AI-Powered Automation

How it works

1. 01AI integrates with your billing system and EMR to analyze historical claims data
2. 02System identifies patterns: CPT mismatches, chronic care gaps, upcoding risks, and denial trends
3. 03Flags missed billing opportunities you can address going forward
4. 04Monitors for patterns that could trigger a fraud audit later
5. 05Provides actionable alerts with explanations so you can make informed decisions

Common questions

Does this work with our EMR system?

Yes, we integrate with most major EMRs including Epic, Cerner, Athenahealth, NextGen, eClinicalWorks, and DrChrono. If you use a less common system, we can likely work with claims exports.

Will this flag things we're doing wrong?

The goal is protection and optimization, not punishment. It flags potential issues so you can address them proactively, before auditors do. You stay in control of all decisions.

How much revenue lift can we expect?

It depends on your specialty, payer mix, and how your practice codes today, so we do not quote a percentage up front. The analysis looks for previously missed opportunities like CCM codes, appropriate E&M levels, and gap closure, and the compliance side flags risky patterns so you can correct them before an auditor finds them.

How it works

1. 01AI monitors incoming faxes, EMR messages, and external records
2. 02System automatically reads lab results, imaging reports, and specialist notes
3. 03Extracts key clinical data: diagnoses, test results, recommendations, follow-up needs
4. 04Generates plain-language summaries with suggested chart updates and action items
5. 05Sends summaries to provider for approval before updating EMR

Common questions

What types of documents can it process?

Lab results, imaging reports (X-ray, MRI, CT), specialist consultation notes, hospital discharge summaries, pathology reports. Essentially any clinical document that arrives via fax, EMR message, or upload.

Does the provider still review everything?

Yes! AI does the first-pass reading and summarization. The provider reviews the summary and approves any chart updates. This maintains clinical oversight while eliminating the time-consuming extraction work.

How does it handle urgent findings?

AI flags critical results (e.g., "critical lab value," "urgent imaging finding") and escalates them for immediate provider attention.

How it works

1. 01AI analyzes historical appointment data: who canceled, when, and under what circumstances
2. 02System identifies patterns: time of day, day of week, patient demographics, appointment type, booking lead time
3. 03Flags high-risk appointments 24-48 hours in advance
4. 04Triggers automated reminder calls/texts to high-risk patients
5. 05Suggests double-booking low-risk slots or filling from waitlist to maximize schedule density

Common questions

How accurate are the predictions?

It depends on how much appointment history you have and how consistent your patterns are, and it improves as the system learns your patient patterns. We do not quote an accuracy number before we have looked at your data. The predictions decide who gets extra reminders and which slots are suggested for double-booking or waitlist fills; your front desk stays in charge of the schedule.

What if we accidentally double-book and both show up?

The system flags low-risk double-bookings only, and your staff decide whether to use them. If both patients show, you have a busy day, which is usually easier to absorb than an empty slot.

Does it work for specialty or procedure appointments?

Yes! The AI learns patterns for different appointment types. Procedure appointments often have different no-show patterns than routine follow-ups, and the system accounts for this.

How it works

1. 01Patient refill request arrives via phone, portal, or pharmacy fax
2. 02AI pulls patient chart and gathers context: last visit date, current medication list, refill history, controlled substance status
3. 03System checks refill eligibility: Is it too early? Is an appointment required? Any drug interactions or safety flags?
4. 04Drafts recommended disposition: "Approve 90-day supply" or "Require office visit, last seen 18 months ago"
5. 05Provider reviews the summary and approves or modifies it

Common questions

How does it handle controlled substances?

The system flags all controlled substances and applies stricter protocols: checking refill frequency, last visit requirements, and state-specific regulations. These always require provider review. AI just does the prep work.

What if a patient needs an appointment for the refill?

AI flags patients who haven't been seen within your practice's protocol timeframe (e.g., 12 months for chronic meds). It drafts a message explaining they need an appointment and can even offer scheduling options.

Does it check for drug interactions?

Yes, it cross-references the refill request against the patient's current medication list and flags potential interactions or safety concerns for provider review.

How it works

1. 01Lab results arrive in EMR or via interface
2. 02AI reads results and translates medical terminology into patient-friendly language
3. 03Generates personalized message in your tone: "Your HbA1c is 7.2%, which means your average blood sugar has been slightly elevated over the past 3 months. We'd like to adjust your medication and schedule a follow-up in 8 weeks."
4. 04Provider reviews message, makes edits if needed, and approves
5. 05Message sent via patient portal or secure text, with no manual typing

Common questions

How personalized are the messages?

Very. The AI considers the patient's specific results, history, current treatment plan, and your communication style. Messages don't feel robotic. They sound like you wrote them, because the AI learns your tone during setup.

Can it handle abnormal results that need urgent follow-up?

Yes! AI flags abnormal or critical results and drafts messages with appropriate urgency: "Your lab shows [issue]. Please call our office today to schedule an appointment." It escalates critical results to provider immediately.

What if the provider wants to add something specific?

Providers can edit any message before sending, and nothing goes out until they approve it. The system learns from edits over time, getting better at matching your preferences.