AI-Native Artera Fills Gaps in Care and Provider Performance

In this lively interview, Guillaume de Zwirek, CEO & Co-Founder at Artera, lays out a vision for patient access where AI provides speedy handling, comprehensive gap coverage, and insightful feedback to providers at a level beyond what humans could do.

De Zwirek offers an excellent, articulate summary of how AI can simplify patient access workflows  with patients. Using everyday language, the agent recognizes the type of request (appointment scheduling, medication refill, medical question) and expertly navigates the provider’s systems to complete it, asking the patient for missing information such as family history. If payer requirements must be satisfied—as they so often are—Artera can generate the right questions to ask for each payer and store the results.

But AI agents created by Artera can do much more. While meeting the patient’s current needs, the agent can check for coverage gaps and handle them on the same call. It can point out that a family member needs a check-up, or ask whether the patient knows that dental coverage is available.

To show the power and reach of Artera’s AI, de Zwirek described a struggling Federally Qualified Health Center that was falling behind even with a 200-person call center. At first, finding that most incoming calls were about scheduling, the AI produced an excellent scheduling agent that worked in multiple languages. Then it turned to care gaps. For a health center drowning in scheduling calls, this is what modern patient access software looks like: an AI scheduling agent that works in multiple languages and books the visit on the first call, instead of a queue that still falls behind.

The manager at the center explained that when they found a care gap and called a patient to schedule an appointment, the call usually went unanswered. Artera took a totally fresh approach. Because most patients call in regularly for one task, the agent identified the care gaps applying to the patient at that time and filled the gaps on the call with the patient rather than calling back later and no one answering.

Provider quality measures are also improved by Artera, because it is as transparent as possible and produces reports describing the decisions AI makes. Thus, if a provider is wondering why it’s not getting as many patient appointments as it wants, it can ask Artera to examine calls and uncover the problem: a major insurance company that’s not accepted, or rules that screen out potential patients.

De Zwirek decried the traditional interactive voice response systems based on rigid trees of questions (what the computer field calls “deterministic” responses). For one thing, these systems waste precious time when the patient has an urgent call about a fall or burn. Second, they can’t handle the infinite variety of patient experiences and needs. He mentioned a provider who had to deal with 21,000 payers: no phone tree could embody all that variety, but AI voice can.

Security also came up. Generic LLM providers take in private data, and it has been shown to leak into other clients’ conversations. Artera self-hosts all its models—six currently—and doesn’t release data. However, they do listen to each call to evaluate quality.

An automated call system is necessary not only for the patient experience but to handle call center burnout. De Zwirek pointed out that everybody enters the health care field because they care about doing a good job, and they are discouraged by “soul-killing” work.

Early in the interview, de Zwirek describes the evolution of Artera over its ten years: first a simple messaging service, then integration with EHRs and other systems to automate routine communications, then deterministic automation. Now AI is central: the company is AI-native, which de Zwirek defines as meaning that the company would be unable to function without its LLMs. In fact, the company itself runs 40% more effectively than it did a year ago.

He also provides an interesting description of how they reduced the layers between the customer and the developer. Instead of many types of marketing and product development staff: they have only two points of contact with the provider: a developer whom he calls a “builder,” and a client experience manager.

Watch our interview with Guillaume de Zwirek from Artera to learn more about how their AI-native approach is improving healthcare.

Learn more about Artera: https://artera.io/

Listen and subscribe to the Healthcare IT Today Interviews Podcast to hear all the latest insights from experts in healthcare IT.

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.

Artera is a proud sponsor of Healthcare Scene.

In this lively interview, Guillaume de Zwirek, CEO & Co-Founder at Artera, lays out a vision for patient access where AI provides speedy handling, comprehensive gap coverage, and insightful feedback to providers at a level beyond what humans could do.

De Zwirek offers an excellent, articulate summary of how AI can simplify patient access workflows  with patients. Using everyday language, the agent recognizes the type of request (appointment scheduling, medication refill, medical question) and expertly navigates the provider’s systems to complete it, asking the patient for missing information such as family history. If payer requirements must be satisfied—as they so often are—Artera can generate the right questions to ask for each payer and store the results.

But AI agents created by Artera can do much more. While meeting the patient’s current needs, the agent can check for coverage gaps and handle them on the same call. It can point out that a family member needs a check-up, or ask whether the patient knows that dental coverage is available.

To show the power and reach of Artera’s AI, de Zwirek described a struggling Federally Qualified Health Center that was falling behind even with a 200-person call center. At first, finding that most incoming calls were about scheduling, the AI produced an excellent scheduling agent that worked in multiple languages. Then it turned to care gaps. For a health center drowning in scheduling calls, this is what modern patient access software looks like: an AI scheduling agent that works in multiple languages and books the visit on the first call, instead of a queue that still falls behind.

The manager at the center explained that when they found a care gap and called a patient to schedule an appointment, the call usually went unanswered. Artera took a totally fresh approach. Because most patients call in regularly for one task, the agent identified the care gaps applying to the patient at that time and filled the gaps on the call with the patient rather than calling back later and no one answering.

Provider quality measures are also improved by Artera, because it is as transparent as possible and produces reports describing the decisions AI makes. Thus, if a provider is wondering why it’s not getting as many patient appointments as it wants, it can ask Artera to examine calls and uncover the problem: a major insurance company that’s not accepted, or rules that screen out potential patients.

De Zwirek decried the traditional interactive voice response systems based on rigid trees of questions (what the computer field calls “deterministic” responses). For one thing, these systems waste precious time when the patient has an urgent call about a fall or burn. Second, they can’t handle the infinite variety of patient experiences and needs. He mentioned a provider who had to deal with 21,000 payers: no phone tree could embody all that variety, but AI voice can.

Security also came up. Generic LLM providers take in private data, and it has been shown to leak into other clients’ conversations. Artera self-hosts all its models—six currently—and doesn’t release data. However, they do listen to each call to evaluate quality.

An automated call system is necessary not only for the patient experience but to handle call center burnout. De Zwirek pointed out that everybody enters the health care field because they care about doing a good job, and they are discouraged by “soul-killing” work.

Early in the interview, de Zwirek describes the evolution of Artera over its ten years: first a simple messaging service, then integration with EHRs and other systems to automate routine communications, then deterministic automation. Now AI is central: the company is AI-native, which de Zwirek defines as meaning that the company would be unable to function without its LLMs. In fact, the company itself runs 40% more effectively than it did a year ago.

He also provides an interesting description of how they reduced the layers between the customer and the developer. Instead of many types of marketing and product development staff: they have only two points of contact with the provider: a developer whom he calls a “builder,” and a client experience manager.

Watch our interview with Guillaume de Zwirek from Artera to learn more about how their AI-native approach is improving healthcare.

Learn more about Artera: https://artera.io/

Listen and subscribe to the Healthcare IT Today Interviews Podcast to hear all the latest insights from experts in healthcare IT.

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.

Artera is a proud sponsor of Healthcare Scene.