and it's not a separate project. It's the same trial period you were already going to run, just measured on purpose instead of by gut feel.
Let Your Coders Pick the Charts, Not the Vendor
Skip the vendor's sample chart. Before the first call, pull two weeks of your own team's actual work — the charts that took longest, generated a query, or fed a denial — and hand that stack (de-identified, per your usual policy) to whichever vendors make it past a first screen. A vendor who balks at coding real charts instead of running their own script has told you something useful before the trial even starts.
This also cuts through a common assumption: plenty of teams search for the best ai medical coding software expecting one universal winner, when the honest answer depends on your specialty mix and how much oversight your compliance team wants in the loop. If you haven't narrowed the field yet, our rundown of AI medical coding software options is a faster starting point than a string of demos.
The Scorecard
Build this with your coders and QA lead before the first vendor call — it takes one meeting, not a committee:
- What you're testing: Accuracy on your own charts — Who scores it: Coders + QA — Pass bar: Matches or beats current audit accuracy
- What you're testing: Turnaround per chart — Who scores it: Coders — Pass bar: Faster than your current average
- What you're testing: Handling of low-confidence charts — Who scores it: Coders + QA — Pass bar: Routes to a human, doesn't guess
- What you're testing: Specialty depth — Who scores it: Coders — Pass bar: Correct on your mix, not a demo specialty
- What you're testing: Query quality — Who scores it: HIM/CDI — Pass bar: Specific, not generic
What to Test During the Trial
Specialty depth, not specialty count. A vendor citing “40 specialties supported” tells you little about whether it handles the modifiers your orthopedic group uses daily. Run the trial against your three or four highest-volume specialties, not whatever sample the vendor supplies, and ask for their accuracy breakdown by specialty in writing.
Accuracy earns this scrutiny because it's not a side detail — CMS's 2024 review of Evaluation & Management claims found a 10.3% improper payment rate, with 49.1% of that traced to incorrect coding rather than documentation gaps ( CMS compliance guidance ). A headline accuracy number only matters if it holds on the codes you actually bill most.
Turnaround under your real documentation, not a clean sample. Time each chart type separately, including the two-line notes and the ones missing a clear diagnosis link. MediCodio's own published figures cite under 1.5 minutes per chart against an industry average of roughly 8 minutes for manual coding — but the number worth watching in your trial is performance on your messiest charts, not your cleanest.
The charts your team already flags. Feed in the charts that trigger recurring queries or show up on the denial report every quarter. This is where a shallow tool either flags the ambiguity for a human or codes through it with false confidence — and the second failure mode is the expensive one, because it looks fine until the denial arrives.
What happens when it isn't sure. Ask plainly: does a low-confidence chart route to a certified coder for review, or does it get coded and submitted regardless? That single design choice affects your denial rate and audit posture more than any accuracy percentage a vendor quotes.
Scoring It Without Turning It Into a Project
Once the trial charts are coded, have each coder and your QA lead score every category above on a 1–5 scale, then compare notes chart by chart. Disagreements are usually the most useful part — a low score for a missed modifier and a high score for fast turnaround on the same chart is a real conversation about what your team values. If you want to formalize the comparison further, the same five categories make a workable RFP rubric, but for most teams the trial and scorecard alone are enough to decide; our cost-per-chart breakdown can help frame the finance conversation once you have.
Whatever you choose, the goal isn't replacing your coders — it's picking the tool your own coders trust on the charts that matter most. For a deeper look at the review workflows worth stress-testing during the trial, see our guide on how coding managers evaluate medical coding ai software .
FAQ
How long should a trial run?
Two to three weeks, covering a full billing cycle, is usually enough to compare trial output against your normal audit results.
Should coders or IT lead the evaluation?
Coders and QA should own accuracy and workflow scoring, since they're the ones who can tell whether a suggested code is right. IT's role is security, integration, and uptime.
What accuracy bar should we set?
Your own current audit accuracy, not an industry headline number. A new tool needs to match or beat that on your real charts.
How many specialties should we test?
Your three to five highest-volume specialties, in depth. Specialty count is a marketing number; depth on your own mix is what affects your denial rate.
What should happen when the software isn't confident?
The chart should route to a certified coder for review, not get coded and submitted automatically. Ask for a live demonstration of that handoff during the trial.
Worth a 20-minute call to see how this scorecard maps to your specialty mix and denial patterns? We're happy to walk through it.