Ortho2 has been a workhorse PMS for orthodontic practices for decades.
It tracks nearly every step a patient takes before treatment begins—exams, recalls, visits, notes, responsible parties, scheduling patterns, and more.
But most of that information stays locked inside the software interface, only visible one chart at a time.
The Integrator API changes that.
This guide shows you, in practical terms:
- The specific API endpoints worth pulling
- How their data helps TCs communicate better and follow up smarter
- How both single practices and DSOs can turn Ortho2 into a reliable analytics foundation
- A light technical sketch for teams who want to automate it
This isn’t meant to replace your PMS—it’s meant to make it actionable.
1. Ortho2 Data: Why Bother Pulling It?
Whether you're one location or a large group, the reasons are similar:
For solo or small practices
- Cleaner, more predictable new-patient days
- A TC who always knows who needs contact next
- No more guessing about exam outcomes
- Faster identification of no-shows and stalled patients
- Ability to generate simple, accurate “who to call today” lists
For DSOs or multi-location groups
- Consistent data across all offices (status definitions, visit types, codes)
- A way to benchmark TCs and new-patient teams fairly
- Ability to combine Ortho2 + OrthoFi + phone logs into a single funnel
- Better visibility into bottlenecks: exams booked but not completed, consults without decisions, recall leakage
In both environments, the value is the same:
You get a structured view of the clinical and scheduling activity leading up to a start.
And once you can see that, you can improve it.
2. The Ortho2 API Endpoints That Actually Matter
The API is large, but only a few endpoints consistently drive operational value.
Here are the ones that matter for most practices.
### A. Appointments — The Backbone of the Patient Journey
Endpoint: /catalogs/{catalog-identifier}/appointments
Appointments reveal everything about the new-patient pipeline:
- When exams were booked
- Which ones completed
- Which ones no-showed
- Who is stuck in recall or re-exam patterns
- How long patients wait between steps
- Provider schedules and availability
How this helps TCs and practices:
- Build daily or weekly “patients who need outreach” lists
- Spot patterns like consult drop-off or long re-exam cycles
- Identify families who need earlier openings
- Smooth out exam capacity for doctors
Small practices get clarity.
DSOs get predictability at scale.
B. Alerts — The Built-In Task System You Should Actually Use
Endpoint: /catalogs/{catalog-identifier}/alerts
Alerts in Ortho2 often function like a hidden to-do list:
- Follow-ups
- Insurance verifications
- Missing records
- Treatment notes that require review
- Recall reminders
Most practices underuse this because it's trapped in the UI.
Pulled through the API, alerts turn into:
- A real task queue
- A TC daily dashboard
- A way to measure “tasks created vs tasks completed”
- A simple prioritization board (urgent vs important)
This is one of the fastest ways to give TCs confidence and structure in their day.
C. Patients & Responsible Parties — The Human Context
Endpoints: Patient + guardian/responsible-party objects
This cluster of endpoints contains:
- Demographics
- Contact information
- Household relationships
- Referral sources
- Observation vs active vs pending statuses
Why this matters:
Scripts, reminders, and outreach are only effective if they reach the right person.
For example:
- Some families have multiple guardians involved
- Some households prefer email vs SMS
- Some parents are the decision makers; others manage scheduling
- Some siblings become future starts
A single practice gets better follow-through.
A DSO can finally understand patterns across demographics and regions.
D. Treatment Data — Understanding the Clinical Story
Depending on the Ortho2 configuration, treatment-related objects can include:
- Recommended treatment type
- Records completion
- Doctor notes
- Observation categories
- Conversion timing (how long from exam → consult → start)
This type of data is especially valuable for:
- Building realistic TC scripts
- Identifying cases that need doctor clarification
- Tracking doctor-specific preferences
- Modeling how long certain cases tend to take
When paired with appointment data, treatment details create a full “clinical funnel.”
E. Scheduling Metadata — The Operational Layer
Not always obvious, but extremely powerful:
- Chairs or rooms assigned
- Provider availability
- Typical doctor schedules
- Blackout windows
For TCs, this translates into:
- Automated time-option generation
- Better control of high-value appointment slots
- More consistent new-patient templates
For DSOs, this helps answer:
- Which locations are overbooked?
- Which have unused exam capacity?
- Which doctor schedules create friction for TCs?
3. Putting It All Together: What You Can Build with Ortho2 Data
Whether you're a single practice or a multi-location group, these are the practical outputs that become possible.
1. A Daily TC Call List (Automatically Generated)
Filtered by:
- Missed exams
- Pending exams needing confirmation
- Patients stuck in recall
- Patients with long gaps between steps
- Families due for check-ins
This alone boosts conversions without changing anything else.
2. A True New-Patient Funnel
You can measure:
- Lead → Exam
- Exam → Consult
- Consult → Decision
- Decision → Start
Most practices think they know these numbers.
Pulling Ortho2 data makes them real.
3. TC Coaching & Benchmarking
Small practices get:
- Clear view of where bottlenecks occur
- Easy “wins” to improve follow-through
DSOs get:
- Normalized metrics across offices
- Visibility into exam quality, scheduling gaps, and conversion patterns
- A coaching model that’s based on data, not anecdotes
4. Smarter AI Scripts and Outreach
When paired with OrthoFi financial data, Ortho2 gives AI models the clinical and scheduling context necessary to build:
- Personalized call scripts
- Email/SMS reminders
- Pre-start nudges
- Multi-channel follow-up sequences
It’s the difference between:
“Hi, just checking in.”
and
“Your exam last Thursday looked great, and Dr. Lee has openings Wednesday at 2:30 or Friday at 10:15. Want me to reserve a spot?”
You don’t need deep AI infrastructure — just clean inputs.
4. A Light Technical Blueprint (For Your Developer or IT Team)
Here’s a simple approach that works for both single practices and DSOs.
Step 1 — Authenticate & Pull Daily Deltas
Using Integrator API keys, poll:
- Appointments
- Alerts
- Patients
- Responsible parties
- Treatment data (where available)
Pull only what changed using created / updated filters.
Step 2 — Normalize Into Core Tables
Most teams model the data like this:
patientguardianappointmentalerttreatment_eventstatus_history
Keep it simple.
Step 3 — Compute Operational Signals
Examples:
- No-show streaks
- Patients overdue for recalls
- Time since last appointment
- Probability a patient will convert
- Schedules that consistently bottleneck new-patient flow
Step 4 — Feed Your Output Layer
Depending on your setup:
- A TC dashboard
- Manager-level reports
- AI-driven follow-up scripts
- Weekly “next steps” briefs
- Or simple CSVs emailed to the team
You don’t need a massive BI stack—just a clean pipeline.
5. The Bottom Line
Ortho2 already captures the full story of your patients before treatment starts.
Pulling that data gives you:
- Better communication
- More predictable exam days
- Higher conversion
- Cleaner reporting
- Less chaos in the TC workflow
Small practices gain clarity and consistency.
DSOs gain visibility across locations.
Either way:
Once Ortho2 data becomes structured, your entire new-patient process becomes easier to manage—and easier to improve.