1. What actually separates good charting from bad

Four things, and only one of them shows up in a demo. Vendors demo the template. What decides whether your team is still happy in month six is the other three: how fast a routine visit closes, who is allowed to read the note, whether a plan survives across visits, and what happens when two clinicians disagree about a note.

What to test Why it decides the day How to check it in a demo
Time to close a routine note A follow-up is most of the schedule. Thirty seconds of friction times twenty patients is an hour a day. Ask them to chart your most common follow-up end to end, with your own wording, while you time it.
Who can read it A note visible to the whole clinic by default is a problem the first time a front-desk hire opens a psych note. Ask what a receptionist sees. Then ask what a locum sees.
Whether the plan spans visits Optimisation care is a programme, not an encounter. A plan trapped inside one note has to be retyped every time. Chart visit one, then open visit two and see what carries forward.
Co-signing If an NP or PA charts under a supervising physician, this is a legal workflow, not a nicety. Ask to see the queue of notes waiting for a signature, and who gets told.

The fifth thing, which nobody asks about until it bites: can you find a note again. Search across charts is the difference between answering a records request in five minutes and spending an afternoon opening patients one at a time.

2. Templates: the difference between a form and a note

Most systems ship a template builder. The question is whether the output reads like a clinical note or like a filled-in form, because the second one is what a reviewer, an attorney or the next clinician actually has to work from.

The practical test is boring and revealing: build one template for your single most common visit, chart two patients on it, and read both notes side by side. If they look identical apart from the numbers, the template is doing the thinking and the note is not worth much. If the structure holds but the clinical content reads differently, it is a note.

In Aminova a template defines the sections a note carries, and the fields inside a section can be pulled from the intake the patient already filled in — so a value the patient typed does not get typed again by a clinician. An AI scribe can draft the narrative from the consultation itself, and the clinician edits rather than composes.

3. Treatment plans that outlive the visit

This is where general-purpose EHRs are weakest for optimisation clinics, because they model an encounter and you are running a programme. A hormone protocol with a titration schedule, a peptide course with a reassessment at week twelve, a weight-loss programme with monthly dose steps — none of those live inside a single note.

What the clinic runs What an encounter-shaped EHR does What it should do
A protocol with a dose schedule Each visit re-states the dose in free text Hold the schedule once; each visit records what actually happened against it
A reassessment due at week 12 Someone sets a reminder, or does not The plan knows the cadence and surfaces the due visit
Labs trended over a year Results file as documents in date order Discrete values that draw a line across visits
A patient-facing version of the plan Printed, handed over, and immediately out of date Visible in the patient app, updated when the plan is

4. Who can read the note is a setting you will care about later

Clinics usually discover this the uncomfortable way. The default in Aminova is that a note is visible to its author and the clinicians who need it, not to everyone with a login — and sharing is explicit, per note, the way a document share works rather than a blanket role switch.

Ask any vendor the same three questions: what does the front desk see, what does a part-time injector see, and what does an outside locum see on their first day. If the answer to all three is “everything”, that is a decision you are inheriting rather than making.

5. Where each system actually fits

There is no best charting system in the abstract — it changes with what a note has to carry.

Disclosure. Aminova publishes this and sells software in this category. We have not tested our competitors’ products, so nothing below rates them or claims what they can do — each line describes the kind of clinic that vendor builds and sells for, which is a question they answer publicly and you can verify in a demo.

Long-form functional and integrative notes — hour-long intakes, extensive panels, a supplement plan as part of the treatment. OptiMantra and Cerbo both sell into functional, integrative and naturopathic medicine.

Coaching-led notes — where the record is mostly check-ins, goals and accountability rather than a prescription. Healthie and Practice Better are built around that relationship.

Aesthetics charting — injection maps, before-and-after photography, consent per treatment. PatientNow, Aesthetic Record and Pabau sell into that work.

Notes that must satisfy a claim — if a meaningful share of revenue is billed to insurance, you want a system built around the claim. Charm is ONC-certified, which matters for some contracts.

Prescribing-led programme notes — a protocol that spans months, titration recorded against a schedule, labs trending across the programme, co-signing for mid-levels. This is the case Aminova was built for, and the one where we would put ourselves forward.

Where we are the wrong choice: if most of your visits are billed to insurance, if you need an ONC-certified record for a Medicaid or health-system contract, or if your charting is primarily injection mapping and photography with no programme behind it. Those are real requirements and we would rather say so here than three weeks into an evaluation.

6. What an AI scribe does and does not change

A scribe drafts the narrative from the consultation so the clinician edits instead of composes. On a long intake that is the difference between charting during the visit and charting at eight in the evening.

What it does not do is decide anything. The draft is a draft, the clinician signs it, and the structured parts of the record — the dose, the plan, the discrete lab values — are not guesses from audio. ⚠️ Ask any vendor what their scribe does when a recording is mostly silence; the honest answer is that a model asked to summarise nothing will invent something, and the safe behaviour is to refuse rather than produce a plausible consultation that never happened.

7. Frequently asked questions

Can we keep our current note templates?
Usually yes — send a few as PDFs or screenshots before you commit to anything and we will rebuild them as templates so your clinicians open something familiar on day one rather than a blank system.

Does a mid-level’s note get co-signed properly?
Yes. A note needing a signature goes into a queue, the supervising clinician is notified, and the signature is recorded against the note. ⛔ What we deliberately do not do is pretend to encode every state’s supervision rules into a matrix — those change, and a wrong matrix is worse than none. You set who co-signs for whom.

Can we search across every chart?
Yes, with one limit worth knowing: notes search respects the same provider scope the chart does, so a clinician does not find a note they would not be allowed to open.

Will the patient see their treatment plan?
If you want them to. The plan can be published to the patient app as a programme with steps, and it updates when the clinical plan does rather than being a PDF that went out of date the day it printed.

Is charting included on every plan?
Yes. Charting, templates, note sharing and co-signing are the product, not an add-on. The AI scribe is the piece that sits on higher tiers.