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AI, patient stories, and the decisions shaping tomorrow’s care.

Specialty drugs are often hailed as miracles of modern medicine, lifesaving therapies for patients with cancer, rare diseases, autoimmune conditions, and more. But behind every prescription lies a hidden maze of bureaucracy. But before a patient can even begin treatment, they must navigate a fragmented system of prior authorizations, benefit checks, enrollment forms, and pharmacy coordination, mostly over the phone or by fax.
 

A patient might wait weeks just to hear back on insurance approval. Others give up entirely. And every missed refill or abandoned therapy represents lost time, revenue, and in some cases, worsening disease.
 

Why is access to these critical medications still so chaotic? And how can the system be re-engineered to serve patients, providers, and manufacturers better? Let’s get into the throes of specialty pharma operations to understand.
 

---

## Why Patients Give Up Before the Drug Even Ships

Before a specialty medication can be dispensed, it almost always requires benefit verification and prior authorization (PA). These aren’t simple checks, they're complex, payer-specific processes that can take days or weeks. Each insurance plan demands different forms, documentation, and clinical criteria. And despite the push toward digital tools, nearly **50% of PAs are still submitted by phone or fax**.
 

One physician described a typical case: four separate calls to four different reps, a 20-minute hold each time, and multiple follow-ups just to correct a missing field. It’s not uncommon for clinics to spend **30-45 minutes per submission**, often chasing faxes or re-sending documents that were “never received.”

And the volume is staggering. The average physician’s office processes **39-41 prior authorizations per week**, consuming nearly **13 hours of staff time,** per physician. Many practices have hired full-time staff just to manage PAs. Others lean on nurses and assistants, who must spend their day on hold instead of with patients.
 

While the cost of these inefficiencies is enormous. **$93 billion a year** is spent on PA-related admin across insurers, physicians, and pharma companies; The real damage is to access: **40% of patients abandon therapy** when a PA is required. And those who stay wait an average of **29 days** to get their medication. 
 

If the insurance roadblock takes this long to clear, what happens when the process hits the provider's side?

## 84% of Providers Say This Is Unsustainable. They’re Right

Once a doctor prescribes a specialty medication, they or their staff are responsible for enrolling the patient in the appropriate hub or specialty pharmacy. But with **no standardization** across programs, each drug can have its own forms, processes, and online portals. A GI clinic managing multiple biologics might juggle **dozens of logins** for different manufacturer hubs. 

This leads to a cascade of errors. One missing signature or unchecked box can stall a case for days. Hubs fax back forms with red ink, or call the provider’s office repeatedly to collect additional info. In the meantime, the patient waits.
 

Some providers get so frustrated that they bypass hub services entirely. They try to manage enrollment, PA, and pharmacy coordination in-house, even if they lack the time or resources. Others simply avoid prescribing specialty meds unless absolutely necessary. In one survey, **84% of physicians called specialty med admin a high or extreme burden**. And in smaller practices, nurses spend up to **10% of their workday** handling insurance paperwork.

Even when hubs or pharma companies try to help, through field reps or reimbursement support, it often falls short. COVID reduced in-office visits by reps, and the gap in hands-on support is still felt. Meanwhile, physicians are left chasing updates, often with **no real-time visibility** into where the patient is in the process.

If providers are struggling to coordinate behind the scenes, what is it like for the patient on the other end of the phone?

 

---

## You’ve Got One Shot to Reach Them. Then the Refill’s Gone.

For most patients prescribed a specialty drug, treatment is rarely as simple as picking up a prescription, it starts with multiple phone calls to a specialty pharmacy or hub, arranging delivery windows, responding to prior auth questions, or coordinating with insurers. 

Everyone’s trying to help, but no one owns the full picture. One call turns into five. A form goes missing. A voicemail goes unanswered.
 
In a recent survey, **82% of patients** said they spent at least an hour coordinating their specialty care. A third spent more than **three hours**.
 

Support teams do what they can. They make outbound calls for education, counseling, and refill reminders. But staffing is limited and patients get pushed into **voicemail and IVR menus** that offer no real answers. **92% of patients say they want 24/7 phone support** for their specialty therapy but few programs offer it.
 

When calls go unanswered or coordination fails, therapy falters. **Only 62% of prescriptions get filled,** many abandoned after enrollment, during long periods of silence.

At **$85,000 per patient per year**, each lost fill hits hard, for both the manufacturer and the patient who never started care.
 

So if patients are falling through the cracks, providers are overwhelmed, and insurers are slowing things down, what can actually fix this?

## The Power of One Voice, Talking to Thousands—24/7

What if getting a patient on therapy didn’t depend on faxes, voicemails, and manual follow-ups?

That’s the promise of **Voice AI**.

Unlike static IVR systems or one-size-fits-all chatbots, AI platforms like **100ms.ai** act as intelligent agents. They make and take calls, collect data, and follow up, automatically.

They can:

- **Call payers** to check coverage, navigate IVR menus, and retrieve prior auth status
- **Engage providers** to collect signatures or missing labs, instantly
- **Handle patient calls** after hours, confirm deliveries, or schedule refills
- **Triaging issues** intelligently, routing the complex cases to humans and handling the rest themselves

Because AI doesn’t wait on hold or forget to follow up, it can shave off **days or even weeks** from time-to-therapy. One voice agent can handle **hundreds of calls at once**, meaning no one waits. 

For patients, that means **real-time answers** to simple questions like “Has my refill shipped?” or “Did insurance approve it?” even at 11pm. For providers, less time on the phone. For manufacturers, fewer abandoned therapies and faster revenue realization. 

Yes, it’s faster. But more importantly, it keeps more patients on therapy. And that’s what matters most.

 
 
---

## Time-to-Therapy Down 30%: Smarter Calls, Faster Fills

Every hour saved in the access process directly increases speed to therapy, improves patient retention, and boosts manufacturer revenue. A few high-impact stats:

- **Cutting time-to-therapy by 30%** can translate to millions in quarterly revenue for blockbuster drugs
- **AI-driven support** can manage 10x the call volume of human agents at a fraction of the cost
- **Better adherence = better outcomes**, and a smoother experience for patients and providers alike

Plus, voice AI enables **real-time data capture**: call logs, response rates, time-to-resolution, all feeding into dashboards that make call centers smarter over time.

With privacy and compliance baked in, voice AI is the logical next step in modernizing how specialty therapies reach the people who need them.

## Here’s how [100ms.ai](http://100ms.ai/) Is Turning Every Missed Call Into a Moment of Care
 

In specialty pharma, every delay is a risk. Every call that goes unanswered, every form that goes unreturned, and every patient who doesn’t hear back fast enough can mean lost therapy, or worse.

Voice AI offloads the repetitive, robotic tasks and lets real people focus on the moments that matter most: the hard questions, the emotional conversations, the real care and specialty pharma can finally move at the speed that patients deserve.

**Want to see how 100ms.ai can reduce your time-to-therapy by 30%? [Watch a Demo](https://demo.100ms.ai/) or [Talk to Our Team](https://www.100ms.ai/contact).**

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The Road to Specialty Pharma Care: Missed Calls, Drop offs, and 29 Days of Delay

Aniket Behera

Co-founder & COO

I'm Aniket Behera, co-founder of 100ms.ai, where we’re building voice AI for healthcare operations. In this episode of the 100ms Life podcast, I had the chance to sit down with Trellis Usher, founder and CEO of Nova Health Labs, a digital health startup focused on oncology.

Trellis brings a rare dual lens to this conversation: she’s both a breast cancer survivor and a longtime workforce transformation leader. Her perspective is uniquely empathetic, informed not only by years of guiding enterprise change at companies like Salesforce and Pax8, but by navigating the very healthcare system she’s now working to improve.

On our side at 100ms, we’re bringing our roots in real-time audio and video systems—from building infrastructure at Disney and Meta, to support millions of minutes of telehealth and voice AI interactions every week. This podcast was a conversation about solving real clinical bottlenecks with voice that feels fast, smart, and human.

## **From Patient to Innovator: Why Trellis Built Nova**

Trellis’ journey into healthcare innovation started not as a builder, but as a patient.

> “I was diagnosed with triple-negative breast cancer after a casual conversation with friends led me to finally schedule a mammogram,” she recalled. “When I got that call, my world shifted.”
> 

As she moved through her treatment, Trellis encountered **caring clinicians** inside a system full of **uncoordinated, fragmented operations**. The toughest parts weren’t always clinical.

> “The hardest part wasn’t the care itself, it was getting to the care. It was voicemails, waiting for callbacks, figuring out if something was urgent or not.”
> 

That experience became the seed for Nova Health Labs, a company built to **amplify empathy and reduce administrative strain** for both patients and care teams.


## Beyond the Chart: The Human Moments That Medicine Forgot

Trellis’ experience as a patient makes one thing very clear: *clinical touchpoints are only a fraction of the patient journey.*

> “A patient’s experience is not limited to the care they receive in the hospital. It’s everything, the voicemails, the delays, the systems they have to navigate just to get care.”
> 
Trellis pointed out that for many patients—especially those experiencing pain, fatigue, or physical side effects—apps and portals simply aren’t usable.

> “If I’m going through chemo and my fingertips are numb from neuropathy, I’m not typing into an app. But I can still talk.”
> 

Aniket expanded on that thought:

> “Voice is the closest thing we have to human conversation—it carries urgency, empathy, emotion. That’s what makes it so powerful for care delivery.”
> 

That belief drives how we build at 100ms, from latency optimization to audio resilience, to make voice-based experiences feel seamless and human.
 
Healthcare leaders know this intuitively, but don’t always act on it. Today’s patients engage with voicemail inboxes, callbacks, disconnected portals, and front-desk handoffs before they ever speak with a clinician. And for those with complex conditions like cancer, every delay increases anxiety, and sometimes, risk.

### The Oncology Breaking Point: Why Patients Can't Wait for Solutions

Oncology teams are under mounting pressure. While earlier detection and longer survivorship are good signs, they’ve also **outpaced growth in the clinical workforce.**

> “The supply of doctors, nurses, physicians, and really just capacity, is not keeping pace with patient volumes,” Trellis said.
> 

One oncology nurse Nova spoke with shared how **her day starts with 40+ voicemails**, many from the previous afternoon. She said, *“I feel like I’m already behind the eight ball before I’ve even started.”*

And here’s what makes it even more challenging: patients often **downplay their symptoms to avoid being a burden**, unintentionally hiding the most urgent needs.

> “Patients are saying, ‘I don't want to bother them,’ and that’s how we end up with urgent voicemails missed for hours or days,” Trellis explained.
> 

This makes it hard for care teams to prioritize, and **dangerously easy to miss red flags**. For operations leaders, this is more than just a staffing issue, it’s a system design failure.

## AI as Clinician Ally: Protecting the Time That Matters Most

One of the most important reframes in this episode is that **AI isn’t coming for jobs, it’s coming for workflows.**

> “Nurses and doctors don’t go into medicine to sit on the phone all day. They go in to provide compassionate, clinical care, and we’re taking that time away from them with inefficient systems,” Trellis shared.
> 

Her mother, a nurse, once told her she’d “fallen out of love with nursing” because it had become more about forms than people. That loss of purpose isn’t just a personal story, it’s a broader workforce risk.

Rather than removing the human touch, AI has the potential to **bring it back,** by letting clinicians spend more time doing what only they can: building trust, offering empathy, and making expert decisions.

> “Let’s not be afraid of it. Let’s train it, refine it, and use it to do the work that clutters up our day—so we can keep doing the work only humans can do.”
> 

---
 

## Why Specialized AI Outperforms General Models in Healthcare

Many healthcare organizations are tempted by general-purpose AI, but Trellis emphasized why **specialization matters**. Nova is built exclusively for oncology.

> “You don’t go to your PCP for a cardiac issue, you see a cardiologist. AI should work the same way.”
> 

Each call helps the system learn, get smarter, and identify patterns. By training on oncology-specific language and workflows, Nova’s voice agent can **triage based on risk**, identify concerning patterns, and integrate seamlessly into EMRs, without overwhelming staff. That kind of specificity creates more value, more quickly. It’s a reminder for strategy leaders: depth matters more than breadth when outcomes are on the line.
 
At 100ms.ai, we take a similar approach. Rather than building generalist AI, we’re focused on delivering **real-time, scalable voice infrastructure** that partners like Nova can layer their clinical intelligence on top of. 

As Aniket shared,

>“We’re not trying to solve oncology workflows ourselves, we’re enabling the teams that know them best to solve them, with better tools.”. 


That infrastructure-first mindset ensures performance, security, and adaptability across specialties.

---

## Liberating the Healers: How AI Targets Paperwork, Not People

One of Trellis’ most powerful takeaways was this: *AI works best when it evolves with, not apart from, the people using it.* That’s why nurses, care coordinators, and front desk teams should be **co-creators** of the tools they use.

> “They’re the ones closest to the inefficiencies. If we want AI that actually works, we have to build it with them, not just for them.”
> 

This means involving staff not just in deployment, but in design. Because when the workflows improve, morale and care quality rise together.

At 100ms, this is something we see across specialties. The real value of AI is in automating what slows clinicians down, not what defines their job.

> “Let’s not be afraid of it. Let’s train it, refine it, and use it to do the work that clutters up our day, so we can keep doing the work only humans can do.”
>

## The Heart of Innovation: Building a Healthcare System That Actually Cares

Healthcare leaders are under pressure to reduce costs, improve access, and protect their clinical teams. In this conversation with Trellis Usher, six insights rose to the top:

1. Patient experience extends far beyond the clinic
2. Oncology is experiencing a dangerous capacity gap
3. AI must protect, not replace human expertise
4. Specialization is essential for real AI impact
5. Voice AI can deliver scalable empathy
6. AI must evolve with clinical teams, not around them

At the center of all this is a bigger question: *Can we design systems that work better for the people inside them, patients and staff alike?*

Our answer is yes. And companies like Nova Health and 100ms.ai are building for that future.

🎧 Listen to the full podcast [here](https://www.youtube.com/watch?v=IDvxkuRMeiM). 

 

## What's Next?

If your organization is exploring AI solutions, now is the time to start. Consider how 100ms.ai's AI voice agents can streamline your operations and unlock new efficiencies in your healthcare practice.

Follow [*100ms.ai*](https://www.linkedin.com/company/68649749/) for continued insights into the intersection of AI and healthcare innovation. Or book time [here.](https://www.100ms.ai/)

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Healing Healthcare: How Voice AI Helps Caregivers Focus on What Matters | 100ms.ai Podcast 3

## When Insurance Delays Block Life-Saving Care

Imagine this: a patient is prepped for a procedure, the care team is ready, and then someone from the front office walks in and says, “We’re still waiting to confirm insurance coverage.”

That delay, a simple administrative bottleneck, can push care by days or even weeks. It frustrates patients and breaks their trust, and also bleeds money from health systems every single day.


>According to the American Hospital Association, administrative waste accounts for nearly 25% of all healthcare spending in the U.S., with eligibility and benefits-related issues topping the list of inefficiencies (AHA Report).
>

This is a care access issue that modern health systems can’t afford to ignore.

So let’s look into what’s broken in benefits verification, and how voice AI can step up to fix it.

## How Benefits Verification Works Today And Where It Breaks

Before we dive into the financial and operational consequences, it’s important to understand how benefits verification actually works today across U.S. hospitals and health systems.
 
### The typical process involves:

1. **Capturing insurance details** during scheduling or pre-registration.
 
2. **Manually verifying coverage** via payer portals or phone calls.
 
3. **Confirming eligibility and benefit limits** (e.g. deductibles, co-pays, service coverage).
 
4. **Initiating pre-authorization** if required for high-cost procedures.
 
5. **Communicating back to the patient** about coverage status or financial responsibility.
 
This sounds straightforward, right? *Wrong*. In actuality, there are cracks everywhere!

- In the emergency department, coverage verification is often deferred due to the immediate urgency of care. Staff are focused on triage and clinical decision-making, not administrative clearances. As a result, claims are filed retrospectively and frequently denied because eligibility details were never fully confirmed.

In fact, U.S. healthcare staff collectively make **billions** of administrative phone calls annually, and **over 90%** of these are still handled manually.

- In outpatient surgical centers or diagnostic imaging clinics, the need for prior authorization introduces additional complexity. Staff must toggle between multiple payer portals, endure hours on hold, or chase down fax confirmations. If pre-auth doesn’t come through in time, the patient’s appointment is postponed, or the health system delivers care at risk of non-payment.
 
- Specialty clinics like neurology, cardiology, and oncology face another layer of difficulty. Coverage often hinges on exact CPT codes, clinical notes, and nuanced policy interpretations. Staff aren’t always trained in these subtleties, leading to partial reimbursements, claim denials, or unintentional undercoding. The process here isn’t just manual—it’s a minefield of payer-specific complexity.
 
- Even inpatient admissions are affected. Whether admitted from the ED or a direct referral, patients often reach a bed before their benefits are verified. The result? Delayed discharges, incorrect classification, and mismatches between billing data and actual eligibility, all of which can delay payment and trigger claim denials.

Across all of these settings, the issue is the same: the verification process is fragmented, slow, and too dependent on human memory and availability.

> According to CAQH, eliminating manual processes in eligibility and benefits verification alone could save the U.S. healthcare system $12.8 billion annually (CAQH 2023 Index).
> 

Modern health systems need a way to verify benefits **quickly, accurately, and at scale**, without burning out staff or delaying care. And that’s exactly where voice AI fits in.

## Inaccurate Benefits Data Is Draining Your Bottom Line

Hospitals lose billions each year to issues that trace back to benefits verification. It starts from billing accuracy and ripples across every part of the patient experience and revenue cycle. 

Every denied claim starts with a missed moment, an unchecked policy number, a delayed pre-auth, a coverage detail that slipped through.
 

Roughly **1 in 10 claims** is denied on first submission, and **over a quarter of those** stem from preventable eligibility issues ([Change Healthcare Denials Index](https://www.changehealthcare.com/insights/2022-denials-index)). Reworking those denials isn’t cheap: hospitals spend **$25 to $118 per claim** just to fix what should’ve been caught upfront ([MGMA](https://www.mgma.com/resources/financial-management/the-true-cost-of-a-claim-denial)).
 

And the financial impact doesn’t end there. On average, these delays stretch out **reimbursements by 42 days**, throwing off cash flow and tying up staff time ([HFMA](https://www.hfma.org/topics/revenue-cycle/revenue-cycle-metrics.html)). In many systems, **front-office teams spend nearly 34 hours a week** on insurance workflows alone, hours lost to hold music, portal logins, and redundant phone calls ([Google/Harris Poll](https://cloud.google.com/blog/products/healthcare-life-sciences/ai-and-ml-to-improve-healthcare-staff-experience)).

 

Worst of all? Patients bear the brunt of this. 

 

In December 2016, Miranda Yaver, a political science professor, was hospitalized due to severe electrolyte abnormalities that posed significant cardiac risks. Despite the urgency and medical necessity of her treatment, her insurer, Aetna, denied the claim, labeling the hospitalization as "not medically necessary." This denial left her facing a staggering $30,000 medical bill.
> *"I had every advantage in the world. I am a white native English speaker. I have a PhD and was working in a premier school of public health. I am very familiar with the US healthcare system, and I have the job flexibility to stay on hold for long stretches during standard business hours. What would a working mother or someone working multiple jobs do? What about someone who isn’t fluent in English or is otherwise unfamiliar with the healthcare system?"*
> 
> 
> — [Miranda Yaver, The Guardian](https://www.theguardian.com/wellness/2025/feb/26/health-insurance-claims-social-media)
>

In fact, **1 in 4 insured adults** reports care delays or denials tied to insurance issues ([KFF Health Care Debt Survey](https://www.kff.org/report-section/kff-health-care-debt-survey-main-findings/)). Needless to say, this is costing all of us a bomb.

## **Why It’s Still So Manual (and Why That’s a Problem)**

In 2025, most benefits verification still depends on:

- Calling insurance reps manually
- Logging into 5+ payer portals a day
- Navigating outdated IVR systems
- Relying on spreadsheets or sticky notes

According to CAQH, **91% of prior authorizations are still processed manually or semi-manually**, requiring phone calls and fax-based follow-up ([CAQH 2023 Index Report](https://www.caqh.org/explorations/2023-caqh-index)). These processes are slow, error-prone, and expensive. 
For time-sensitive cases like oncology, cardiology, or neurology, care comes to a halt.

## **Voice AI: Your New Superpower in Benefits Verification**

One of the most time-consuming admin tasks is calling insurance companies to verify coverage: waiting on hold, navigating phone menus, confirming eligibility and benefits, and documenting the outcome, all before the patient even sees a provider. 

Multiply that by hundreds or thousands of patient visits per week, and it’s easy to see how costly and unsustainable this is. 

That’s where voice AI comes in.

Voice AI agents are not bots or scripts. They are intelligent systems designed to mimic the actions of a trained benefits specialist over the phone. These agents can place outbound calls to insurance companies, understand and respond to interactive voice menus, speak with payer representatives, and collect information about a patient's plan coverage, deductibles, co-pays, and pre-authorization requirements.

More importantly, they don’t just gather the data, they log it, summarize it, and push it directly into the health system’s backend systems like EHRs or billing platforms. 

That means your front-desk and revenue cycle staff no longer have to toggle between five different screens or spend 20 minutes per call chasing information.

Here’s what this means for your organization:

1. **Time back to your team:** Voice AI takes on the repetitive calls—insurance checks, benefit questions, so your staff can focus on what really matters: helping patients.

2. **Support when it’s busiest:** During enrollment peaks or high-volume weeks, AI scales instantly to keep things moving, no need to stretch your team thin.

3. **Consistent, reliable support:** With consistent scripts and data capture, AI helps avoid rework and missed info, making everyone’s job easier.

4. **Overnight coverage without the burnout:** AI works after hours to gather info and queue up next steps, so your team starts the day ahead, not behind.

5. **More time for care:** By handling the admin load, AI gives your staff time back for the human work, solving problems, guiding patients, and improving outcomes.

Think of it this way: voice AI can never replace your team, it simply multiplies their bandwidth.
They navigate payer phone trees. Ask the right questions. Wait on hold. Document responses. And push everything back into your system of record.


So the staff on ground can focus on the people centric bits of healthcare. 
For patients who don’t use apps or portals, like seniors, Medicaid members, or non-English speakers, a phone-first solution isn’t just convenient. It’s *essential* for equity.

 

**Health equity insight:** According to the National Digital Inclusion Alliance, over **42 million Americans** lack reliable internet access ([NDIA](https://www.digitalinclusion.org/digital-divide/)). A phone-based AI system closes that access gap.

If you want to be the system known for clear answers, no surprises, and timely care, you have to verify faster.

## **Fast to Deploy. Built for Humans. Ready Now.**

Most AI feels like a science project. 100ms.ai’s voice AI on the other hand can:

- Integrate into your existing EHR and billing systems
- Operate securely and HIPAA-compliantly (SOC 2 / HITRUST-certified platforms)
- Be deployed without any new headcount or tech lift (turnkey or API-enabled solutions)

And best of all: it frees up your staff to focus on patients, not portals.

> One third-party administrator reported using an internally developed voice AI agent to manage surges in benefit verification volume without hiring seasonal agents, demonstrating scalable, in-house innovation (Voicegain Case Study).
> 
**CFOs** can expect cleaner claims, fewer denials and reduced rework which lead to lower A/R days and increased net collections. 
**CMOs** can rely on shorter wait times to get them higher HCAHPS scores and no surprise billing complaints! This builds phenomenal patient trust in the long run. 
**CIOs** love that voice AI empowers them by being API-ready, EHR-integrated, scalable, and HIPAA-aligned.

## Verified Before You Ask: Voice AI's Predictive Revolution in Healthcare Benefits

Imagine this:

- Before a patient walks in, their insurance is already verified.
- Their out-of-pocket estimate is clear.
- If something is missing, your staff gets alerted, no chasing, no guessing.

Voice AI enables that world.
> Organizations using automated verification tools reported 30% fewer claim denials and a 50% improvement in verification turnaround time, according to MGMA benchmarking data (MGMA).
> 

It’s not about removing people from the process. It’s about removing friction so they can do their best care management.

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Delayed Benefits, Denied Care: Voice AI Fixes the Broken Benefits Verification System

If there’s one thing everyone in medicine agrees with, it’s that time is the MVP. But inefficiencies continually eat away at it leaving physicians burnt out. Care providers shouldn’t have to juggle back-and-forths, administrative burdens and last-minute cancellations on top of their critical routines. Meanwhile patients shouldn’t have to delay appointments by weeks—sometimes months—despite open slots in provider schedules.

In this episode of the 100ms.ai Podcast, Aniket Behera, COO and co-founder of 100ms.ai, sits down with Dr. Latha Alaparthi, MD gastroenterologist and former president of the Digestive Health Physicians Association (DHPA). She’s been a strong advocate for physicians and patients, and shared everything she thinks AI can do to make the industry she’s served in the last 24 years, better - transforming scheduling, reducing burnout, and building a healthcare system people trust. Check out the full podcast [here](https://youtu.be/A3qX3wNLuN4?feature=shared), or keep reading to gather the gist of it!

---

## **The Scheduling Puzzle: Why AI Appointments Mean Better Care**

For Dr. Alaparthi, the challenges of scheduling aren’t just an industry issue, they’re a daily reality.

> *"I’ve seen the frustration on both sides,"* she shares. *"Patients feel stuck waiting for care, and providers feel stretched thin. There’s no lack of willingness to help—it’s the system that’s inefficient."*
> 

The issue isn’t simply about filling available slots—it’s about matching the right patient to the right provider at the right time. Many hospitals and clinics still rely on manual scheduling systems that can’t adjust dynamically. AI scheduling solves this gap by predicting cancellations, optimizing provider workload, and ensuring patients get timely care.

> ”We are in a significant shortage of healthcare providers and clinicians that can help patients in need of care”, Dr. Latha tells us, “We also are at a point where there's a record high burnout in healthcare providers from all of the cognitive burdens. You were hoping, about 20 years ago, when EHRs came into effect that you would actually decrease the burdens. But in the last 15, 20 years, that's only increased our burdens of having to remember that click and this click. A lot click away without even paying attention to what they're clicking because they’re just so inundated with all of the steps we have to take to do one task. 
I feel the significant urge to do something different at this moment. “
> 

Aniket chips in that after talking to so many MDs, he sees that there sure are set rules for appointment scheduling, but it's essentially the person implementing those rules is making or breaking the system in most cases.

 

To which Dr Latha backs up with her own experience around how efficient scheduling reflects the physician's schedule. “It was interesting when I worked with certain individuals, my schedule wouldn't be as busy as when I worked with certain individuals because they knew how to fill up a schedule. So that sort of reinforces the point you just made.”, she said. 
 

They also discuss how airline cancellations & booking are so easy to make for the end-user and for technology to automate versus healthcare appointment booking, on the other hand, is a mess. “Because the airline system is connected end-to-end and very public. But in healthcare, EMRs don’t give you real-time data easily. Provider availability sheets are often not in some system. It's on some sheet somewhere which is constantly getting updated. When AI is interfacing, they can also log into these operating systems as humans would, just faster, read all of that information and process it to actually talk back to the patient.”

> “Essentially what this means is all of these unstructured or otherwise closed systems now will also become an integrated single system. And that is a very powerful moment.”
>

The impact here is 3 levels deep: Physicians avoid burnout, patients get faster care, healthcare organizations reduce revenue loss from last minute no-shows.

*"It’s not just about convenience—it’s about better care,"* Dr. Alaparthi explains. *"When AI helps smooth out scheduling, it means fewer delays, which can be the difference between early detection and late-stage diagnosis."*
 

If Google can retrieve data from your Gmail about your upcoming Saturday night movie plans, add to your calendar and remind you 2 hrs before the slot to leave on time because you should expect heavy traffic expected along your route to the hospital, technology should be able to do that for doctor’s appointments too. Especially because each no-show, each one-hour, each ill-planned cancellation delay is costing hospitals dollars, providers their sweet time, and delayed treatment for another patient in who’s in need of that slot. 

#### For healthcare leaders, this means rethinking scheduling as a tactical tool—not just an administrative task.
---

## **AI as the First Touchpoint: Smarter, Smoother Patient Engagement**

But getting an appointment isn’t enough. **Ensuring patients actually show up on time and prepared is another challenge.**

*"One of the biggest bottlenecks in healthcare is the volume of patient interactions before and after an appointment,"* Aniket points out.

Think about it: **reminders, rescheduling, pre-visit instructions, and follow-ups**. Traditionally, these require **endless phone calls** and administrative work, creating a strain on staff. AI is now stepping in to **automate and personalize these touchpoints**, improving efficiency while keeping patients engaged.

> *"AI-driven assistants don’t just send reminders—they guide patients through their journey,"* Dr. Alaparthi explains. *"In gastroenterology, for example, preparing for a colonoscopy requires very specific steps. AI ensures patients follow those instructions correctly, reducing cancellations and complications."*
> 

With AI’s proactive patient reminders and chatbots answering patient queries, call center volumes drop by 25% (Source: HIMSS, 2024) and no-show rates by upto 30%. (Source: JAMA, 2023)

Your staff on the other hand, can finally thank you and focus on high-value tasks. 

*"Patients don’t want to be left in the dark,"* Dr. Alaparthi adds. *"AI keeps them informed and engaged, without them having to wait on hold for answers."*

Aniket elucidates what the stage of 100ms.ai’s AI voice tech is at right now. Their AI voice agents can now:

- Handle people talking about stuff like why they missed their last appointment or life problems and respond back in a human manner
- Follow an agenda, but also acknowledge what the person in front of you is saying
- Even modify voices to be closer to the community.

If you want to check out everything that [100ms.ai](http://100ms.ai) is capable of, 

#### Healthcare executives, this is your chance to use AI patient engagement as a tool to drastically change the patient experience and provider efficiency.
---

### **The Big Misconception: Will AI Replace Doctors?**

Whenever AI enters the conversation, there’s a common concern: *Is AI going to replace human providers?*

Dr. Alaparthi is quick to set the record straight.

> *"AI isn’t replacing doctors—it’s replacing inefficiencies,"* she says. *"If anything, it’s allowing us to be more present with our patients, rather than drowning in paperwork."*
> 

Aniket agrees.

> *"We have to shift the mindset from AI being competition to AI being an assistant. The best healthcare systems will be the ones that use AI to enhance—not replace—the human touch."*
> 

Clearly, AI in healthcare is not about reducing staff—it’s about giving overworked healthcare teams with some respite and a smarter workplace. 

---

 

On that note of shared optimism for AI revolutionizing patient care for the better, we wrapped up another episode of this podcast. 

Aniket reflected on how Dr. Alaparthi’s, who’s not just talking about change in healthcare but actively making it happen, highlighting the real world challenges clinicians adds serious momentum to 100ms.ai’s mission. 

Dr. Alaparthi echoed the sentiment, emphasizing how these discussions are crucial for bridging the gap between technology and frontline healthcare needs. *"AI isn’t about making healthcare impersonal—it’s about removing the obstacles that keep doctors from doing what they do best,"* she concluded.

### **What’s in it for Healthcare Leaders?**

For healthcare executives, finance teams, and strategy leaders, AI for your frontline team is no longer a maybe, it’s a resounding yes that should’ve arrived yesterday. 
 

**Where can leaders start?**


1️⃣ Identify the biggest bottlenecks, begin with scheduling, patient outreach, or administrative workflows.

2️⃣ Choose an AI solution that integrates seamlessly. AI should **enhance** existing operations, not disrupt them. Book a meeting with [100ms.ai](http://100ms.ai) today. 

3️⃣ Educate providers and staff on AI’s role. Help them see AI as an ally, not a replacement.

 

As Aniket puts it:

*"The smartest organizations aren’t debating whether to use AI anymore. They’re figuring out how to use it best."*

For healthcare leaders, the question isn’t if AI will transform the industry, it’s whether they’ll be ahead of the curve or scrambling to catch up.
 
🎧 Listen to the full podcast [here.](https://youtu.be/A3qX3wNLuN4?feature=shared)

 

### **What’s Next?**

If your organization is exploring AI solutions, now is the time to start. Consider how AI voice agents and automation tools can streamline your operations and unlock new efficiencies in your healthcare practice.

Follow [*100ms.ai*](https://www.linkedin.com/company/68649749/) for continued insights into the intersection of AI and healthcare innovation. Or book time [here.](https://www.100ms.ai/)

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What Happens When AI Picks Up the Phone? | 100ms.ai Podcast, Ep. 2 

## 9:02 AM on a “Normal” Tuesday in the GI world

It’s 9:02 AM at a busy GI clinic. The first patient of the day is filling out a clipboard. Behind the desk, phones are already ringing. A nurse is sorting through a mountain of digital faxes, trying to find the referral she swore was sent last Thursday. The e-prior auth file is missing again. A front desk coordinator is 16 minutes deep into a benefits verification call, stuck in hold-music purgatory. Another patient canceled because they didn’t complete their bowel prep correctly.

This brokenness is somehow still the “standard operating procedure” across U.S. gastroenterology.

Across the U.S., most GI clinics still rely on a mishmash of faxes, phone calls, and manual data entry to manage referrals, scheduling, and insurance verification. These are life-critical workflows that should move fast, but they’re held together with duct tape and goodwill. 

And when that tape fails, patients don’t get scheduled, urgent care gets delayed, and staff burn out.

### **Your Front Desk Needs a Co-Pilot, Not Another Portal**

In GI, a single missed screening can mean a missed cancer. Front-desk staff are the first triage layer, but they’re drowning in repetitive, urgent busywork. They don’t need another portal or dashboard, they need a **24/7 colleague that can talk, listen, remember, and act**.

**Voice AI agents** shoulder the grunt work while humans focus on empathy and clinical nuance.

 

**Pros**
- 24/7 throughput without new headcount
- Error-free data capture → fewer denials
- Instant patient touch-points → higher conversions

 

**Cons & Mitigations**
- Nuance with angry callers → sentiment-triggered escalation
- Edge-case payors → fallback human queue
- Staff adoption → frame AI as a *grunt-work sponge*, not a job thief

### **Turning the Referral Black Hole into a Feedback Loop**

A primary care doctor sends over a referral. But it’s missing some critical details, no insurance info, vague reason for visit. The e-fax queues behind a long list of piled-up referrals. By the time someone sees it, it’s been 8 days. The patient hasn’t been contacted. No one followed up. Eventually, the patient gives up and goes elsewhere.

 

On the physician’s end, a significant 68% of specialists report receiving no information from the referring primary care physician before a patient's visit, leading to inefficiencies and potential misdiagnoses. 
(Source: Steinberg, Goodman & Kalish)

 
This happens every day. Studies say only half of specialist referrals are ever completed. That means out of the more than 100 million referrals sent annually, close to 50 million patients may never receive the specialist care they were advised to get.


Because the process is still largely reliant on paper faxes [(upto 70-90% !!)](https://kmbs.konicaminolta.us/blog/new-facts-about-fax-in-healthcare/#:~:text=EHR%20systems%20provide%20electronic%20referral,new%20patient%20to%20another%20facility), manual calls, and staff assessing what *feels* urgent, it was never built for scale or speed.

Clinics using voice agents like those from 100ms.ai are starting to close the loop in real-time. 

Instead of manual triage, every referral gets triaged instantly. Staff still oversee and approve, but they’re not chasing paper, they’re coordinating care.

The ability to track, follow-up, and escalate referrals through automation creates a feedback loop instead of a black hole. When referrals are acknowledged within minutes, conversions rise. Patients build faith. And physicians feel confident their patients are receiving the care needed.

### Insurance Verification While You Sleep

If you ask front desk staff what they dread most, benefits verification and prior authorization will top the list. It’s tedious, it’s error-prone, and it’s often a single point of failure for the entire care pathway.

Each insurance check takes around 12 minutes manually. Multiply that by 30-50 patients per day, and you’re looking at the equivalent of a full-time role just to handle eligibility.

And it gets worse. Up to 50% of claim denials stem from errors in the front-end registration process: wrong insurance numbers, missed authorizations, or outdated coverage data. 

Most EMR e‑Benefits checks are surface‑level at best. They rely on CAQH CORE rules, which only require coverage info for a narrow set of services like imaging or surgery—not pathology, anesthesia, or specific procedures [(CAQH CORE)](https://www.caqh.org/core/eligibility-benefits). Some even lean on pharmacy-focused networks like Surescripts, which only return drug coverage—not medical benefits [(Surescripts FAQ)](https://surescripts.com/news-center/intelligence-blog/what-you-should-know-about-electronic-eligibility-verification). That means front-desk teams are left guessing on critical coverage details, and patients end up paying the price—sometimes literally—with surprise bills for care they thought was covered.

For GI clinics, where every procedure depends on insurance clearance, this is transformative. One missed prior auth can delay a colonoscopy by weeks. Multiply that across a month, and you're not just dealing with inefficiencies. You're risking patient outcomes.

Automating this layer also means better preparedness. When patients show up, they already know their financial responsibility. There are no last-minute surprises. Clinics can collect payments upfront, and claim denials plummet.

### AI for Prep: Patients show up ready, Clinics don’t miss a beat

Prep adherence is what keeps GI care lagging. Procedures like colonoscopies, follow a strict protocol like: fasting, medication timing, bowel prep, hydration. If the patient gets it wrong, the procedure simply can’t happen.

The result? A missed appointment, an empty slot, and a potential missed diagnosis.

GI clinics typically experience 5-8% no-show or cancellation rates, with forgetting being the #1 reason patients miss appointments. Prep issues are a close second with some facilities reporting as high as 15% of patients showing up inadequately prepped. 

Traditionally, staff make reminder calls a few days before the procedure. But that’s a massive time sink.

University of Chicago Medicine reported a 6% drop in no-shows using automated navigation reminders. And one clinic using automated prep calls saw inadequate bowel prep drop by 40%.

### From Burnout to Bandwidth with AI

Now imagine a front desk where none of these fires exist.

Referrals are reviewed automatically within minutes of arriving. Insurance is verified overnight. Prep reminders go out automatically, in multiple languages. And your staff? They’re focused on patients, not phone trees.

This is not a distant vision. It’s already underway.

Experts predict that by 2026, the majority of front desk workflows in ambulatory care will be handled by AI agents indicating that the *work of healing* will always be centralized with the frontline staff who can then delegate all the tedious, manual bits over to AI. 

Early AI adoption in GI clinics is resulting in a state of calm - where the front desk is proactive and tasks don’t fall through. And where patients move through care pathways with clarity. 
 
Someday soon, the fax machine will still sit at the clinic’s front desk. But it won’t be plugged in. It’ll be on a shelf. Beside it, a small brass plaque:

***"Retired: 2024. Replaced by real-time care."***

---
 
 

**Ready to modernize your front desk?** AI voice agents from [100ms.ai](https://www.100ms.ai/) are already helping health systems streamline referrals, prep, and verification, so nothing urgent gets missed, and everything important gets done.

*Sources: CAQH Index, University of Chicago Medicine, Konica Minolta Healthcare Report, American Journal of Managed Care.*

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From Fax to Future: Voice AI Is Quietly Transforming the GI Front Desk

The intersection of artificial intelligence and healthcare is transforming the way medical offices and healthcare organizations operate. In the first episode of **100ms.ai**'s podcast series, host **Aniket Behera**, co-founder of **100ms.ai**, sits down with **Dr. Lukasz Kowalczyk**, MD gastroenterologist (of 20+ years) and tech entrepreneur. They talk about how AI is enhancing healthcare operations, from patient scheduling to improving overall workflow efficiency.

This blog is a summary of that [podcast](https://youtu.be/_mAMAsRrkj8?feature=shared), where we’ll be highlighting five key takeaways from Aniket and Lukasz's conversation - so you have insights that matter for healthcare finance leaders, strategy executives, and medical office decision-makers. 


###  The Complexity of Healthcare Operations and AI’s Role

Healthcare operations are notoriously complex, with multiple stakeholders, regulatory requirements, and high-stakes patient interactions. **Aniket Behera points out that** every operational step—from scheduling to reminders—directly affects patient outcomes, making efficiency a critical factor.

Dr. Kowalczyk echoes this sentiment, emphasizing that AI has the potential to streamline these intricate workflows.

Administrative inefficiencies in healthcare are a major barrier to timely patient care. AI helps us break down these inefficiencies so doctors can focus on what matters—treating patients.

MD and CEO of Soothien HealthTech Advisory

AI-driven agents, like those developed by **[100ms.ai](https://www.100ms.ai/)**, can handle routine yet essential tasks, reducing the burden on human staff while improving the patient experience. For healthcare executives, this means increased efficiency, reduced administrative costs, and fewer scheduling bottlenecks—all of which lead to improved revenue cycles and patient satisfaction.


### AI and the Patient Scheduling Funnel

Dr. Kowalczyk MD compares patient scheduling to a **sales funnel**, where acquiring and retaining patients mirrors customer acquisition strategies in other industries. He describes how a patient’s journey starts with a referral moves through appointment scheduling, and ultimately leads to the procedure or consultation.

A key challenge in this process is that scheduling staff often have limited medical literacy, yet they play a crucial role in ensuring patients receive care on time. AI-powered voice agents can bridge this gap by intelligently guiding conversations, ensuring patients receive the right information without relying on staff who may lack specialized knowledge.


For hospital administrators and finance leaders, this automation reduces appointment no-shows, optimizes provider schedules, and enhances patient throughput —all of which contribute to better financial performance and operational stability.

The reality is, a lot of scheduling staff don’t have deep medical knowledge. AI can help structure those conversations so that patients get accurate and timely information without delays. 

### Personalization and Patient Trust ###

One of the biggest concerns with AI in healthcare is ensuring that patient interactions feel genuine and empathetic. Dr. Kowalczyk highlights that AI-driven voice agents can be designed to sound natural and build trust with patients.

He notes that regional accents and conversational tone can make AI-driven calls feel more authentic and personalized. For instance, older patients, who may initially be skeptical of AI, are often more receptive when the system mirrors the tone and mannerisms of human agents.

People assume AI interactions are robotic, but when done right, they can feel incredibly human—sometimes even better than a rushed phone call with an overworked staff member”

From a strategic standpoint, this level of personalization increases patient engagement, reduces friction in communication, and builds long-term trust in AI-powered healthcare solutions. Leaders in healthcare strategy must consider these human factors when integrating AI into patient-facing operations.

### Operational Excellence Meets Clinical Excellence

For AI to succeed in healthcare, it must seamlessly integrate with both clinical expertise and operational workflows. Dr. Kowalczyk explains that without proper alignment between administrative efficiency and medical decision-making, AI implementations can fall short of their potential.

He emphasizes that AI is most effective when it augments, rather than replaces, human decision-making. AI scheduling, for example, must be designed with input from clinicians to ensure medical priorities—such as urgent cases—are appropriately handled.

Healthcare executives should view AI as a collaborative tool rather than a standalone solution, ensuring that both operational and clinical teams are aligned in its implementation. This approach results in better patient outcomes, streamlined workflows, and enhanced financial performance. 

### The Future of AI in Healthcare: What’s Next?

As AI adoption grows, its role in healthcare operations will only expand. Aniket Behera notes that 


AI voice agents have already seen strong patient acceptance rates, and future developments will focus on enhancing predictive analytics, proactive patient engagement, and real-time operational decision-making

COO and Co-Founder at 100ms

The next phase of AI in healthcare will involve more sophisticated automation, where systems not only assist with scheduling but also predict patient needs, optimize resource allocation, and provide actionable insights for healthcare leaders. 

For decision-makers in healthcare finance, operations, and strategy, this means now is the time to **invest in AI-driven solutions that can enhance both efficiency and patient care**. Organizations that proactively adopt and integrate AI will gain a competitive edge in an industry where **operational excellence is key to success**.

### **Conclusion: The Time to Act is Now**

AI is not just a futuristic concept—it’s already revolutionizing healthcare operations. From streamlining patient scheduling to improving engagement and workflow efficiency, AI-driven solutions are transforming the industry. 

For healthcare executives, the key takeaway is clear: AI isn’t here to replace human expertise—it’s here to amplify it. By strategically integrating AI into healthcare workflows, organizations can enhance operational efficiency, reduce costs, and improve patient experiences. 

This conversation between Aniket Behera and Dr. Lukasz Kowalczyk highlights the immense potential of AI in healthcare. Now, it’s up to industry leaders to embrace this transformation and take action. Head over [here](https://youtu.be/_mAMAsRrkj8?feature=shared) to listen to the whole podcast here. 

### What’s Next?

If your organization is exploring AI solutions, now is the time to start. Consider how AI voice agents and automation tools can streamline your operations and unlock new efficiencies in your healthcare practice.

Follow [*100ms.ai*](https://www.linkedin.com/company/68649749/) for continued insights into the intersection of AI and healthcare innovation. Or book time [here.](https://www.100ms.ai/) 

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The Doctor Will See You Now | Thanks to AI Scheduling | 100ms AI Rx EP01

Lukasz Kowalczyk

MD and CEO at Soothien HealthTech Advisory

## What is Patient Scheduling and Why is it a Big Deal?
At the core of every healthcare system is one deceptively simple question: How do we make sure patients get the right care at the right time? One low-hanging fruit - patient scheduling - determines everything from clinical outcomes to hospital efficiency to financial performance. 

Scheduling is the thin line in healthcare between timely illness detection that could potentially save countless lives & US dollars vs missed healthcare opportunities that cost a fortune!

Yet still, it remains one of the most overlooked, inefficient, and fragmented processes in US Healthcare.

## Understanding the Complexity of Patient Scheduling

Patient scheduling plays a critical role across various healthcare settings, each with its own nuances and requirements.

In a **primary care setting**, scheduling involves routine check-ups, follow-up visits, and same-day sick appointments. The pertinent problem here is how do we minimize administrative burden on our front desk team that is busy juggling between reschedules, cancellations and triage patient needs in real time?
 

In **surgical centers**, it means seamless cross-team coordination, securing operating room availability fast, and accounting for procedure durations. Inside the labyrinthine workings of a giant hospital, a single scheduling dependency can set off a domino effect and disrupt the entire day’s workflow. 
 

Operating rooms require cohesive cross-communication between surgeons, anesthesiologists, nurses, and recovery teams. Rigid scheduling models that don’t adapt quickly to the mercurial temperament of a hospital, can end up being ineffective and costly - a surgery could run longer than expected or a last-minute emergency case could pop up any minute. 
 

**Specialty clinics & referral scheduling** Referrals are where a lot of patients fall through the cracks. A primary care doctor flags something that needs a specialist’s - a cardiologist’s or a dermatologist or any other specialist’s- attention. But what next? Patients are expected to navigate scheduling on their own - call up offices, figure out availability, waiting weeks or months for an open slot. And the numbers back this up: GPs in the NHS make around 400,000 referrals a month, but many get sent back because outpatient clinics are already full.

From the specialist’s side, it’s just as chaotic.

They’re juggling long waitlists, urgent cases, and meandering busy schedules, while trying to ensure the patients requiring critical care, don’t get lost in the backlog. Multi-specialty clinics are sinking in this mess even more! Since every provider has different availabilities, procedure times, and rules. 
 

The result? 
The system fails patients. 
Who then lose hope in healthcare and resort to private clinics.
And clinics struggle to keep up with demand.
It’s a vicious cycle. 
 

In **telehealth**, a functioning scheduling system implies smooth virtual visits with patients receiving timely appointment reminders so that no one’s time is wasted! This sector is more prone to the appointments being skipped entirely, thus requiring additional checks and balances to maintain provider efficiency and patient access. 
 

**Diagnostic centers and outpatient clinics** must ensure that patients are properly prepared before their appointment. One mistake like not fasting before a test can lead to last-minute cancellations, wasted resources, and delayed patient care.

So here’s the deal: the difference between a well-run scheduling system and a broken one isn’t just administrative — it’s financial, operational, and clinical. And right now, most healthcare systems are on the losing side.

What happens with a well-functioning scheduling system in healthcare is that you reap threefold the benefits.

- **Firstly, Patients receive prompt care** without unnecessary delays.

- **Next, providers operate at full capacity** without gaps or overbooking.

- And finally, you have maximum efficiency, minimum **operational waste in the context** of exam rooms, equipment or admin staff. 

Now, let’s contrast that with how scheduling actually works today.

## The Cost of Poor Scheduling

Every open slot, last-minute cancellation, or missed referral translates into **wasted revenue and underutilized resources.** Besides the humongous financial ramifications that add up to 1 Trillion US dollars each year, perhaps the saddest blow that comes from inefficient scheduling in healthcare is the increasingly high number of cases of **delayed care and misdiagnoses** that could’ve easily been avoided. 
 

Here’s a glimpse into exactly how many dollars are wasted annually due to this fragmented process.

- **[$150 billion per year](https://www.hcinnovationgroup.com/policy-value-based-care/article/13030987/missed-appointments-cost-the-us-healthcare-system-150b-annually)** in lost revenue due to no-shows.
- Each missed appointment resulting in **[$200 in lost revenue](https://www.phreesia.com/2021/06/01/the-hidden-cost-of-missed-appointments-how-no-shows-affect-your-practice/)**
- **Provider downtime** that results in **underutilized clinical hours.**
- **Patient leakage.** Nearly **30% of patients** have left a provider due to excessive wait times.
 

For healthcare providers, **fixing scheduling isn’t just about patient experience—it’s about operational survival.**

## How Can AI Solve Scheduling Challenges?

2025 has already been a year of constantly exclaiming *what can’t AI do*. In healthcare scheduling too, AI can help drastically bring down wasted resources and streamline healthcare operations. Going beyond simple automation, AI with predictive intelligence can make real-time scheduling adjustments, and deliver a personalized patient engagement. So how can AI help?


### AI Scheduling & Patient Self-Service

Instead of you as a patient listening to the hold music for hours, interact with an AI voice agent that would handle the end-to-end scheduling process in a jiffy with negligible hold times. This ensures non-native English speakers have access too. Manual booking barriers are removed and so patients can schedule, reschedule, or cancel appointments 24/7 through voice, text, or online platforms within seconds.

AI scheduling could also halve the vexatious administrative work on providers, so they can pay attention to patient care. That's an indispensable amount of time to give back to our healthcare providers!

Organizations that have adopted AI scheduling already report a **35–45% increase in patient satisfaction**!

### Ditch the Robocalls: Proactive Patient Engagement & Reduce No-Shows

Traditional reminder systems fail because they’re passive and react too late. But AI engagement with its proactivity and adaptability brings radical change in continued care and provider utilization.

Ditch the generic robocalls. Use AI reminders to engage patients proactively in real-time conversations, confirming attendance, rescheduling, and even assisting with transportation! Who would’ve thought that you can use AI can to sniff out high-risk no-show patients and tailor your communication accordingly. AI reminders at healthcare centres are already delivering a drop in no-show rates by 30-45%.

### Real-time Scheduling & Allocating resources

Appointment booked! What next? Need reminders? Sent! Did they cancel? Auto-backfill open slots, contact waitlisted patients, offer earlier appointments to those already scheduled. AI works round-the-clock optimizing scheduling.
 

Inside hospitals, AI predicts surgical case durations to reduce operating room (OR) downtime. In outpatient settings, AI optimizes diagnostic scheduling so your MRI and CT scan machines operate at full capacity, avoiding wasted resources from last-minute cancellations!
 

*On the first episode of 100ms.ai’s podcast with Aniket Behera and Gastroenterologist turned tech-entrepreneur Lukasz Kowalczyk, we delved into the depths of this and here’s an excerpt:*

Schedulers basically dial a lot of phone numbers, not knowing who they’re calling. They just know, ‘I have a referral in,’ but there’s no intelligence around it, no segmentation. So much time is wasted on cold calls and voicemails.

Head [here](https://www.100ms.ai/podcast/ai-agents-are-revolutionizing-healthcare-operations-100ms-ai-ai-rx-episode-1) to listen to the whole conversation. 

### AI Referral Management & Patient Follow-Ups

Referral leakage, where up to 50% of referred patients never complete their specialist appointments, is currently a $500 million healthcare challenge! AI helps conquer by automating follow-ups, prioritizing high-risk cases, and assisting patients with scheduling specialist visits.


It can segment referrals into high and low-priority cases so that urgent patients get seen first. In a single interaction, the AI voice agent will explain referrals, answer patient queries, and book appointments - thus narrowing the referral leakage gap.


Your front office staff should be helping patients in-person, not spending six hours a day leaving voicemails. That's where AI can really make a difference. 

### AI-Augmented Human Schedulers

AI isn’t replacing human schedulers, only 10x-ing their efficiency. Monitoring scheduling calls, suggesting real-time adjustments, and on-the-go coaching would also improve staff performance.

For example, if a scheduler is handling a high-risk patient, a simple AI-prompt for an earlier appointment can make a notable difference in timely care.

### Personalized AI Outreach & Demographic Adaptation

One-size-fits-all scheduling just doesn’t work in healthcare. The way you engage a 25-year-old for an appointment isn’t the same as how you engage a 75-year-old.

Like, the older demographic may not be as comfortable answering texts as they’d be receiving voice call reminders. If your admin team is sending out textual appointment/rescheduling prompts, the 60+ crowd may never respond back or be able to even navigate through the messages. Being able to analyse this is a bottleneck, and adjust on-the-go is a great asset and this is exactly what robust AI systems can do for you.

Language is another major barrier. AI-powered, multilingual outreach can detect a patient’s preferred language and communicate in Spanish, Mandarin, or Hindi. It can even sense hesitation and offer to connect them to a human agent if they seem unsure about scheduling.

This is what scheduling should have been doing all along. But now that AI is here, the healthcare staff can focus on everything important while AI delivers intelligent, patient-first engagement.

### AI Scheduling Resilience & Fail-Safes

Healthcare scheduling must be resilient, with built-in redundancies to prevent breakdowns. Advanced AI scheduling systems include multi-layered fail-safes, ensuring that patient outreach continues even if one method fails.

For example, if a patient doesn’t respond to an initial call, AI re-engages them through an alternate channel (text, email, or human agent escalation). Additionally, AI scheduling agents monitor real-time patient check-ins and dynamically adjust schedules to accommodate late arrivals or unexpected cancellations.

## What This Means for Healthcare Leaders? AI in Scheduling: A Cohesive Healthcare Experience

If you’re leading patient access, operations, or scheduling, here’s where the future is headed: 

-  Reduce No-Shows: AI reminders & follow-ups keep patients engaged and on time. 

-  Increase Revenue: Fewer empty slots mean higher appointment volume and revenue.

-  Relieve Staff Burnout: Your team focuses on patient care, not chasing voicemails.

-  Optimize Scheduling Efficiency: Use AI to book the right patients at the right times.

By merging AI with human experience, healthcare scheduling becomes proactive & dynamic - able to adapt patient needs and provider availability in real time. Healthcare providers adopting AI scheduling solutions will reduce administrative burdens, increase patient retention, and unlock new levels of operational efficiency, ushering in a new era of intelligent healthcare scheduling.

## 100ms.ai is revolutionizing healthcare scheduling and how

At 100ms.ai, we’re building AI-powered voice agents to tackle this head-on. Our solutions seamlessly integrate into existing healthcare systems, automate patient interactions, and optimize scheduling workflows to create a frictionless experience for both patients and providers.

Healthcare has seen success in adopting proven operational models from other industries—so why not scheduling? The same AI-driven automation that transformed retail, fintech, and hospitality is now ready for healthcare.

The reality is simple: manual scheduling is outdated, inefficient, and costly. The future is AI –- automated, and patient-centric. The only question is—will your healthcare system be an early adopter or risk falling behind?

AI is not plug-and-play yet. It takes fine-tuning to make sure it actually works for your specific patient population.

Catch all the insights about real-world AI scheduling results, best practices, and how AI is transforming patient access in the Episode 1 of our podcast with Aniket Behera and Doctor Lukasz Kowalczyk. 
 

🎧 Listen to the full episode **[here](https://www.100ms.ai/podcast/ai-agents-are-revolutionizing-healthcare-operations-100ms-ai-ai-rx-episode-1)**
 

If you’re ready to explore how AI scheduling can work for your organization, let’s talk. **[100ms.ai](https://www.100ms.ai/)** is already helping leading healthcare providers streamline scheduling and improve patient access. 

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**[Book a Demo Today](https://www.100ms.ai/contact)**
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