Monday, October 19, 2026

< + > Key Healthcare Cybersecurity Lessons From the SHI Summit

I was excited to take part in my first ever SHI Summit hosted by the good people at SHI International.  They hold these Summits each quarter and bring together their clients from across multiple industries.  Each Summit has a focus and this quarter’s summit was focused on Cybersecurity and AI.

At the SHI Summit, the sessions explored the latest technology innovations and heard from cybersecurity leaders about what it takes to build a resilient security program. From hands-on technology labs and cybersecurity testing to managing risk, prioritizing investments, building trust, and communicating effectively with executive leadership, these takeaways highlight the people, strategies, and technologies that healthcare organizations need to strengthen their cybersecurity efforts.

Below you’ll find some of the key perspectives we heard and shared on social media along with a little extra additional commentary.

I really don’t know how to capture the experience of checking out the unique spaces that SHI has available to their customers.  For a techguy (largely becoming former techguy) like me, this was like heaven.  The Next Gen Device Lab was great to see all the latest AI powered devices and to see the benchmarking tools that SHI was using to evaluate them.  Not to mention their warehouse’s ability to store, prep, and ship out devices was amazing.

The AI and Cyber Labs took me back to my data center days.  A really unique space for SHI customers to be able to see the latest products.  Plus, the way they could test all of these products and help their customers understand how they’re going to work before being in production was really cool.  Not to mention the racks in a box (literally) that they can build and ship out to a data center where it can just be plugged in and ready to use.  The Customer Innovation Center was a great showcase of the latest products as well.  Sometimes it’s hard to really understand a new device until you get your hands on it.  I was handed one device that felt like a sheet of paper it was so small.  Always great to get your hands on devices before buying them.

Cybersecurity is a hot topic in every healthcare organization.  However, while there’s a lot of concern, I wonder if healthcare is going this deep with their cybersecurity efforts.  What do you think?

I was really struck by what it takes to create resiliency in your cybersecurity efforts.  However, Tammy Moskites pointed out how it’s the humans that make it all work.  This isn’t something you can just buy and forget about it.

Technology is great and necessary when it comes to healthcare cybersecurity.  However, Tammy appropriately pointed out that people are still the strongest response.  You could say that people + technology is where the real magic happens though.

I’d never really connected some of the “softer” skills of self doubt and imposter syndrome to security risks.  It was fascinating to see Moskites tied those two things together.  Of course, over confidence can also be a security risk as well.  As with most things in life, there’s a balance that we have to achieve.

I think most of us have faced some version of imposter syndrome in our live.  I like Moskites 4 suggestions on how to battle imposter syndrome.  What do you think of these ideas?

I don’t think I’ve ever heard someone say an audit was a friend.  Most people hate audits.  Although, Moskites makes a really good point that the details from an audit can be a key lever you can use to get money for cybersecurity efforts.

I’ve been chewing on this idea for a while.  Kind of reminds me of the famous phrase, you’re only as strong as your weakest link.  Leadership is good and can help a team become more resilient, but a team that works together is key to building a resilient cybersecurity program.

We’ve often heard this at Healthcare IT Today, but it was a good reminder.  Board rooms care about risks, not the details.  If you lead with the details, you’ll lose them.  If you lead with the risks, you’ll win them over.

I know this can be a challenge for IT and security leaders that aren’t known for being the best communicators.  However, it’s a skill you can develop and need to develop since Finance and Operations are essentially your “competition” for budget, attention, and resources.

This was a fascinating response.  I was impressed by the CISO’s conviction in their roadmap.  With the pace of change in cybersecurity, hopefully they have some flexibility in that roadmap.  However, I can see why that conviction matters.  When budgets are tough, it’s easy to cut cybersecurity which only gets attention when something goes wrong.

The idea of sharing the truth was powerful as well.  Not being truthful is how people get fired.  Candid truth with an appropriate response builds trust in leaders even when the truth is hard to hear.

It was so powerful when the CISO panel shared that if you don’t share the problems that you’ll become the fall guy.  I like to say that ignorance is bliss until it’s not.  Transparency is key.

I heard this a number of times at the SHI Summit.  No one has enough resources for cybersecurity, so you have to prioritize where you invest.  It really is the most important thing a healthcare CISO does.

As part of an organization’s prioritization, I really liked this idea and analogy around risks and threats.  What do you think of the analogy?

This is a drastic shift and one I’ve seen as well.  We went from “If we have a security incident…” to “When we have a security incident…”  This doesn’t absolve us from trying to reduce cybersecurity incidents, but it does mean we need to have a good recovery and mitigation plan in place when a cybersecurity incident happens.

It was great to hear so many cybersecurity perspectives that healthcare can use.  Next up, we’ll share some of the AI insights from the SHI Summit.



< + > Vocca Raises a $20M Series A After Growing From 2,000 to 15,000 Practitioners in a Year

Vocca, the AI platform medical practitioners rely on to speak with their patients, announces a $20 million Series A led by Norrsken VC, with participation from Heal Capital, Speedinvest, and Firstminute Capital, and angel investors including the founders of Alan and Datadog. Total funding to date is $25 million.

Vocca’s specialized AI agents handle over one million patient interactions a month, end to end, across more than 20 medical specialties.

Vocca Leads with National Deployments as the Category Matures

Vocca’s first product is an AI phone assistant that picks up phone calls and automates them. A year ago, at its seed round, 2,000 medical practitioners used it. Today, 15,000 do, across 1,500 practices and twenty specialties in the United States and Europe. Over the same period, conversation volume grew 10x, now exceeding one million a month from inbound calls alone, and revenue grew 7x.

On average, Vocca resolves 70% of conversations end to end with no human involvement; its most mature customers exceed 85%. National groups run their scheduling on it: DAG Dental (37 practices), Point Vision (67 ophthalmology practices), Résonance Imagerie (60 imaging centres), and hospital systems such as the Hôpital Fondation de Rothschild, which handles intake, calls, and confirmations with Vocca for its 350,000 yearly patients.

AI That Understands How Medical Practices Actually Work

Four in ten calls to a medical practice go unanswered. Nearly half of health workers report frequent burnout, up from a third in 2018. Practices turned to AI and found generic tools didn’t know their rules. Vocca learned each specialty’s scheduling logic, integrated with the software practices already used, and was built to handle patient data securely.

“Practices don’t ask us about price. They ask how fast we can deploy and how we handle their edge cases,” said Eliott Hoffenberg, CEO and Co-Founder. “Doctors want an AI that works like their best scheduler, follows the rules of their specialty to the letter, and fills more appointments without compromising on quality.”

Vocca understands the difference between hundreds of medical exams and steers each patient to the right one. Behind the voice is a scheduling engine with a library of specialty-specific models that encode these rules, so practices go live in days rather than months.

Practices Trust Vocca to Run Their Schedule

“Vocca resolves more than 75% of calls fully autonomously: booking appointments, answering questions about exams, consultation preparation, and administrative requests,” said Charlotte Cardin-Taillia, Deputy General Director of Hôpital Fondation de Rothschild. “For the remaining quarter, the AI immediately transfers urgent calls to the front-desk staff and calls back complex, lower-priority requests. Teams can then focus on the patients who truly need to speak with a person.”

“We tested a handful of AI tools across different offices. Vocca was the clear winner, and we rolled it out across the group,” said Opal Anderson, Chief Operating Officer at DAG Dental. “It absorbs the volume and the repetition. Our teams keep the judgement calls, they’ve gained back hours a day, and our patient satisfaction has never been higher.”

The Second Wave of Healthcare AI is Conversational

Healthcare’s fragmentation has kept software out for decades, and a quarter of US health spending still goes to administration, much of it on the phone. The first wave of AI in medicine was documentation: in a few years, ambient scribes became standard. The second wave is conversational, and it moves faster because it asks no one to change how they work. Patients keep calling; staff keep their tools. What changes is capacity.

Vocca’s thesis is that the conversation is the interface and the scheduling engine behind it is the infrastructure, both built for healthcare’s real constraints.

“We’ve rarely seen customer love like this in healthcare. After speaking with Vocca’s customers, we knew we had to back this company,” said Alexander Danielsson, General Partner at Norrsken VC. “The team’s vision goes far beyond phone calls. They’re building the healthcare experience every patient wishes they had.”

What the Funding Will Go Towards

Vocca will use the funding to build the best scheduling infrastructure in healthcare and the best interface for patients to reach it: new channels beyond voice, more specialties and more complex scenarios, and a deeper presence in the United States. The North Star is clear: remove the friction between a patient and care, so that every one of them gets through to the right slot, the right preparation, and the right care.

About Vocca

Vocca is the AI platform transforming access to healthcare. Founded in July 2024 by Eliott Hoffenberg and Hugo Danet, the company handles more than a million patient interactions a month and is live in 1,500 practices across twenty specialties, for dental, ophthalmology, medical imaging, general practice, and private hospital groups in the United States and Europe. Vocca has raised $25M to date.

Vocca runs separate production environments: data is hosted in the United States for American customers and in the EU for European ones. Its infrastructure partners are SOC 2, ISO 27001, and HDS certified. Vocca is built to meet HIPAA requirements and operates as a HIPAA Business Associate.

The company employs around 40 people in New York and Paris and is hiring 40 more across both by the end of the year.

About Norrsken VC

Norrsken is an impact-driven fund that makes big bets in healthcare and biotech, and it is backing a thesis Vocca has spent two years proving: healthcare does not get automated by general-purpose AI, it gets automated by a vertical player able to build inside healthcare’s actual constraints. Learn more at www.norrsken.vc.

Originally announced October 6th, 2026.



Sunday, October 18, 2026

< + > Bonus Features – October 18, 2026 – 74% of cyberattacks lead to disruptions in patient care, 56% of caregivers use AI tools to support their responsibilities, plus 30 more stories

Welcome to the weekly edition of Healthcare IT Today Bonus Features. This article will be a weekly roundup of interesting stories, product announcements, new hires, partnerships, research studies, awards, sales, and more. Because there’s so much happening out there in healthcare IT that we aren’t able to cover in our full articles, we still want to make sure you’re informed of all the latest news, announcements, and stories happening to help you better do your job.

Stats

Partnerships

Products

Implementations

Company News

If you have news that you’d like us to consider for a future edition of Healthcare IT Today Bonus Features, please submit them on this page. Please include any relevant links and let us know if news is under embargo. Note that submissions received after the close of business on Thursday may not be included in Bonus Features until the following week.



Saturday, October 17, 2026

< + > Weekly Roundup – October 17, 2026

Welcome to our Healthcare IT Today Weekly Roundup. Each week, we’ll be providing a look back at the articles we posted and why they’re important to the healthcare IT community. We hope this gives you a chance to catch up on anything you may have missed during the week.

Shifting With or Without Permission From the Healthcare System” at Withings. The company’s Antoine Pivron talked to John Lynn about consumer and physician interest in longitudinal monitoring of chronic conditions, even if business models still embrace fee-for-service care. Read more…

Announcements and AI Perspectives at Workday Rising. Many of today’s innovations don’t technically use use generative AI, John  learned – but generative AI opened the door for organizations to be more accepting of automations. But are orgs and their users ready for the pace of change? Read more…

Top Telehealth and Virtual Health Voices on LinkedIn. Get to know the health system, vendor, and professional organization leaders explaining trends, policy changes, and the latest research into telehealth outcomes. Read more…

Life Sciences Today Podcast: Revolutionizing Stroke Recovery. Danny Lieberman sat down with Dr. Leo Petrossian at Kandu, which is developing at-home brain-computer interface therapy for chronic stroke. Read more…

Healthcare IT Today Podcast: Is Healthcare Vulnerable to Runaway AI? John and Colin debated if healthcare is closer to AI-driven adverse events or true interoperability. Read more…

Audit Readiness Is Decided Months Before the First Chart Request Arrives. Readiness results from upstream conversations about how documents are structured, who owns the workflow, and whether key provider relationships already exist, noted Michael Egbert at Sherpas Healthcare Solutions. Read more…

Healthcare Sovereignty Is Overdue, and Patients are Demanding Better. Being granted access to your own data is not the same as having a say in it or the ability to contribute to it, said Jessica Chalk at myStoria. The fix is patient-directed data infrastructure governed by real interoperability standards. Read more…

Patient-Facing AI Must Know When to Call for Help. Healthcare is rolling out patient-facing technology that’s not equipped to answer the questions many patients have, according to Steve Pappas at eGain. AI systems need permission to say “I don’t know” and route patients to a human. Read more…

AI Will Turn Up the Heat on Humanity Before It Destroys Us. James Moade at Accreditation Commission for Health Care said there will be several warning signs that AI is taking over healthcare – namely, that no one knows who owns a decision and AI is acting on behalf of clinical teams. Read more…

A Successful AI Payer Call Should Leave More Than a Transcript. RCM teams still needs to know what the payer actually confirmed, how to verify it, what remains uncertain, and what should happen next, noted Rahul Agrawal at QuickIntell. Read more…

This Week’s Health IT Jobs for October 14, 2026: OrthoVirginia is looking for a Chief Medical Officer. Read more…

Bonus Features for October 11, 2026: 49% of patients have administered a self-test, and 43% have used an AI chatbot instead of seeing a doctor because of cost concerns. Read more…

Funding and M&A Activity:

Thanks for reading and be sure to check out our latest Healthcare IT Today Weekly Roundups.



Friday, October 16, 2026

< + > UrgentIQ Announces Strategic Growth Investment From Five Elms Capital

Five Elms Capital Leads Investment to Accelerate UrgentIQ’s AI Platform and Expansion Across the Rapidly Growing Urgent Care Market

  • UrgentIQ has received a Series A growth investment from Five Elms Capital, accelerating the company’s mission to build the definitive AI-native operating system for urgent care centers
  • The investment will accelerate UrgentIQ’s expansion beyond the EMR into a unified clinical and financial platform, including AI-powered documentation and coding, automated revenue cycle management, insurance verification, and checkout
  • Five Elms Capital brings deep experience scaling vertical AI-native software businesses and will support UrgentIQ as it continues to grow and innovate across the urgent care industry

UrgentIQ, the AI-native electronic medical record (EMR) purpose-built for urgent care centers, announced today a $15M Series A growth investment from Five Elms Capital. The partnership will accelerate UrgentIQ’s product roadmap to expand AI-powered clinical workflows while scaling the team to better serve a rapidly growing network of urgent care operators across the country.

Founded by Nat Gibbs, UrgentIQ has quickly established itself as an AI-native platform built specifically to support urgent care centers, earning a 9.7/10 average customer satisfaction rating. Unlike legacy EMRs adapted from hospital and primary care environments, UrgentIQ was built from the ground up around the unique economics and workflow of urgent care – where speed, throughput, documentation, coding, and collections are tightly interconnected. Customers leveraging UrgentIQ platform cited significant improvement in throughput times of patients in their facilities, through agentic AI-powered automation and a seamless experience for the end user.

“Urgent care is one of the most operationally demanding environments in healthcare: patients arrive sporadically and providers have minutes, not hours, to make decisions; plus every visit has to move seamlessly from care to payment,” said Nat Gibbs, Founder and CEO at UrgentIQ. “And yet, the industry’s core software was largely built for healthcare environments that operate nothing like this. We believe urgent care deserves its own operating system – one designed around speed, intelligence, and automation from the ground up. That is what we’re building with UrgentIQ.”

With Five Elms’ backing, UrgentIQ will accelerate development of its core platform, including a native billing module to bring revenue cycle management fully in-house, advanced AI-powered diagnosis and coding capabilities, live insurance verification, and an AI checkout agent. These capabilities are designed to help clinics see more patients, capture more revenue, and reduce administrative burden across every stage of the patient visit. As the urgent care market consolidates around private equity-backed platforms and multi-site groups, UrgentIQ is positioned to serve both independent operators and larger organizations seeking a modern, scalable platform that works across their entire network.

Joe Onofrio, Partner at Five Elms Capital, commented on the investment, “UrgentIQ has built a platform with exceptional operator adoption and product satisfaction, and the metrics reflect it. We are proud to partner with Nat and the team as they bring a modern, purpose-built solution to a market that has been long overdue for one.”

About UrgentIQ

UrgentIQ is the AI-native operating system for urgent care. Built from the ground up around the speed, throughput, and economics of walk-in care, UrgentIQ brings scheduling, patient intake, clinical documentation, AI-powered coding, revenue cycle management, and payments together on a single intelligent platform. By embedding AI directly into the workflows that run an urgent care center, UrgentIQ helps operators automate administrative work, move patients through care faster, and capture more of the revenue they earn. UrgentIQ is trusted by independent operators and multi-site urgent care groups across the country. For more information, please visit urgentiq.com.

About Five Elms Capital

Five Elms Capital is a growth investor in B2B software companies delivering innovative, AI-powered solutions to vertical end markets. We provide capital and resources to help companies accelerate growth and further cement their role as industry leaders.

With over $3 billion in assets under management and a team of over 80 professionals, Five Elms has invested in more than 70 software platforms worldwide. Beyond providing capital, Five Elms delivers strategic and operational expertise, focused on executing initiatives that move the needle on AI, growth, retention, and product to set companies up for long-term success. For more information, visit fiveelms.com.

Originally announced September 11th, 2026



Thursday, October 15, 2026

< + > H1 Acquires Defacto Health to Strengthen Provider Network Intelligence

Acquisition Brings Provider-Network Data and Experienced Healthcare Data Leaders to H1

H1, the AI-powered platform that connects the world to the right doctors, today announced it has acquired Defacto Health, a healthcare data company specializing in provider network intelligence. Defacto maintains data on payer networks, healthcare providers, and the insurance plans providers accept, helping health plans assess directory accuracy, isolate error clusters, and benchmark their networks.

The acquisition brings a longtime H1 data partner into the company and strengthens H1’s investment in the connected, high-quality healthcare data customers use to understand providers, networks, and access to care. Defacto will operate as part of H1, with co-founders Ron Urwongse and Tarun J. Theogaraj joining H1 to continue leading the work.

“Health plans are under continued pressure to maintain accurate provider directories while managing information that changes constantly across providers, facilities, plans, and networks,” said Ariel Katz, Co-Founder and CEO at H1. “We have worked with Defacto and know firsthand the value of its data and the expertise of its team. Bringing Defacto into H1 continues to strengthen the data foundation behind our platform and helps us continue to provide health plans and their industry partners with the tools and intelligence they need to understand their networks, identify inaccuracies, and make better-informed decisions.

Mr. Urwongse and Mr. Theogaraj bring longstanding experience in provider data and interoperability. Before founding Defacto, both led provider-data work at CAQH. Urwongse managed provider-data and interoperability solutions, while Theogaraj managed provider-data solutions and later led product work for CAQH’s flagship provider-data platform.

“Provider and payer data is complex, dynamic, and foundational to so many healthcare decisions,” said Ron Urwongse, Co-Founder of Defacto Health. “We built Defacto to make provider network information more accurate, accessible, and useful. Joining H1 gives our team the opportunity to invest further in that work and apply it within a broader healthcare intelligence platform that helps organizations connect with the right doctors.”

By bringing Defacto’s provider-network expertise together with H1’s healthcare data, technology, and AI, H1 will continue building a more connected view of the healthcare ecosystem, strengthening the intelligence that helps organizations identify, understand, and connect to advance the vision of connecting the world to the right doctors.

Financial terms of the transaction were not disclosed.

About H1

H1 is an AI-powered platform that helps identify and engage the right doctors for critical workflows across pharma, health plan, health system, and technology companies. At the core of the platform is H1’s Doctor Graph—a structured representation of physician identity, expertise, relationships, and behavioral signals, creating a powerful network effect as it is continuously enriched by participants across the healthcare ecosystem. Built on one of the world’s largest and most comprehensive global datasets of healthcare professionals, H1 combines deep healthcare data with agentic AI workflows to power critical workflows across drug development, medical and commercial engagement, care navigation, and provider data and network intelligence. Today, 85% of the top 20 pharmaceutical companies and 9 out of 10 of the top health plans trust H1 as a critical partner in building a healthier future for all.

Learn more at h1.com.

About Defacto Health

Defacto Health aggregates, organizes, and streamlines access to payer and provider data, helping organizations pursue innovative use cases across healthcare. Greater data liquidity and transparency unlock novel uses that will transform how healthcare is operated, organized, and accessed. Defacto’s team is led by provider-data and interoperability veterans who have deployed healthcare data sets used by hundreds of payers, millions of providers, and tens of millions of patients. Defacto works closely with payers to support compliance with government requirements and to provide constructive feedback on the data and APIs they publish, and collaborates with health tech innovators to understand their use cases and data needs.

Originally announced September 9th, 2026



Wednesday, October 14, 2026

< + > Patient-Facing AI Must Know When to Call for Help

The following is a guest article by Steve Pappas, Head of Innovation at eGain

Lately, it seems that we can’t turn on the TV or scroll through our social media feeds without stumbling across a high-level politician, news personality, or celebrity moralizing about the rapid rise of artificial intelligence (AI), especially in high-impact, customer-centric fields such as healthcare.

AI is rapidly becoming an integral part of the healthcare industry, transforming it in ways we could not have imagined even ten years ago. And while the technology offers the potential for greater efficiency in how providers diagnose, treat, and manage patients, its implementation and integration must first and foremost account for the single most important aspect of healthcare: the patient-provider relationship.

The Trust Factor

As more technology becomes embedded in the clinical decision-making processes of providers and the everyday care of patients, it is critical that AI be integrated in a manner that strengthens the relationship, not in a way that damages trust, empathy, or human connection.

Even today, many patient questions are answered through automated chatbots, but these tools cannot understand the nuances of every case or accurately resolve every interaction.

Patient-facing AI must be designed to recognize uncertainty and nuance and to escalate complex questions to a live representative. As these tools become more capable of recognizing their limits, trust in the process increases, and patient frustration declines.

When AI Misses the Warning Signs

Picture a woman in her 60s, two days out from a cardiac catheterization, opened her health system’s app at 11:40 on a Tuesday night and typed: “Is it normal for the puncture site to be warm and a little swollen?”

The chatbot immediately responds that the clinic is currently closed and will reopen at 9:00 a.m. the next day, then links to a page about parking.

This hypothetical experience encapsulates the entire problem in one sentence: the bot didn’t do anything wrong, it just didn’t know it was in over its head.

The healthcare industry is rolling out patient-facing technology that is not equipped to answer the questions many patients have. While AI can certainly field elementary inquiries such as billing questions, appointment scheduling, or parking details, in most deployments, the technology is incapable of recognizing the moment it starts to become harmful. In this example, AI provided the wrong answer in a confident manner, which means it stopped being useful and became dangerous.

If a true resolution isn’t within its capabilities, the system, in essence, provides a “close-enough” approximation with total composure, and the patient believes that the answer is reliable. In contrast, a real-life interaction is more instinctive. If a human representative doesn’t know the answer, they might, for instance, indicate that this is not their area of expertise and seek out another, more knowledgeable representative.

In other words, saying “I don’t know” is not necessarily a bad thing. In fact, it is a far more valuable response than a “close-enough” answer from an AI tool designed to eliminate “I don’t know.” Because these systems are ultimately measured by escalations (how many times they have to turn to a live representative), the designers tune them specifically to eliminate the one behavior that protects patients.

Teach AI What It Does Not Know 

If we don’t design a level of uncertainty into these systems, it is unlikely to appear on its own. So, instead of designing AI to be infallible, perhaps these systems should also account for areas where it is unsafe to approximate. I refer to this as “negative knowledge”: a list of topics for which the only answer is a real person, no matter how the question is phrased. These might include post-surgery symptoms, medication doses, or any time the word “fear” appears in a patient’s question.

One organization I worked with built a system with what the team referred to as a “boundary page.” It was a document just over a page long, maintained by a nurse informaticist and reviewed quarterly by a physician. The document listed every specific situation that would require the tool to stop and route the patient to a live representative. And although the document was simple in its wording, it was anything but simple in its scope, relying on more than two thousand articles for substantiation. Most importantly, it gave the system permission to say “I don’t know.”

Escalation is a Handoff, Not a Transfer

I’m quite sure that the most frustrating aspect of trying to connect with a healthcare facility is the endless phone queue or the chatbot that asks, “How can I help you today?” after you’ve spent the last 12 minutes filling out a form required to speak to it.

From a patient’s perspective, this repetitive experience is one of not being heard, akin to being passed around in a telephone loop and having to start from scratch every time a new person picks up the phone.

A true handoff, as opposed to a transfer, must contain four elements:

  1. Understanding: The initial “receiver” understands the full context of what was requested and catalogues the complete interaction
  2. Trust: The patient is told, in plain language, why they are being moved. In the example above, this would be the “I don’t know” scenario, and it represents real care, not a cold brush-off
  3. Exactness: The ultimate “receiver” is the right caregiver, not just the available one; anything else is just a delay tactic
  4. Honesty: If it’s too late at night to escalate to the right representative, the system should indicate this. If the matter is urgent, it should instruct the patient exactly what to do in the meantime; put the patient first

Escalation is Not Failure 

Most dashboards I have seen treat escalations as defects and are designed to drive escalation rates to zero. On the contrary, I would argue that a patient-facing tool that never escalates is likely answering questions that it shouldn’t.

And it’s not a complex measurement. If a patient contacts the system a second time or multiple times after the initial interaction, this is most likely indicative of a system that has decided it resolved something it really hasn’t. If a human auditor indicates that the interaction should have been escalated, that’s surely a “miss.” If a patient has to start over after a transfer, that’s a failure. If those three measurements are good, your system is likely operating successfully from both the patient and provider perspectives.

Accountability Cannot Be Automated

When a provider gives the wrong answer, it’s a mistake. The person who owns the knowledge owns the risk of making that mistake. AI tools should be, and already are in some industries, treated the same way. If a healthcare chatbot gives the wrong answer, the healthcare organization should be held accountable. Healthcare is not an exception.

Ultimately, this means that the system needs an owner, a review protocol, a review cadence, and an auditable version history. It means ensuring both legal and regulatory compliance and reviewing an organization’s responsibilities and authority (its boundary page) before incidents occur, not after. Lastly, it means establishing “I don’t knows” with a person who has actually spent time with patients and fully understands that some questions lead to more complex ones.

The Most Trusted AI Will Know Its Limits

Of course, none of this is an argument against the technology. These tools are already used to supplement overworked staff and provide answers during off-hours. But the systems that will earn patients’ trust over the next few years will be the ones built with humility and that know when to call for help.



< + > Key Healthcare Cybersecurity Lessons From the SHI Summit

I was excited to take part in my first ever SHI Summit hosted by the good people at SHI International .  They hold these Summits each quarte...