Healthcare Brew covers pharmaceutical developments, health startups, the latest tech, and how it impacts hospitals and providers to keep administrators and providers informed.

Healthcare Brew

Cassie McGrath

Healthcare Brew delivers the latest news and trends in healthcare.

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In 2017, Hurricane Maria devastated Puerto Rico.

The storm led to a collapse of the island’s healthcare system, a 

 reported, following power outages and a lack of disaster management plans that contributed to 3,000+ deaths. 

 in 2017 that Puerto Ricans living on the island already had low access to healthcare before the hurricane hit. Years after the storm, the region faced ongoing staffing shortages and issues with federal funding that restricted care, 

That’s why, in October 2017, Emmanuel Oquendo and Israel Figueroa founded BrainHi, a health tech company with an AI receptionist called Lara, which completes administrative tasks for providers. The tool can answer missed calls and schedule appointments, and is designed to reduce clinicians’ workloads. Some of the company’s clients include NeoMed Center, Ashford Hospital, Manatí Medical Center, and Mennonite Healthcare System, all based in Puerto Rico. 

Oquendo spoke with Healthcare Brew about his goals for the company going forward.

This interview has been edited for length and clarity.

Do you solely serve Puerto Rico at the moment? Are you looking to expand?

When we launched, we were very focused on that critical moment in Puerto Rico [after Hurricane Maria], and how we can help our island and providers.

 face a unique challenge, just like Puerto Rico, where the staff is often overwhelmed by daily demand, and they’re not able to serve all the patients. So what we found is that Puerto Rico is not the only place in the US that may find these sorts of issues and may need automation. Puerto Rico remains to be the core of our company, but we work with health centers in Florida and in other places in other parts of the US.

You introduced AI for administrative tasks before its current rise in popularity. What have you learned from this experience?

We’ve been working nearly a decade on this.

We’re not only focused on the AI component but we offer a full digital front-door platform that serves as a host for all the communication that is happening, and it facilitates and streamlines a collaboration between AI and the human side. That’s what’s given us a great advantage as we expand now and accelerate growth because now that we are gaining a ton of traction and there’s 

, we’re ready for this. We’re ready—not only with the technology, but we deeply understand the workflows and the integrations that are required to really 

What separates AI receptionist Lara and BrainHi from your competitors?

In addition to the comprehensive platform, we stand out in a crowded place of 

 because we’re looking beyond transactional interactions. Our focus is on building a trusted, long-term relationship between the AI and patients because we believe that the next frontier for AI is to create human connection at scale.

Let’s say that Lara has a call with a patient. As soon as we get that first call, we start creating a profile on that patient that goes far beyond what is documented in the electronic health record.

What we found is that getting all these personal notes about the patient and understanding what they need allows us to personalize that relationship much more. We still believe that AI is not there yet in terms of being completely human, if you will. But by being very diligent on understanding the patient’s needs, understanding their preferences, actively listening to the patient, and taking notes on the conversation, we’ve seen that it greatly impacts engagement.

Emmanuel Oquendo, founder of AI administrative company BrainHi

Meet Emmanuel Oquendo, founder of AI administration company BrainHi 

This founder made an AI admin tool in response to Hurricane Maria’s impact on Puerto Rico. 

Welcome back to AI 411, a monthly roundup of artificial intelligence (AI) announcements from across the healthcare industry.

This month, the FDA announced the launch of a large language model (LLM) AI tool named Elsa. In a 

 on its website, the FDA said that Elsa is designed to “summarize adverse events to support safety profile assessments, perform faster label comparisons, and generate code to help develop databases for nonclinical applications.” It marks the agency’s first step in its AI journey.

But that wasn’t the only news this June. Here’s your roundup of health-related AI updates from around the industry.

 On June 11, the AMA adopted a new policy calling for “explainable clinical AI tools” that give users clear information about the safety and efficacy of the product. In other words, the AMA is asking AI tool companies to provide clear explanations of how their tools work so clinicians can make the best decisions when using them.

Cigna announced on June 12 the release of several new digital tools, including an AI virtual assistant that can chat with patients about insurance and care options on the company’s app. Soon, the company said in a release, the tool will include new provider matching technology that connects patients with clinicians based on insurance and needs.

Digital musculoskeletal clinic Hinge Health announced on June 17 the release of HingeSelect, a provider network powered by AI and designed to connect patients to in-person care at low prices.

Software company LeanTaas announced its new AI-powered tool iQueue for Surgical Clinics on June 10, which will use AI modules to help coordinate surgeries from the administrative side to the operating room, including case-building, patient outreach, insurance authorizations, scheduling.

AI assistant company Nabla, known for its ambient scribe, announced a $70 million Series C funding round on June 17. Fundraising was led by HV Capital, with additional investment by venture capital firms Highland Europe, DST Global, Cathay Innovation, and Tony Fadell's Build Collective. The company has so far raised $120 million, and new money will go toward product development and expansion.

On June 2, the Massachusetts Institute of Technology and biotech Recursion announced the release of Boltz-2, an open source AI that helps pharmaceuticals design small molecule drugs by predicting if they will work effectively on patients.

The University of Texas MD Anderson Cancer Center and HealthEx. 

MD Anderson and tech company HealthEx announced on June 9 a strategic collaboration to develop AI tools that can support the patient consent process and make it easier for patients to control how their data is used.

Mental health company Wysa announced on June 11 the launch of Wysa Gateway, a chatbot that uses AI to facilitate conversations between therapy providers and health plans.

Healthcare Brew monthly series on AI Startups

AI 411: June 2025

Your monthly roundup of AI announcements is here.

AI regulations in healthcare are, well, sort of nonexistent at the moment.

 from regulating AI for the next 10 years, though that was scrapped from the June 6 

 for a new proposal that restricts broadband funding in states that regulate AI.

, and according to the Deloitte Center for Health Solutions, 75% of top healthcare companies are experimenting with generative AI. The research organization also reported that 82% of healthcare organizations plan to “implement governance and oversight structures for generative AI.”

That’s where the public-private Coalition for Health AI, or CHAI, comes in. Launched in December 2021, the group of 3,000 providers, tech companies, and other healthcare organizations—including Mayo Clinic, Cleveland Clinic, and Mount Sinai—are working together to create standards for AI in healthcare.

 for responsible AI use in healthcare, released last June, which companies can reference when building out their models, including principles of trustworthy AI, system design, and monitoring.

“It started with a group of eight of us in the private sector coming together, agreeing that this is an effort building best practice frameworks,” Brian Anderson, CEO at CHAI, told Healthcare Brew. The group hopes to “provide the kind of guardrails and guidelines that build trust” across the spectrum, from payers to providers to patients.

One of the core tenants of CHAI’s guidelines is that “transparency is critical,” Anderson said.

The company has what it calls a model card, which Anderson described as a “nutrition label” with information like metric goals, warnings, and testing types so providers and health companies can see what sorts of AI practices others use. For instance, if the Mayo Clinic had a new AI note-taking tool it was using, the model card would outline how the health system uses it, metrics to show performance (such as its safety and usefulness), and potential risks, biases as well as ethical considerations to keep in mind.

Fairness is also a key tenant of CHAI, Anderson said, to ensure training models are “highly effective on people” across the country, from rural states to urban areas to tribal nations.

CHAI’s focus is on the tech side, Anderson said, and it doesn’t advocate for any specific external regulations or federal policies.Though he said many members are most interested in regulations that don’t stifle innovation or create an “uncoordinated patchwork set of state regulations,” he added.

“We want our public-sector colleagues to see CHAI as a resource to educate them on the principles of responsible AI and how the private sector is adopting, implementing, and moving forward in that space,” he said.

On June 11, CHAI announced a new partnership with the Joint Commission, a nonprofit that also sets standards for healthcare and accredits hospitals. For instance, the organization doles out a Gold Seal of Approval to healthcare organizations that hit certain quality and safety measures.

Together, the two organizations hope to “accelerate the development and adoption of AI best practices and guidance across the US healthcare system” by creating AI rules and tools as well as a new certification program “rooted in the Joint Commission’s platform for evidence-based standards and CHAI’s consensus-based best practices for health AI,” according to a release.

That guidance is coming in the fall, followed by the accreditation, the release said.

Another priority for the organization this year, Anderson said, is to connect with smaller providers, like 

, to “make an intentional, significant effort to build playbooks for those community clinics that don’t have the kinds of resources that an [academic medical center] has.”

The organization also announced Kyu Rhee, president and CEO of the National Association of Community Health Centers, as a new board member in February as a part of these efforts.

What are the benefits of CHAI for companies?

Emmanuel Oquendo, CEO of software company BrainHi, became a member of CHAI in November.

BrainHi, based in San Juan, Puerto Rico, helps automate phone calls and other operations for medical practices that need 

Oquendo joined CHAI, he said, because one of the organization’s principles is to ensure AI algorithms and models “are fine-tuned for specific communities’ needs.”

“There are some algorithms that might work great for a Caucasian community but not necessarily for 

He was also inspired to join because CHAI provides an opportunity to learn and network with other healthcare experts about using AI “responsibly and securely,” he said.

Oquendo is now part of a CHAI working group developing guidelines on deploying AI chatbots in healthcare, and said CHAI provides him with valuable guidance to bring back to his own company’s best practices. “I felt that I would get very important information by being part of the community that I could share with my customers,” he said.

AI lacks regulations in healthcare. The Coalition for Health AI set some guidelines

AI use is growing in healthcare. But regulations aren’t. 

AI lacks regulations in healthcare. This group set some guidelines

 (AI) has made its way into healthcare, from 

 are already happening, and there’s no doubt that AI is starting to change how care is delivered.

Already 75% of big healthcare companies are “experimenting with or planning to scale generative AI across the enterprise,” according to Deloitte Center for Health Solutions.

But less discussed are the potential downsides of this new technology. Just as the implementation of electronic medical records 

—like easier collaboration across departments, but more time at the computer—it’s likely AI will see a similar varied trajectory.

“There’s vast amounts of marketing hype [around AI], compared to the actual clinical proof,” James Barlow, a professor at Imperial College Business School in London, told Healthcare Brew. “How do you as a company or developer actually build up an evidence base for the claims you’re making?”

We spoke with experts about the potential challenges AI presents to healthcare, and how the industry can best guard itself against them.

To build models, most AI tech is trained using existing data, whether that's

published research or a patient’s chart. That means, in order to work well, the tools must have access to accurate and high-quality information. But experts are concerned whether this is happening.

 in general, but in healthcare, it could make the quality of care worse, especially for higher-risk patients, Barlow said. “What base are you training the AI on? Are the datasets representative? If they’re not, they might produce biased results.”

Harish Yalamanchili, a surgeon at vascular clinic Coastal Vein Care in California

said understanding what sources data is trained on is “one of the most important things.”

“How careful are you in generating and making sure that your sources are carefully vetted?” he said, adding that “we’re running out of data to build our AI.”

 publishers and other online sources are preventing their information from being used to build AI. In other words, AI needs existing information, but many sources have already been used or are getting restricted.)

There’s concern this could lead companies to “loosen the restrictions a little bit,” on the quality of data used to build platforms, Yalamanchili said.

“AI for me should be a tool that makes your ability to treat people easier,” Yalamanchili said. “The outcomes have to be equivalent to the outcomes without AI, or better.”

Though, he added, he also worries these tools could make it easier to miss errors introduced into a patient’s chart. “If you have a corrupt data point anywhere…how do you know what the reality was before this?” he said.

Bad data or errors could create mistrust between clinicians and patients, Barlow added. There’s also 

In terms of building up guardrails around these challenges, Barlow said a lot of it comes down to trust.

“[Building trust] requires being very open and transparent about the data that’s being used, the quality of the data, how you’re designing the algorithms that use that data, whether you’re using advanced datasets,” he said.

It’s also important to follow any future laws that may emerge, he said. There are currently no “absolute” regulations for AI in healthcare, Yalamanchili added, though organizations like the American Medical Association and Coalition for Health AI have 

Yalamanchili said including more clinicians in leadership could also help, as they know what would best support staff and patients.

“The way we’re going about it, and just throwing all these darts at the dartboard, and hoping that one of them hits bull’s-eye,” he said. “We’re talking about actual human lives,” said.

Experts share how to protect against the downsides of AI in healthcare 

There’s a lot of hype about AI in healthcare, experts say, but being transparent is essential.

Cue Diana Ross, as San Francisco-based virtual health provider Omada Health is “coming out” as a public company.

The company debuted on June 6, ending the day at $19 per 7.9 million shares. But the next morning its stock rose to $23 per share, a 21% jump that the company is touting alongside a $150 million fundraise following its IPO.

 the company at just under $1.3 billion, up from $1.1 billion before going public, according to 

Omada works to support patients with diabetes, hypertension, prediabetes, and musculoskeletal issues. In 2023, it launched a GLP-1 program for patients with obesity.

 a new AI agent called OmadaSpark, which will provide patients with nutrition education, support, and care for healthy eating.

The company declined to comment, citing the “post-IPO quiet period.” But

John Beadle, co-founder and manager partner of investment firm Aegis Ventures, 

“Notably, it is the only venture-backed IPO in the current market where the IPO price was set above the most recent private market valuation,” he told Fierce, adding that Omada “demonstrated superb discipline and rigor” in how it structured its offering.

Morgan Stanley, Goldman Sachs, and JPMorgan were lead book-running managers for the IPO.

Orange stethoscope forming a dollar sign on blue background. Horizontal composition with clipping path and copy space.

Omada Health IPO debuts with $150m fundraise 

Omada Health also just launched an AI agent at the end of May. 

This month, health tech companies saw big fundraisers and announced new products that use AI to support patient care.

Let’s get into it. Here is your roundup of health-related AI updates from May.

Akido, a Los Angeles-based care delivery company announced a $60 million Series B funding round on May 15. Funding was led by venture capitalist Oak HC/FT. The money will be used to bring to more patients the company’s system, ScopeAI, which supports medical appointments with AI tools that listen, take notes, and build clinical reports.

New York startup Complement 1, a health tech that uses AI to personalize lifestyle treatments for patients with cancer, announced a $16 million seed round on May 13. The platform helps people experiencing issues with sleep and pain through lifestyle adjustments including “physical activity, nutrition, and somatic practices,” and the funding round was led by Owl Ventures and Blume Ventures.

San Francisco-based virtual provider Omada Health launched a new product called OmadaSpark on May 20. It’s an AI agent that will work with the company’s patients to provide nutrition education, support, and care for healthy eating.

 Massachusetts-based AI-based pharmacy tech company Scripta launched a new GLP-1 navigator in its app on May 20. Members can now see advice and resources related to weight management on the company’s Rx Navigation platform, which provides patients with pricing information on weight loss medications.

Voice AI company SoundHound AI, based in Santa Clara, California, announced May 29 a partnership with Minneapolis-based health system Allina Health. Under the partnership, SoundHound AI will deploy its AI agent Alli, which will answer phone calls and help manage appointments.

Hoboken, New Jersey-based publication and research company Wiley announced May 5 a new collaboration with Amazon Web Services to create a generative AI agent that supports searches for scientific literature. According to a press release, “the AI agent will demonstrate how researchers can conduct comprehensive full-text scientific literature search” of Wiley’s journals. The approach is different from traditional searches because it will allow for not just abstract-only searches but also method- and results-based searches, the company said in the release.

AI 411: May 2025 edition

Maia Anderson

Medicare may soon be able to reimburse physicians for using artificial intelligence-based medical devices, thanks to a bipartisan bill recently introduced to Congress.

The bill, called the Health Tech Investment Act, would set up a payment system for devices that use AI or machine learning, which the bill’s cosponsors say would encourage providers to use the technology in clinical settings and help improve diagnoses.

“Medicare patients deserve access to the life-changing care that artificial intelligence-enabled devices can offer,” Sen. Mike Rounds of South Dakota, one of the bill’s cosponsors, said in a statement on April 10. “There is currently no clear Medicare payment system for these devices, meaning that it can take years to be approved and paid out by Medicare accurately.”

If the bill is signed into law, it would create a temporary Medicare payment code for devices that use AI, machine learning, or “other similarly designed software.”

That temporary code would be applied to the devices for at least five years, during which time the Centers for Medicare and Medicaid Services (CMS) would collect data to determine a permanent payment code, according to a press release from the bill’s cosponsors.

 While the bill, if passed, would be a good first step toward creating a payment system for AI-based devices, it probably wouldn’t “open up the flood gates” for Medicare to actually start covering them widely, according to Jenn Kerfoot, chief strategy and growth officer at health tech company Duos, which works with Medicare beneficiaries.

For one, the bill’s wording is somewhat ambiguous in terms of what medical devices would be covered by the payment code, Kerfoot said.

AI-based medical devices also aren’t at the top of the priority list for many payers or health systems at the moment, according to Kerfoot.

“Hospital systems right now are trying to debate if they need to buy a new MRI machine because it’s about to be hit by a 

,” she said, adding that finding room in budgets for health systems and payers right now may be difficult because they need to balance changes in risk adjustments, Part D policy, and drug and utilization costs.

It’s unclear what kind of financial impact paying for AI-based medical devices would have on Medicare.

There may be an initial increase in spending at first, Kerfoot said, but in the long term, the devices could lead to cost savings. With some AI-based devices able to detect diseases earlier, they “really can reduce that need for more expensive interventions later,” she said.

For example, a deep learning tool developed at Washington State University detects disease in human tissue faster and at a higher accuracy rate—and more consistently over time—than humans when reviewing histopathological slides, according to a 2024 

The bill, if passed, could also spur development of new and improved AI medical devices, Kerfoot noted, as more companies may be willing to throw their hat in the ring if they know there’s a 

The use of AI in healthcare has grown substantially in recent years, with 66% of about 1,100 physicians in 2024 reporting they used AI as part of their workflows, up from 38% in 2023, according to a 

There hasn’t been any movement on the bill since it was introduced last month, but AdvaMed, the medical device industry’s largest trade group, has lauded the legislation, with its President and CEO Scott Whitaker saying in a statement that it “is critical to advancing the medical progress upon which patients depend.”

A healthcare professional’s hand interacting with the touchscreen of a medical device screen displaying treatment options.

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