Here’s a number that should bother you: a study of 7,000 calls across 22 medical practices found that 42% of incoming calls go unanswered during business hours. Not after hours. Not on weekends. During the workday, when your front desk is supposedly available.
If you manage a practice, you already know this intuitively. You see the phones ringing while your receptionist is checking in a patient, pulling insurance cards, and fielding a question from the billing department simultaneously. You hear the hold music playing for the third caller in the queue. You know that some percentage of those people are hanging up and calling the orthopedic group down the road instead.
1. A virtual receptionist software can reduce administrative burden and be a cost-effective solution
2. Which tasks a virtual receptionist can take on for your practice
3. How to tell if call deflection and automated messaging is right for your practice
What you might not know is what those missed calls cost. The National Institutes of Health estimates each missed appointment slot represents roughly $200 in lost revenue. Missed calls are the leading cause of missed appointments, and missed appointments cost the U.S. healthcare system over $150 billion annually. For a mid-sized practice, even a modest 20% call abandonment rate can quietly drain six figures in annual revenue.
A virtual medical receptionist is the fix. But the term has gotten confusing—it now covers everything from a person in the Philippines answering your phones to an AI agent that books appointments by voice. These are wildly different solutions with different costs, capabilities, and failure modes. This guide breaks down what actually exists, what it costs, and what works for which type of practice.
Forget the fluffy definitions. A virtual medical receptionist handles the tasks that keep your front desk underwater but don’t require clinical judgment. Specifically:
The point isn’t to replace your receptionist. It’s to stop burying them under a pile of repetitive calls so they can actually do the parts of their job that require a human brain—handling a frustrated patient in the waiting room, coordinating a complex referral, explaining a confusing billing statement face-to-face.
At a typical 10-provider practice, front desk staff might field 300-500 calls per day. The majority are routine. Somebody needs an appointment. Somebody needs a refill. Somebody needs to know if you take Blue Cross. These are important interactions, but they don’t require the person who’s also managing your waiting room. Learn more about the role of virtual medical receptionists.
While it may sound new-agey, the virtual medical receptionist, is a transformative approach (powered by platforms like OhMD) to make complicated communication workflows, simple. These AI assistants redefine patient interaction through automation and streamlined communication. By integrating OhMD’s tools, practices can automate the collection of patient data, schedule appointments, and even handle routine inquiries, all without a single phone call. This shift from traditional phone-based systems to a more dynamic, digital interface significantly reduces the administrative burden on your staff.
Furthermore, virtual receptionists are not just about efficiency; they are about enhancing the patient experience. Instead of getting angry with wait times, patients enjoy a more personalized and immediate interaction.
Gone are the days of staff being tied in 1-to-1 phone calls. While the virtual medical receptionist works, staff can be responding to many other patients at the same time. Patients provide their information and receive updates in a more convenient, less intrusive manner. This level of accessibility and ease not only elevates patient satisfaction but also fosters a stronger trust in your practice.
Adopting a solution like this is more than just a technological upgrade; it’s a strategic move towards operational excellence. It empowers your practice to handle high volumes of patient interactions seamlessly while ensuring accuracy and patient privacy. By embracing this innovation, healthcare practices can significantly reduce wait times, enhance data management, and provide a more patient-centered service, ultimately leading to a more efficient and effective healthcare delivery system.
This is where most guides get it wrong. They lump everything together. In reality, there are three distinct categories, and they serve different practices at different price points.
This is the original model. A trained person, working remotely (often from a call center or home office), answers your phones using your practice’s scripts and protocols. Companies like WellReceived, Davinci Virtual, and My Mountain Mover provide this service.
Best for: Solo practitioners and very small practices (1-3 providers) who want a human voice on every call and have relatively low call volume—under 100 calls per day. Also a good fit if your patient population skews older and you’re concerned about patient comfort with automated systems.
The tradeoff: You’re paying for a person’s time, which means per-minute or per-call pricing that scales linearly with volume. A practice handling 200+ calls per day will find this model expensive. And because these are generalists (not your staff), they can handle scripted scenarios but struggle with anything that requires real knowledge of your practice, your providers, or your clinical workflows.
These are software systems—voice AI agents, chatbots, or automated messaging platforms—that handle patient interactions without a human in the loop. They use natural language processing to understand requests and take action: booking appointments, answering FAQs, processing refill requests. Companies in this space include Simbie AI, My AI Front Desk, Hyro, and Assort Health.
Best for: High-volume practices (5+ providers) where the cost of human receptionists would be prohibitive and most calls follow predictable patterns. Also a strong fit for practices that want 24/7 coverage without overnight staffing.
The tradeoff: Pure AI systems handle routine calls well, but patients sometimes hit a wall. They ask something the AI wasn’t trained on, or the situation is emotionally sensitive (a new cancer diagnosis, a billing dispute, a scared parent), and the system either loops unhelpfully or dumps them into a voicemail. The worst-case scenario isn’t that the AI can’t handle a call—it’s that the AI thinks it handled a call when it actually didn’t.
This is the newer model, and in my view, the one that actually solves the problem rather than just shifting it. A hybrid system uses AI to handle routine calls autonomously but routes anything complex, sensitive, or ambiguous to your actual staff—with full context of what the AI already discussed with the patient.
OhMD’s Nia is built this way. The AI answers the phone, handles scheduling, refills, and common questions. If a patient mentions chest pain, asks about a test result, or says something the AI isn’t confident about, the conversation gets passed to your team with a full transcript. Your staff picks up where the AI left off, not from scratch.
Best for: Multi-provider practices and medical groups that need to significantly reduce call volume but can’t afford to lose patients in the gaps between what AI handles well and what requires human judgment. Also the right model for practices in specialties where patient conversations are frequently nuanced—oncology, fertility, complex orthopedics.
The tradeoff: Your staff is still involved, which means you’re not fully “hands-off.” The system reduces their call burden dramatically (practices using OhMD report 68% fewer staff-answered calls), but it doesn’t eliminate the need for trained front desk staff entirely. That’s actually a feature, not a bug—but it means this isn’t a replacement for your team. It’s a force multiplier.
| Remote Human | AI-Only | AI + Human Hybrid | |
| Monthly cost (est.) | $800–$3,000+ | $200–$1,500 | $300–$1,200 |
| Cost per call | $0.75–$1.50/min | Flat or usage-based | Flat or usage-based |
| Scales with volume | Cost rises linearly | Cost rises linearly | Cost rises linearly |
| 24/7 availability | Depends on plan | Yes | Yes (AI); staff hours for escalations |
| Handles complex/sensitive calls | Somewhat (scripted) | Poorly | Yes (routes to staff with context) |
| EHR integration | Rare | Some vendors | Yes (OhMD: 85+ EHRs) |
| HIPAA compliance | Varies by vendor | Varies by vendor | Built-in (platform-level) |
| Patient satisfaction risk | Low (human voice) | Moderate (AI limitations) | Low (AI + human fallback) |
| Time to deploy | 1–2 weeks | Days to weeks | Weeks (EHR integration) |
I’ve watched practices make this decision dozens of times. The ones that end up happy focused on five things. The ones that ended up switching vendors within a year focused on the wrong things (usually the demo and the price).
If your virtual receptionist can’t see your schedule, it can’t book appointments accurately. If it can’t write back to your EHR, someone on your team is manually entering everything the AI just collected. That defeats the entire purpose. Ask specifically: does it read and write to my EHR, or does it just display a widget next to it?
This matters more than people realize. A system that integrates with athenahealth or eClinicalWorks at the API level can check provider availability in real time, book directly into open slots, and push patient information into the chart. A system that doesn’t is basically a fancy message-taker.
Every vendor will tell you they’re HIPAA compliant. Fewer can explain how. You want a platform where compliance is built into the architecture—encrypted data transmission, signed BAAs, access controls, audit logs—not bolted on as an afterthought. Ask to see their BAA before you sign anything. If they hesitate, walk away.
The most important moment isn’t when the AI answers a routine call. It’s what happens when the AI encounters something it shouldn’t handle alone. Does the patient get dumped to voicemail? Transferred cold to a general line? Or does the system pass the conversation to a specific staff member with full context—what the patient said, what they need, and what’s already been discussed?
This is the difference between a system that frustrates patients and one that actually improves their experience. Coastline Orthopaedic Associates saw their call abandonment rate drop by 63% after implementing a hybrid approach, largely because patients who needed human help actually got it—quickly and with context—instead of bouncing between menus.
Some vendors will tell you they “answer 100% of calls.” That’s easy—a voicemail box answers 100% of calls too. The metric that matters is resolution rate: what percentage of calls were actually handled without requiring your staff to intervene? And of the ones that did escalate, did your staff have enough context to resolve them efficiently?
At Heart and Vascular Care, a cardiology group, AI handles over 60% of routine patient calls without staff involvement. That’s 60% fewer interruptions for a front desk team that was already stretched thin. The other 40% still reach staff—but with notes, transcripts, and context, so the average handling time dropped too.
This is a blindspot for a lot of practices. Voice-only AI solves one channel. But patients increasingly want to text their doctor’s office—especially younger demographics and working parents who can’t make phone calls during business hours. A virtual receptionist that handles calls and texts from a unified inbox gives your staff one place to manage everything, instead of toggling between a phone system, a texting platform, a web chat tool, and their EHR.
Let’s talk real numbers, because most guides dodge this.
| Option | Small Practice (1–3 providers) | Mid-Size (4–10 providers) | Large Group (10+) |
| Full-time in-house receptionist | $35,000–$45,000/yr + benefits | 2–4 staff: $80K–$180K/yr | $250K–$500K+ /yr |
| Remote human receptionist | $500–$1,200/mo | $1,500–$3,000/mo | $3,000–$8,000+/mo |
| AI-only platform | $200–$500/mo | $500–$1,200/mo | $1,000–$3,000/mo |
| Hybrid AI + human-in-the-loop | $300–$600/mo | $500–$1,000/mo | Custom pricing |
The comparison that matters isn’t virtual receptionist vs. no receptionist. It’s virtual receptionist vs. hiring another human to answer phones. At $40,000-$50,000 per year fully loaded (salary, benefits, training, turnover), a second or third receptionist is a significant expense. A platform that handles 60-70% of your call volume for $500-$1,000 per month is a fundamentally different cost structure.
And that’s before you factor in the revenue side. If your practice is missing 42% of calls and each missed appointment slot costs $200, the math on a $6,000-$12,000 annual software investment becomes very straightforward.
I want to be honest here, because vendors love to say “go live in 48 hours” and that’s almost never the full story.
A remote human receptionist service is genuinely fast to set up. You give them your scripts, your schedule, and your routing rules. They start answering calls within a week or two. The limitation is that they can’t do much beyond following your scripts.
An AI or hybrid system takes longer—typically 2-4 weeks for a full deployment, and sometimes longer if your EHR integration is complex. That time is spent configuring the AI to understand your specific scheduling rules, provider availability, and common patient questions. It’s also spent training your staff on how the handoff works and what the new workflows look like.
The practices that have the smoothest implementations do three things:
Set a 30-day check-in. Review call logs, escalation rates, and patient feedback. Adjust scripts and routing rules based on what you see.
Audit their call volume first. Track two weeks of calls: how many, what time, what the patient needed. This tells you exactly how much of your volume is automatable.
Start with a subset of calls. Don’t flip the switch on everything at once. Start with scheduling calls or after-hours overflow. Let the system prove itself, then expand.
I should be honest about this too. A virtual medical receptionist isn’t the right solution for every practice.
If you’re a solo practitioner seeing 10-15 patients a day and your call volume is manageable, the complexity of implementing a new system probably isn’t worth it. Your existing receptionist (or your own phone) is fine.
If your problem isn’t call volume but call complexity—say you’re a psychiatric practice where most calls involve sensitive clinical conversations—AI isn’t going to help much. You need more humans, not fewer.
And if your EHR is so locked down that no third-party tool can integrate with it, you’ll end up with a virtual receptionist that creates more manual work than it eliminates. Check your EHR’s integration capabilities before you start vendor conversations.
Features like Autopilot, Virtual Phone Assistant and two-way texting can elevate your practice.
See how OhMD can innovate your office!
Frequently Asked Questions
It depends on the type. Remote human services typically charge $0.75–$1.50 per minute or $500–$3,000+ per month depending on call volume. AI-powered platforms are usually $200–$1,500 per month on a flat-rate basis. Hybrid AI-plus-human platforms like OhMD fall in the $300–$1,200 per month range for most practices. Compare this to a full-time in-house receptionist at $35,000–$50,000 per year plus benefits.
They should be, but not all are. Look for platforms that offer a signed Business Associate Agreement (BAA), encrypt data in transit and at rest, maintain audit logs, and have access controls. A vendor claiming HIPAA compliance without a BAA is a red flag. Purpose-built healthcare platforms are generally safer bets than general-purpose answering services that have added a “HIPAA compliant” label.
For routine calls—scheduling, refills, office hours—most patients prefer speed over a human voice. A recent JAMA study found patients actually preferred AI-generated responses to physician responses 78.6% of the time because they were faster and more thorough. Where patients get frustrated is when AI can’t handle their specific issue and there’s no clear path to a real person. That’s why the handoff mechanism matters more than the AI itself.
A traditional answering service takes messages. A virtual medical receptionist resolves requests. The difference is action: a virtual receptionist can book an appointment into your EHR, process a refill request, or send the patient a text with pre-visit instructions. An answering service writes down what the patient said and passes it along for your staff to act on later.
It depends on the vendor and your EHR. Some platforms integrate with a wide range of systems—OhMD, for example, connects with 85+ EHRs including athenahealth, eClinicalWorks, ModMed, Elation, and DrChrono. Others are limited to a handful. Always confirm bidirectional integration (reads and writes to your EHR) before committing, and ask specifically about your system.
Remote human services: 1–2 weeks. AI or hybrid platforms: 2–4 weeks, depending on EHR integration complexity and how customized your scheduling rules are. Some vendors offer a phased rollout where you start with after-hours coverage or a single call type and expand over time.
This varies dramatically by vendor and it’s the most important question to ask during a demo. The best systems route the call to a specific staff member with a full transcript of the conversation so far. The worst dump the patient to a generic voicemail. Ask the vendor to show you exactly what happens on an escalated call—not just the happy path.
Yes. A virtual medical receptionist handles phone-based and text-based interactions. You still need someone to greet patients in person, manage the waiting room, handle check-in and check-out, and deal with situations that require a physical human presence. The goal is to free that person from the phone so they can do their in-person job well—not to eliminate the role entirely.
