Automation Insights: 26 Million Healthcare Calls Analyzed

Refill Requests vs. Appointment Calls: What 26 Million Healthcare Calls Reveal About Automation

Not all patient calls are created equal. Some can be fully automated without any loss in care quality. Others require clinical judgment that no algorithm should replace. The difference between a well-run medical practice and one drowning in phone chaos often comes down to one thing: knowing which calls fall into which category — and having the infrastructure to handle each appropriately.

At CallMyDoc, we have processed over 26 million patient calls across 38 states, categorized into 12 distinct clinical request types. That dataset — spanning single-provider family practices to 1,354-location enterprise health systems — gives us an unusually clear picture of what patients actually call about, how long each call type takes to resolve, and which ones can be safely automated without clinical risk.

This article breaks it all down: the real percentages, the operational cost of each call type, and the staffing math that should drive your automation decisions.

The 12 Clinical Call Categories: A Data-Driven Breakdown

When practices think about phone automation, they tend to lump all calls into a single bucket. That is a mistake. The call types that consume 60–70% of your phone volume are fundamentally different from the remaining 30–40% — in complexity, liability profile, and automation potential.

Here is what 26 million calls reveal about the actual distribution of patient call types in medical practices:

Fully Automatable Call Types (60–70% of Total Volume)

These call categories follow predictable workflows, require no clinical interpretation, and can be resolved with structured routing, AI transcription, and patient self-service tools.

Combined: These seven categories account for roughly 60–70% of all inbound calls at a typical medical practice. Every one of them follows a repeatable workflow that clinical communication infrastructure can handle without human intervention — or with minimal human touchpoints.

Calls Requiring Human Judgment (30–40% of Total Volume)

These call types involve clinical interpretation, patient-specific decision-making, or negotiation that AI should support but never replace.

Here is the critical distinction: even for this 30–40%, AI still plays a vital role. CallMyDoc’s infrastructure handles the capture, transcription, categorization, and routing for every single call — including these complex ones. The AI does everything except the clinical decision itself. That is the human-in-the-loop model that separates clinical communication infrastructure from generic AI answering services.

The Refill Request Deep Dive: Highest-ROI Automation Target

If you could only automate one call type, prescription refill requests should be your first target. Here is why the data is so compelling.

The Traditional Refill Workflow Is Broken

In most practices, a single refill request touches three to four staff members and takes 15 to 30 minutes of aggregate labor:

1. Front desk answers the call (3–5 minutes): Takes patient name, medication, pharmacy info. Often interrupted by in-office patients.
2. Message routed to nursing staff (5–10 minutes of waiting + 3–5 minutes of review): Nurse reviews chart, checks last fill date, confirms medication is appropriate for refill.
3. Provider reviews and approves (2–5 minutes): Provider interrupted from patient encounter to review refill request, sign off.
4. Staff calls pharmacy or patient back (3–5 minutes): Confirmation call, sometimes phone tag if pharmacy line is busy.

Multiply that by 30 to 50 refill requests per day — which is typical for a multi-provider primary care practice — and you are looking at 7 to 25 hours of aggregate staff time consumed daily by refills alone.

The CallMyDoc Refill Workflow

With CallMyDoc’s e-prescription and refill infrastructure, the workflow compresses dramatically:

1. Patient calls → AI identifies the patient by date of birth and matches to their chart
2. AI transcribes the request → Medication name, dosage, pharmacy, and any patient notes are captured verbatim
3. Structured task created in EHR → Refill request appears as a documented task with full context, routed directly to the prescribing provider
4. Provider approves on mobile → One tap, under 30 seconds, from anywhere

Total staff involvement: near zero. Total provider time: 30 seconds. Total patient wait: minutes instead of hours or days.

Real-World Impact: Hudson Headwaters Health Network

Hudson Headwaters — a community health network spanning 89 offices across rural New York — deployed CallMyDoc across their system and saw 68.1% of business-hour calls handled automatically. Refill requests were among the highest-impact categories. Nursing staff who had been spending significant portions of their shifts on the phone were freed to return to bedside care — the work they were trained and hired to do.

With 7,532 monthly calls flowing through CallMyDoc, after-hours calls were handled 3× faster, and 41.6% of routine requests — heavily weighted toward refills and scheduling — were resolved entirely within the platform without any staff involvement.

The Appointment Call Deep Dive: Highest-Volume Automation Target

While refills deliver the highest per-call ROI, appointment scheduling is the highest-volume call type at 25–30% of all inbound calls. Automating scheduling produces the single largest reduction in total phone workload.

Why Scheduling Calls Consume So Much Staff Time

A traditional scheduling call averages 5 to 10 minutes because of the back-and-forth required:

• Verifying patient identity and insurance
• Checking provider availability across multiple days and times
• Navigating patient preferences (“I can only come in the afternoon”, “I need to see Dr. Smith specifically”)
• Confirming the appointment and providing instructions

At 200 calls per day — a moderate volume for a multi-provider practice — scheduling alone generates 50 to 60 calls requiring 4 to 10 hours of staff time daily.

40-Second Self-Scheduling

CallMyDoc’s Schedule My Patient feature lets patients book appointments in under 40 seconds — no patient portal login required, no staff involvement needed. The system identifies the patient, presents available slots based on provider, visit type, and location, and confirms the booking. The appointment appears directly in the practice’s scheduling system.

The downstream impact extends beyond the initial call:

• No-show reduction: CallMyDoc’s dual automated reminders (voice, text, and email at 7 days and 1 day before) reduce no-shows by up to 40%
• Revenue protection: Every empty appointment slot represents $150 to $350 in lost revenue depending on the visit type. For a practice with 10 no-shows per week, that is $78,000 to $182,000 in annual revenue leakage
• Staff redeployment: Hours previously spent on scheduling calls become available for revenue-generating activities — insurance verification, care coordination, patient engagement

Real-World Impact: Castle Hills Family Practice

Castle Hills Family Practice in San Antonio — a two-location practice handling 5,222 monthly calls — achieved a 50% reduction in phone workload after deploying CallMyDoc. Scheduling and refill automation accounted for the bulk of that reduction. In just 90 days, the practice served 1,938 unique patients through the platform, and 51.9% of their calls came after hours — all of which were documented and routed without any staff overtime.

The Symptom Call Challenge: Why These Cannot Be Fully Automated

When patients call with symptoms — “I have had chest pain since this morning,” “My child has a 104-degree fever” — the stakes change fundamentally. These calls represent 7–9% of volume, but they carry disproportionate clinical and legal risk.

Why Full Automation Is the Wrong Approach

Some AI platforms advertise the ability to “triage” patient symptoms autonomously. This creates three problems:

1. Malpractice liability: If an autonomous AI system tells a patient their symptoms are not urgent and they later experience a cardiac event, the practice is exposed to significant liability. Courts have not established clear precedent for AI clinical decision-making, which means the practice bears the risk.
2. Clinical nuance: A 45-year-old woman reporting “heartburn” requires different assessment than a 25-year-old male with the same complaint. Context from the patient’s chart — medications, history, recent procedures — matters enormously.
3. Patient trust: Patients calling with symptoms want to feel heard by their care team, not processed by a bot.

The Human-in-the-Loop Model

CallMyDoc’s approach to symptom calls is deliberately designed as human-in-the-loop AI — the system maximizes what AI does well while preserving human clinical judgment where it matters:

• AI captures exact words: The patient’s description is transcribed verbatim — no paraphrasing, no message-pad abbreviations, no lost details
• AI determines urgency level: Based on keywords, tone, and clinical context from the patient’s chart, the system categorizes urgency and routes accordingly
• AI routes with chart context: The provider receiving the notification sees the transcription alongside the patient’s relevant chart information — medications, conditions, recent visits
• AI timestamps everything: Every interaction is logged with timestamps in the EHR, creating a complete documentation trail for compliance and malpractice protection
• Humans make the clinical decision: The provider — not the AI — determines the appropriate response

This model is why CallMyDoc has maintained zero malpractice incidents across 26 million calls. The AI accelerates every step around the clinical decision without replacing the decision itself.

Staffing Implications of the 60/40 Split

Understanding the automatable-vs-clinical split transforms how practices should think about staffing. The math is straightforward and significant.

The Calculation

Consider a practice handling 200 inbound calls per day (moderate for a multi-provider clinic):

• 60% automatable: 120 calls × 7 minutes average handle time = 840 minutes = 14 hours of staff time per day
• 40% requiring human judgment: 80 calls × 8 minutes average = 640 minutes = 10.7 hours of staff time per day

Automating the 60% means recovering 14 hours of staff labor every single day. Over a year, that is approximately 3,640 hours — equivalent to nearly two full-time employees dedicated exclusively to answering phones.

But It Is Not Just About Headcount

The real staffing impact is qualitative, not just quantitative:

• Reduced burnout: 30–50% of medical practice staff time is consumed by inbound calls. Automating the routine ones lets staff focus on work that requires their training and judgment.
• Better patient experience for complex calls: When staff are not rushing through a scheduling call to answer the next ringing line, they have time to give thoughtful attention to the patient with a symptom concern or test result question.
• After-hours coverage without overtime: Castle Hills data showed 51.9% of calls came after hours. Without automation, those calls become morning voicemail backlogs or expensive after-hours answering service charges.

Enterprise Scale: Millennium Physician Group

At enterprise scale, the staffing impact compounds dramatically. Millennium Physician Group — with 200+ locations, 900+ providers, and 34,492 monthly calls flowing through CallMyDoc — achieved 52.1% business-hours resolution within 1.8 hours across their 1,354 dashboards. At that volume, even a 5% improvement in automation rates translates to thousands of recovered staff hours per month.

How IVR Design Changes by Practice Type

One of the most overlooked factors in medical call automation is IVR design — the menu structure patients navigate when they call your practice. A poorly designed IVR wastes patient time, routes calls inefficiently, and drives up abandonment rates. But here is what most practice administrators do not realize: the optimal IVR design varies dramatically by specialty, and it should be driven by your actual call mix data.

CallMyDoc configures IVR routing differently depending on whether a practice is refill-heavy or appointment-heavy — and the difference in outcomes is substantial.

Refill-Heavy Practices (Psychiatry, Pain Management, Endocrinology)

Specialties where medication management dominates the clinical workflow require an IVR architecture that front-loads refill capture. These practices configure sub_type_routing to enable options H (Medication), I (New Prescriptions), J (Prescription Refill), C (Scheduling), and D (Non-Urgent Other). This routing structure gives medication-related calls their own dedicated pathways rather than funneling them through a generic “leave a message” option.

These practices use phrase group 62-J with a targeted refill capture prompt that identifies the specific medication, dosage, pharmacy, and last fill date upfront — before the call reaches any staff member. This structured capture eliminates the back-and-forth that typically adds 5–10 minutes to each refill call.

The IVR design front-loads refill capture because 35–45% of call volume in these specialties is medication-related — combining refills, medication questions, and new prescription requests. For psychiatry, pain management, and endocrinology practices, a single well-designed refill menu option can eliminate 20–30% of total front-desk call handling. That is not a marginal improvement; it is the difference between needing three front-desk staff and needing two.

Appointment-Heavy Practices (OB/GYN, Orthopedics, Dermatology)

Specialties where scheduling dominates call volume need a fundamentally different IVR approach. These practices use a streamlined configuration with override_call_type: Patient and sub_type_routing: 0 (disabled). Fewer menu layers are needed because the majority of calls are scheduling-related.

The IVR bypasses the call-type selection menu entirely and routes directly to scheduling or message-taking. This means the patient hears fewer prompts, makes fewer button presses, and reaches the right destination faster. For appointment-heavy specialties, self-scheduling (under 40 seconds) produces the highest ROI because appointment calls represent 40–50% of their volume.

Why this matters: One-size-fits-all IVR designs waste patient time and route calls inefficiently. A psychiatry practice that uses the same IVR as a dermatology clinic is forcing 35–45% of its callers through a menu structure optimized for a call type that represents only 15–20% of its volume. Practices should configure their phone infrastructure based on their actual call mix — and that mix varies dramatically by specialty. The data should drive the design, not the other way around.

The Automation Opportunity: Real Savings by Call Type

Understanding the theoretical automation potential is one thing. Seeing the actual dollar savings by call type makes the business case concrete. The following table breaks down current automation rates, achievable targets, and the annual cost recovery for a typical five-provider practice:

Several insights emerge from this data that challenge conventional assumptions about medical call automation:

The largest single savings category is routine refill requests — not appointment booking. This surprises most practice administrators, who assume scheduling automation delivers the biggest financial impact because it has the highest call volume. But the math tells a different story.

Refill automation delivers more savings per call because the current automation rate is so low (20%) and the manual workflow is so labor-intensive. Each manually processed refill touches 3–4 staff members and consumes 15–30 minutes of aggregate labor. Closing the gap from 20% to 60% automation on a high-cost-per-call category produces outsized savings.

Appointment confirmations, by contrast, already have higher automation rates (60%) — many practices already use some form of automated reminders. So the marginal improvement from 60% to 90% is smaller in both percentage terms and absolute dollar impact.

The $52,000 to $85,000 annual range represents staff time freed for patient-facing activities, not headcount reduction. Practices that automate these call types typically redeploy staff to revenue-generating work — insurance verification, care coordination, patient outreach — rather than eliminating positions. The recovered hours become an investment in practice growth rather than a cost-cutting measure.

7 Key Takeaways from the Data

After analyzing the full spectrum of refill and appointment call data, seven conclusions stand out — several of which run counter to what most practice administrators assume:

1. Refills win on cost-per-resolution. The manual refill workflow involves 3–4 staff touchpoints and 15–30 minutes of aggregate labor. Automated refill capture reduces this to a 30-second provider approval. No other call type offers this dramatic a compression ratio.
2. Appointments win on volume reduction. At 30–40% of all calls, scheduling is the single largest phone workload category. Even modest automation rates produce the biggest absolute reduction in total call handling minutes.
3. 30% of refill calls generate secondary appointment calls. When a patient calls for a refill and the provider’s approval requires a follow-up visit (“I’ll approve a 30-day supply, but you need to come in”), that refill call spawns an appointment call. Practices that automate refills see a cascading reduction in scheduling call volume.
4. The biggest automation savings come from refill request capture, not appointment scheduling. This is counterintuitive because scheduling has higher volume. But refill automation closes a wider gap (from 20% to 60%) while scheduling automation improves on an already-decent baseline (from 15% to 50%).
5. Specialty determines which call type to automate first. Psychiatry and pain management practices should prioritize refill automation (Sub-Type J). OB/GYN and orthopedic practices should prioritize self-scheduling (Sub-Type C). The IVR configuration should follow the data.
6. After-hours refill calls are more urgent than daytime refill calls. Patients calling for refills at 9 PM have typically already missed a dose. The PM collection mode should route refill requests for time-sensitive medications (insulin, blood pressure, psychiatric) with higher urgency flags.
7. Documentation quality matters more for refills than scheduling. A scheduling error means a patient shows up on the wrong day — inconvenient but fixable. A refill error — wrong medication, wrong dosage, wrong pharmacy — creates clinical risk. This is why CallMyDoc separates Sub-Type H (Medication questions) from Sub-Type J (Prescription Refill) in its routing: the downstream consequences of errors are fundamentally different.

What This Data Means for Your Practice

The 60/40 split is not just an interesting statistic — it is an operational blueprint. Here is how to apply it:

Step 1: Audit Your Call Mix

Before investing in any automation, understand your practice’s specific call distribution. Track call types for two weeks. Most practices discover their numbers closely match the 26-million-call averages, but specialty practices may skew — dermatology tends to have higher scheduling volume; cardiology tends to have more symptom calls and test result inquiries.

Step 2: Automate Refills First

Refills deliver the highest ROI per call because the manual workflow is so labor-intensive. If your providers are still being interrupted to approve routine refills, that is your first and most impactful automation target.

Step 3: Deploy Self-Scheduling

Scheduling automation produces the largest absolute reduction in call volume. Combined with automated appointment reminders, this eliminates both inbound scheduling calls and outbound confirmation calls.

Step 4: Build Infrastructure for the 40%

The calls that require human judgment still benefit enormously from proper infrastructure — AI transcription, intelligent routing, chart context, and complete documentation. The goal is not to automate clinical decisions but to ensure every piece of information reaches the right person as fast as possible.

Step 5: Measure and Optimize

CallMyDoc’s KPI dashboard tracks call volume, resolution time, and staff efficiency in real time. After deployment, monitor your automation rates and identify remaining bottlenecks. Hudson Headwaters reached 68.1% automatic handling; your practice may reach higher or lower depending on your call mix and specialty.

The Bottom Line: Infrastructure That Knows the Difference

The practices that thrive operationally are not the ones that automate everything indiscriminately or the ones that refuse to automate at all. They are the ones that have clinical communication infrastructure intelligent enough to know the difference — that routes a refill request to a 30-second mobile approval while ensuring a symptom call reaches the right provider with full chart context in minutes.

That distinction — built on 26 million calls, zero breaches, zero lost calls, and a track record spanning 38 states — is what separates a communication platform designed for healthcare from a generic AI answering service.

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