Freed AI Pricing Plans: What You Actually Pay in 2026

The cheapest Freed AI plan that allows unlimited notes still requires manual copy-paste at every visit. Here is what each tier actually costs your practice once labor and workflow gaps are factored in.

Freed AI's individual pricing structure looks straightforward on the surface: three tiers, three price points, a clear feature list. But the decision most practice administrators make at this stage, picking the cheapest plan that handles unlimited notes, quietly locks them out of the features that actually protect revenue. Understanding exactly what each tier includes, and what it withholds, is the only way to arrive at a number your CFO will respect. As of 2026, Freed AI lists three individual plans: the Starter plan at $39/month, the Core plan at $79/month, and the Premier plan at $119/month (or $104/month billed annually). Confirm current pricing with Freed before budgeting, since vendor pricing can change.

Freed AI’s pricing tiers scale from limited monthly usage to unlimited access, with EHR integration and ICD-10 coding appearing at the Premier level:

• Starter → $39/month → Annual cost: Not listed → 40/month cap → EHR integration: ❌ No → ICD-10 coding: ❌ No.
• Core → $79/month → Annual cost: Not listed → Unlimited usage → EHR integration: ❌ No → ICD-10 coding: ❌ No.
• Premier → $119/month → $104/month annually → Unlimited usage → EHR integration: ✅ Yes → ICD-10 coding: ✅ Yes (beta).

Pricing note: Freed AI’s lowest listed monthly plan price is $39/month.

Freed's three-tier structure creates a meaningful decision point: the only plan that includes both unlimited notes and EHR integration is Premier at $119/month. Any practice benchmarking against the $79 Core plan is evaluating a workflow that still requires manual copy-paste at every encounter, a step that practice operations literature consistently associates with per-encounter labor overhead, transcription lag, and charge-entry delay. Whether that overhead exceeds the monthly tier delta depends on encounter volume and staff wage rates, and is worth modeling before the plan decision is finalized.

The Starter plan's 40-note monthly cap ends most serious evaluations quickly. A primary care physician seeing a typical daily patient load can exhaust that cap within the first few working days of the month. Based on standard ambulatory encounter volumes, active primary care physicians routinely exceed the Starter cap each month, meaning Starter is realistically suited only to part-time clinicians or those early in building a panel.

Core removes the note cap and adds a template builder and an AI clinician assistant for post-encounter editing. For a clinician who dictates, reviews, and manually pastes notes into their EHR, Core covers the documentation generation side cleanly. The honest trade-off is structural: without EHR integration, every note still requires a manual transfer step, introducing transcription lag, field-level error risk, and per-encounter labor that compounds across a full month of visits.

Premier adds EHR integration and delivers a seamless ambient documentation experience, but only when the practice is already running a supported EHR such as Epic or Athenahealth. It also includes:

• ICD-10 coding assistance (beta as of 2026)
• Visit summaries
• Patient instructions
• Referral letters

The ICD-10 feature carries an important caveat: practices needing billing-grade coding accuracy should verify current accuracy levels before treating it as production-ready.

Key takeaways

• Freed AI's cheapest unlimited-notes plan looks like the obvious choice, until you see which revenue-protecting features it withholds from lower tiers.
• A signed BAA and a SOC 2 Type II report confirm a vendor secured your data during an audit window; they say nothing about whether the notes generated will survive a payer's E&M coding review.
• Freed AI's Chrome extension pushes notes into your EHR, but the architecture behind that push determines whether physicians get their evenings back or just trade one manual step for another.
• The biggest documentation-related financial loss in most practices never appears on an invoice, it accumulates one undercoded encounter at a time, in the gap between what was documented and what the visit actually warranted.
• Subscription price is the variable every pricing page is designed to make you focus on; it is also the variable least likely to predict whether an AI scribe investment improves your practice's financial position.
• Before trialing any tool, pull three months of encounter data and compare your billed E&M distribution against specialty benchmarks, that gap is the number your CFO actually needs.
• iScribe Health's EHR integration closes the loop by pushing AI-generated notes directly into the correct patient chart across major EHR platforms, eliminating copy-paste and duplicate entry so the documentation burden disappears instead of moving downstream.

Free Trial, Student Discount, and Groups Pricing - Everything Else You Pay (or Don't)

Pricing tiers answer the "how much per seat" question. They rarely answer the question that actually determines whether a tool earns its place in your budget: what does each tier include, who qualifies for a discount, and where is the real negotiating room? Those three questions have concrete answers for Freed AI, and each one changes the math in ways the pricing page alone does not surface.

The 7-Day Free Trial, No Credit Card Required

Freed AI's free trial runs seven days with no credit card gate, meaning a practice can put the full product through its paces before a single dollar is committed. Freed AI delivers its greatest value when physicians want a completely hands-free documentation experience during the visit. Ambient listening runs in the background while the clinician focuses entirely on the patient, with the AI drafting the encounter summary at the point of note completion. That workflow only reveals its real return in a live clinical environment, not a demo.

Clinicians who evaluate ambient scribes in a real clinical setting consistently find that note quality varies significantly across specialties and documentation styles, and that a trial period is the only reliable way to assess fit. Seven days is enough to run the tool across a representative mix of visit types, review output quality, and identify any workflow friction before the team is committed. This is particularly relevant for high-volume practices where clinicians regularly chart two or more hours outside of patient care time, since the burnout-reduction math becomes visible quickly under real load. See Freed AI's own breakdown of AI scribe costs for context on how trial access fits into the total cost picture.

Key takeaway: Seven days is tight if your physicians have variable schedules or if you need multi-provider sign-off before a purchase decision. Plan the trial deliberately, not casually.

Student, Trainee, and Fellow Discount

A residency program coordinator evaluating the tool for trainees can cut the per-seat cost in half before the first invoice arrives. The discount applies to individual plans, not Groups pricing, so academic medical centers running a group contract cannot route trainee seats through this tier. One friction point worth planning around: practices and programs that have moved through plan changes, for example, upgrading from an AI add-on plan to a higher tier, have experienced waiting periods before the new access actually activates.

If your training program has a hard go-live date, confirm the activation timeline with Freed's sales team in advance rather than assuming the upgrade is instantaneous. Verification requirements and whether the discount carries forward post-graduation are also details worth confirming directly before building a training program around the pricing assumption.

50% Max discount for students and trainees

Groups Pricing - Custom Quotes and What Drives Them

Groups and practice pricing is custom and requires contacting Freed's sales team. The actual economics hinge on EHR integration depth, SSO configuration, and admin infrastructure, all of which vary widely by practice size and tech stack. Freed AI materializes most cleanly when the practice or health system is already running a supported EHR and wants a seamless ambient documentation experience layered into existing workflows. Administrators who enter the Groups conversation understanding what EHR integration, single sign-on, and dedicated support are actually worth operationally leave far less on the table than those who treat it as a pure per-seat negotiation. For an independent benchmark on how Groups pricing stacks up, Twofold's Freed AI pricing comparison provides a useful outside reference.

The Groups tier includes four infrastructure components that solo-plan pricing does not:

• Admin dashboards
• Single sign-on
• A dedicated account manager
• Priority support

That infrastructure layer typically determines whether a multi-provider rollout succeeds or stalls. A note of caution that experienced practice administrators will recognize: shared or group-buy pricing arrangements across any SaaS platform carry inherent reliability risks. Access continuity is never fully guaranteed under shared licensing models, and service disruptions, however infrequent, are a known operational exposure. The Groups tier's dedicated account manager and priority support exist precisely to reduce that exposure for practices where documentation downtime has direct patient care consequences. When Freed AI is running across every encounter in a high-volume practice, the stability of that infrastructure tier is not a procurement footnote, it is a clinical operations dependency.

HIPAA Compliance and Security - What Freed's Certifications Actually Cover

Signed BAA in hand, SOC 2 Type II report attached to the vendor questionnaire: for most practice administrators, that combination feels like the compliance conversation is over. It isn't. The certifications tell you a vendor has addressed data security controls during a defined audit window. They say nothing about whether the notes that vendor generates will hold up when a payer pulls your E&M coding patterns for review.

Freed's HIPAA and SOC 2 Type II Certifications Explained

Freed AI holds both HIPAA compliance and SOC 2 Type II certification, and a BAA is provided to covered entities. SOC 2 Type II audits evaluate whether security controls, including access management, encryption, and incident response, operated effectively over a 6 to 12 month observation period. HIPAA governs protected health information specifically. Neither certification eliminates the need to review subprocessor agreements, data retention timelines, or breach notification procedures.

What makes this gap particularly consequential for practices using ambient AI documentation tools is the way PHI moves in a modern clinical workflow. PHI does not stay in one place. It flows through the ambient listening layer that captures the encounter, the conversational AI that structures it, the EHR integration that receives the finalized note, and the automated E&M coding engine that assigns codes at the point of note completion. Each handoff is a potential exposure point.

Practice administrators who treat HIPAA compliance as a checkbox bolted on after deployment, rather than something interrogated across every integration, are the ones who discover gaps only when a breach notification or payer audit forces the question. SOC 2 and HIPAA address different risk surfaces, and satisfying one does not satisfy the other.

Key takeaway: Control drift after that audit window closes is your practice's exposure, not the vendor's audit finding.

The BAA Is a Starting Point, Not a Finish Line

A BAA is a contractual requirement, not a certification. Every administrator should ask four questions beyond the checkbox:

• What is the breach notification timeline and procedure?
• Which subprocessors receive PHI, including third-party AI model providers, ambient listening infrastructure, or cloud systems supporting EHR integration?
• What are the audio and note data retention and deletion timelines?
• When was the most recent SOC 2 Type II report issued, and what dates does it cover?

The subprocessor question is not theoretical. In a workflow that spans ambient listening, real-time denial alerts, and automated E&M coding, PHI routinely touches infrastructure that is not explicitly named in the BAA itself. A signed agreement is a necessary starting point, but subprocessor schedules and data flow diagrams are the documents that complete the picture of your practice's actual data exposure.

For high-volume practices and health systems where clinicians are charting two or more hours outside of patient care time, the compliance surface is not smaller than in a solo practice; it is larger, because the volume of PHI moving through ambient documentation and EHR integration is proportionally greater. A signed BAA with no corresponding review of those downstream data flows is not a compliance posture, it is a compliance assumption.

Related Reading

• Ambient Digital Scribe
• What Is Ambient AI
• Automated Medical Documentation
• Automated SOAP Notes

EHR Integration Support - What Freed's Chrome Extension Does: and Where Native Integration Matters More

That assumption shows up constantly in procurement conversations: find the cheapest plan covering unlimited notes and a basic EHR push, and documentation costs are optimized. In practice, the architecture behind that integration determines whether physicians gain back their evenings or simply trade one manual step for another, a distinction that matters most in high-volume practices where clinicians are already charting two or more hours outside of patient care time every day.

Freed's EHR Push Is a Chrome Extension, What That Means at the Workflow Level

Freed's EHR integration is delivered via a Chrome browser extension, not a native connection to your EHR's data layer. Per Freed's own announcement, EHR Push is positioned as one-click AI note transfer into any web-based EHR, the operative phrase being web-based, because the extension overlays the browser session running your EHR and pushes generated note text into visible fields. That is meaningfully different from a preferred-partner API integration, which writes structured data directly to the correct encounter fields at the database layer.

The practical difference surfaces the moment a physician tries to push a note into a complex Epic encounter with multiple discrete fields: the extension pushes text, not structured data, so field-mapping fidelity depends entirely on what the extension can "see" in the browser window at that moment. One reason extension-based delivery persists in this market is a genuine infrastructure constraint: legacy EHR systems often lack API or FHIR support, making native integration extremely difficult or impossible for many vendors. A Chrome extension is a pragmatic workaround for that reality.

The problem is that the workaround is often presented as equivalent to a native connection, and for physicians, nurse practitioners, and clinical staff who need defensible, field-mapped documentation, that gap is not cosmetic.

Why EHR Integration Is a Tier Gate, Not a Deployment Guarantee

EHR push is gated to the Premier tier. Practices on lower-tier plans have no push capability at all and must copy notes manually into their EHR, reintroducing exactly the friction ambient AI is supposed to eliminate. When an EHR lacks preferred-partner integration support, providers are forced to manually copy and paste AI-generated text, creating downstream inefficiencies that compound across every encounter, every day.

Even on Premier, the extension-based architecture means deployment is not automatic. A practice running Epic or Athenahealth will likely need IT to whitelist the extension under enterprise browser policy before a single physician can use it. That approval process does not appear on the pricing page, and it is not a formality: security teams in clinical environments routinely flag unapproved browser extensions during quarterly audits, and remediation timelines can stretch weeks.

IT and EHR administrators, the people who actually govern extension policy, are carrying integration-setup responsibility that the vendor's marketing does not acknowledge.

Extension-Based vs. Native API Integration: the Operational Gap

The core architectural gap is this: a Chrome extension operates at the UI layer, while a native preferred-partner integration operates at the data layer. UI-layer pushes transfer text; data-layer integrations transfer structured, field-mapped clinical data. For downstream coding and compliance, that distinction is material.

A note dumped into a free-text field does not populate the discrete diagnosis, procedure, or visit-type fields that drive E&M level assignment and billing accuracy. Industry research on ambient AI scribe deployments consistently shows that field-level mapping fidelity, not note generation quality, is the variable that separates tools that reduce documentation burden from tools that relocate it, moving the manual effort from the note-generation step to a downstream copy-paste or field-correction step that still consumes physician or staff time. This is where iScribe combines Ambient AI Documentation with EHR Integration designed for practices and health systems already running a supported EHR that want a seamless ambient documentation experience, not a browser overlay that approximates one.

At the point of note completion, after the AI drafts the encounter summary, iScribe Health's Automated E&M Coding and E&M Coding Intelligence work against structured, field-mapped data, the kind that actually populates discrete diagnosis, procedure, and visit-type fields. That matters for Real-Time Denial Alerts and billing accuracy downstream; you cannot fire a denial alert against a free-text blob. For clinical informatics teams and IT administrators responsible for integration governance, the difference between auditing a whitelisted Chrome extension and managing a supported native integration is the difference between a quarterly security risk and a supported workflow.

The goal throughout is defensible documentation, not just faster documentation, for physicians, nurse practitioners, and clinical staff across every patient encounter.

A note dumped into a free-text field does not populate the discrete diagnosis, procedure, or visit-type fields that drive E&M level assignment and billing accuracy.

Coding Assistance Features and the Real Cost of E&M Undercoding - What Freed's Pricing Page Doesn't Tell You

Every month, a practice's biggest documentation-related financial loss doesn't appear on any invoice. It doesn't show up in the scribe staffing budget, the EHR licensing renewal, or the per-seat line on an AI subscription. It accumulates silently, one undercoded encounter at a time, in the gap between what a physician documented and what the visit actually warranted.

Freed's Tiers - ICD-10 on Premier, CPT Still in Beta

ICD-10 coding is available on the Premier tier only. On Starter and Core, the note gets generated, but no diagnosis code surfaces alongside it. CPT coding exists in beta, meaning it is not yet a production-grade feature any billing team should treat as audited output. For practices comparing tiers on price, this distinction matters more than any other line item: the two lower tiers generate faster notes, but they do not close the coding loop. The revenue impact of that gap compounds with every encounter.

CPT Coding in Beta vs. Billing-Grade Accuracy Standards

Industry benchmarks for billing-grade CPT coding accuracy in production AI environments sit above 90% for systems that have completed clinical validation. "Beta" means a feature has not yet reached that threshold in real-world billing conditions. For a practice administrator signing off on a Groups contract, deploying a beta coding feature into an active billing workflow carries audit exposure, not just efficiency uncertainty.

The safer operational posture is to treat beta CPT coding as a roadmap item, not a current capability, and to evaluate vendors on what their coding accuracy looks like today, and whether that accuracy is applied consistently across every provider in the group, not just in isolated test cases. iScribe Health's E&M Coding Intelligence is designed precisely for this gap. Rather than treating coding as a downstream afterthought, iScribe surfaces Automated E&M Coding at the point of note completion, after the AI drafts the encounter summary, and before the note ever reaches the billing queue.

That timing matters: it is the moment when the clinical detail needed to justify a higher-complexity code is still fresh and correctable. The system is also built to improve coding consistency across providers, which means a high-volume practice or health system doesn't absorb one physician's systematic undercoding pattern while another bills accurately. The inconsistency itself is a revenue and audit risk that production-grade, non-beta coding intelligence is designed to eliminate.

The E&M Undercoding Gap Hidden from Scribe Pricing Pages

Tenpas and Dietrich's research in Exploratory Research in Clinical and Social Pharmacy frames undercoding as a Fermi problem: its financial magnitude can be estimated from known variables, specifically encounter volume multiplied by the revenue delta between the billed and warranted E&M level. The study found that billing losses from undercoding are real, measurable, and systematically ignored in standard pricing comparisons. The Milbank Memorial Fund's 2025 Primary Care Scorecard reinforces the broader context: primary care practices are already operating under compounding financial and operational pressure, and revenue leakage from documentation failures deepens that strain.

Key takeaway: Undercoding is a documentation architecture failure. When a note omits the medical decision-making complexity that would justify a 99215, the code that follows will be a 99214, and that difference across dozens of encounters per week is where the revenue disappears.

The practices most exposed are high-volume settings where clinicians regularly chart two or more hours outside of patient care time, exactly the environments where ambient AI documentation delivers its greatest impact.

When physicians are documenting under fatigue and time pressure, the MDM complexity that warrants a higher E&M level is the first thing to get compressed or omitted. iScribe Health's ambient listening and conversational AI captures that complexity in real time, during the encounter, so the note reflects what actually happened rather than what a tired physician reconstructed afterward.

Calculate Your Practice's Documentation Drag Score

• Estimate your undercoding rate. Tenpas and Dietrich demonstrate these losses are estimable from observable billing data, and audit studies consistently place undercoding rates between 10% and 20% for primary care practices
• Multiply by the average reimbursement delta between adjacent E&M levels for your payer mix
• Run that product across a full month, then annualize it

That annualized number reframes the conversation from "can we afford a $119/month scribe subscription" to "can we afford to keep absorbing a five- or six-figure annual revenue leak." It also reframes the vendor evaluation: the relevant question is not whether a tool generates faster notes, but whether it improves coding consistency, reduces undercoding systematically, and does both across every provider, not just for the physicians who happen to document most carefully on their best days. iScribe Health's E&M Coding Intelligence, integrated directly into a supported EHR workflow and active across every patient encounter, is built to close that gap at the source, not patch it after the claim has already been submitted at the wrong level.

Freed AI Alternatives and Comparisons - How to Evaluate When Sticker Price Isn't the Right Metric

Subscription price is the variable every pricing page is designed to make you focus on. It is also the variable least likely to predict whether an AI scribe investment actually improves your practice's financial position. MGMA's 2024 survey data showed the overwhelming majority of medical groups absorbing rising operating expenses, a cost environment in which per-seat price optimization is a narrow lever.

The administrators best positioned in that environment are those who frame documentation tool decisions around total cost of ownership rather than subscription line items alone, a framing that the cost-pressure data supports even where head-to-head outcome studies have not yet been published. One friction point that compounds this problem at the practice level: many AI scribe vendors, including those marketed as Freed alternatives, hide costs behind required sales calls or deploy enterprise-tier pricing structures that simply don't scale down to a one- or two-provider setup. A small independent practice can spend more time navigating an opaque pricing process than it would spend evaluating the tool itself.

That opacity inflates the true cost of switching and distorts any subscription-to-subscription comparison before it even begins.

"Small independent practices struggle to evaluate AI scribe pricing because many vendors (including Freed alternatives) hide costs behind sales calls or use enterprise-tier pricing structures that don't scale down to 1-2 provider setups."

1. iScribe Health - Best When Documentation Accuracy Drives Revenue Integrity

The three variables that determine whether an AI scribe pays for itself are EHR integration depth, post-note coding accuracy, and the hidden overhead of your status quo. Per-seat price is a distant fourth.

Key takeaway: A tool that saves a physician 90 minutes of after-hours charting but pushes notes through a browser extension into the wrong encounter field has not solved the problem; it has relocated it.

The status quo is not free. Scribe salaries, turnover, and the revenue lost to undercoded E&M encounters compound every month the decision is delayed. Most practices absorb that cost invisibly because it never appears as a line item on any invoice. The impact is sharpest in high-volume settings where clinicians are regularly charting two or more hours outside of patient care time, the precise environment where iScribe Health's ambient documentation delivers its most measurable return, realized across every patient encounter and every day of clinical practice.

There is a second hidden cost that no pricing page surfaces: AI scribes that struggle with complex, multi-thread conversations or specialty medical terminology force staff to invest manual correction time after every note generation. The sticker price of a cheaper tool shrinks when you account for the post-generation cleanup burden it silently transfers back to your team. iScribe Health's Ambient Listening and Conversational AI is built to handle that complexity at the point of capture, before the note ever reaches a clinician for review.

2. Freed AI - Best for Solo Physicians Prioritizing Speed Over Customization

Freed AI's flat monthly pricing and minimal onboarding make it attractive for independent physicians who want immediate documentation relief without IT involvement. Its value proposition centers on reclaimed after-hours charting time rather than enterprise-grade configurability. For solo or small practices, the ROI is real and fast. The key limitation: specialty-specific note customization and EHR deep-integration are constrained compared to platforms built for multi-provider or health system environments.

3. ScribePT - Best for Therapy and Rehab Practices Evaluating True Total Cost of Ownership

ScribePT frames AI scribe evaluation around total cost of ownership, factoring in implementation, QA overhead, compliance maintenance, and ongoing support rather than just subscription fees. This makes it a strong fit for physical therapy and rehab practices that need specialty-tuned documentation and want to avoid hidden cost surprises post-deployment. The tradeoff is that its specialty focus means it's a poor fit for multi-specialty or primary care environments seeking a single unified platform.

4. OmniMD - Best for Clinic Administrators Who Need ROI Justification Before Buying

OmniMD offers an interactive ROI calculator that lets clinic administrators model charting time saved, productivity gains, and projected revenue growth before committing to a purchase. This makes it particularly valuable when procurement decisions require internal financial justification or board-level sign-off. It reframes the Freed AI pricing conversation from cost to measurable return. The limitation: the calculator's outputs are estimates, and actual ROI depends heavily on provider adoption rates and EHR workflow fit.

5. Sully AI - Best for Health Systems Comparing AI Scribes on Clinical Workflow Depth

Sully AI positions itself as a comprehensive clinical AI layer, addressing not just transcription but ambient intelligence across the full encounter workflow. For health systems evaluating alternatives to Freed AI pricing on a per-seat enterprise basis, Sully's depth of EHR integration and security compliance posture makes it a credible contender. It's best suited when the evaluation metric is workflow transformation, not just note generation speed. The tradeoff: higher complexity and longer deployment timelines compared to plug-and-play consumer-grade tools.

Related Reading

• Best Medical Dictation Software
• Medical Coding Automation
• EHR Documentation Burden
• AI Medical Dictation Data Security

Next steps

If your evaluation process keeps circling back to per-seat price while your billing team quietly absorbs undercoded encounters every month, the path forward starts with treating documentation architecture as a revenue decision, not a subscription comparison. Start with our AI medical scribe.

The three-tier pricing trap covered earlier makes this concrete: the only Freed plan that includes both unlimited notes and EHR integration costs $119 per month, and even that plan pushes text through a browser extension rather than writing structured data to discrete EHR fields. That architecture gap means coding accuracy downstream depends on what the extension can see in a browser window, not on field-mapped clinical data. Separately, the E&M undercoding analysis in this post establishes that the revenue leak from one systematically undercoded code level, multiplied across daily encounter volume and annualized, routinely dwarfs any monthly subscription delta.

Together, those two findings point to a single action: evaluate an AI scribe that closes both gaps at once, combining native EHR integration with coding intelligence applied at the point of note completion, before a single claim leaves the practice.

Start with an AI medical scribe built for that standard. From there, run the encounter audit described in Step 1 of the evaluation section above, bring the annualized undercoding number to your CFO, and the subscription conversation stops being about price.

Frequently Asked Questions

What's the real difference between the Core and Premier plans, is the $40/month jump worth it?

The Core plan at $79/month removes the 40-note cap and adds a template builder and AI clinician assistant, but every note still requires manual copy-paste into your EHR. Premier at $119/month adds EHR integration, ICD-10 coding assistance (beta), visit summaries, patient instructions, and referral letters, meaning it's the only tier that eliminates that manual transfer step entirely. Whether the $40 delta is worth it depends on your encounter volume and staff wage rates, since the per-encounter labor overhead from manual copy-paste compounds across a full month of visits.

Does Freed AI's EHR integration actually connect natively to my EHR system?

No, Freed's EHR integration is delivered via a Chrome browser extension, not a native API or FHIR connection to your EHR's data layer. The extension pushes text into visible browser fields rather than writing structured, field-mapped data at the database level, which means discrete diagnosis, procedure, and visit-type fields that drive billing accuracy may not populate automatically. Practices running Epic or Athenahealth may also need IT to whitelist the extension under enterprise browser policy before any physician can use it, a process the post notes can stretch weeks.