Healthcare IT Today sat down with Robert DeLuca, EHR Innovation Administrator at MedFlorida Medical Centers. We explored the realities of deploying eClinicalWorks AI tools, particularly for RCM, and how getting it right benefits both clinicians and the billing team.

Key Takeaways

• AI is a Growth Engine: AI in the revenue cycle is about scaling a practice efficiently. By speeding up the billing process, practices can confidently expand locations and add new providers without straining their existing administrative infrastructure.
• Nip Claim Rejections in the Bud: The best time to fix a claim is before it ever leaves the exam room. Point-of-care AI that prompts clinicians to correct insufficient documentation immediately eliminates the time-wasting back-and-forth with the billing department.
• Ambient Listening is a Powerful Recruiting Weapon: Ambient AI scribes have evolved from a simple documentation aid into a non-negotiable recruiting asset. Recognized widely by clinicians as a way to reduce charting fatigue, AI scribes are now seen as a must-have.

AI is a Growth Engine

For DeLuca, Implementing automation is fundamentally about increasing capacity and not about cutting staff. MedFlorida wanted to expand and he understood that their internal administrative workflows needed to keep pace. DeLuca believed that AI could provide the efficiency that they needed to scale.

“Our goal with AI for billing was to make it more efficient so that we can take on more and grow,” DeLuca stated. MedFlorida successfully implement eClinicalWorks’ RCM AI. With it, the organization can manage a higher volume of claims smoothly without the need to add billing staff who are increasingly difficult to hire and retain.

Nip Claim Rejections in the Bud

A rejected claim is a massive drain on resources. It creates a frustrating loop between the billing department and the provider. Catching documentation errors at the point of care changes the entire dynamic.

With eClinicalWorks’ RCM AI, the system alerts a clinician that information may be missing in order to bill properly. By prompting immediately, the fix takes seconds, without any back-and-forth with the billing team.

“It’s hard to quantify exactly, but you can imagine how much time that is saved,” explained DeLuca. “Had that claim been submitted, it may have been rejected or the billing department may have caught it. In either case, they would have to send that progress note back to the clinician to fix it. With eClinicalWorks the clinicians knows to fix it in the moment.”

That simple prompt eliminates the claim reject-fix loop that is universally despised.

Ambient Listening is a Powerful Recruiting Weapon

Clinicians documenting late into the night benefits no one. Introducing ambient listening tools directly targets this “pajama time”, keeping providers focused on patients instead of screens.

The technology is so effective that it has become a core part of the hiring pitch and a retention tool. “I know for a fact that when clinicians leave our practice, wherever they’re going, they’re looking for ambient listening because they’ve had it here,” observed DeLuca. “They’re addicted to it, and they don’t they don’t want a workflow without it,”

DeLuca firmly believes that if you are not offering these tools, you are losing top talent to practices that do.

The Bottom Line for Health IT Leaders

For DeLuca and MedFlorida, eClinicalWorks’ RCM AI is tool that enables growth and expansion. By eliminating time-consuming loops in their RCM process, the team has increased their capacity without adding people. They realized similar benefits with AI scribe technology. Seeing AI as a growth enabler is powerful reframe for MedFlorida leadership and for them, AI has quickly become a baseline for running a modern, competitive practice.

What Healthcare IT Leaders Are Asking

How does AI reduce claim rejections in healthcare? AI reduces claim rejections by analyzing documentation at the point of care and prompting clinicians to correct missing or mismatched information before the progress note is finalized – a key feature of eClinicalWorks’ RCM AI. This proactive approach ensures the billing department receives a clean claim. It stops the cycle of returning notes to busy providers for revisions.

How does AI help a billing department scale? The primary function of AI in the revenue cycle is to increase efficiency. By automating repetitive tasks and catching errors early, current billing teams can process a larger volume of claims. This allows practices to grow and add new providers while maintaining a smooth administrative workflow.

Why are AI scribes important for recruiting clinicians? AI scribes, like Sunoh.ai, are important for recruiting because clinicians are actively seeking workplaces that prioritize their well-being. Tools that automatically draft clinical notes save hours of administrative work and significantly reduce burnout. Providers who have experienced this workflow consider it a necessity and will choose practices that offer it over those that do not.

Learn more about MedFlorida Medical Centers at https://medflorida.com/

Learn more about eClinicalWorks at https://www.eclinicalworks.com/

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Here’s a preview of the topics and questions we discuss in this episode:

• Who should be on the Mount Rushmore of Health IT Companies?
• Who would be on your own personal Health IT Mount Rushmore?

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AI in healthcare is massive right now. And I think the best way to look at it is this: there are so many use cases, but nothing has actually been adopted into our daily lives in a way that changes what the job feels like.

Healthcare was built largely by people from non-clinical backgrounds, and that matters because the problems they designed solutions for are not always the problems physicians actually have. The low-hanging fruit everyone is going after right now is the administrative side: paperwork, filling out applications, and reading notes. That stuff is real. It takes up a lot of time. But what often gets missed is that even when you free up that time, two things tend to happen.

One, physicians are asked to learn, train on, and integrate yet another tool. That adjustment takes energy, and that is where a lot of the fatigue comes from. Two, when AI frees up time from writing notes, that capacity often gets absorbed by increased patient volume rather than returned as breathing room. Health systems are under enormous pressure to do more with less, and efficiency gains tend to get reinvested into throughput. That is understandable, but it means the burnout equation does not change the way we hope it will.

So at the end of the day, burnout isn’t really addressed. We’re still overworked because we’re still understaffed.

The Efficiency Trap

This is not a theoretical concern. A peer-reviewed study published in Learning Health Systems in 2025 by researchers at UC Davis and UC San Diego concluded that it is premature to assert that AI tools will reduce physician burnout, noting that rapid AI adoption could introduce new stress as the apparent needs of health systems are not always aligned with those of their human workforce. That finding should give health IT leaders pause before positioning AI as a burnout solution to their boards and clinical staff.

There is also a subtler problem with how AI lands at the clinical level. Every new tool requires learning, workflow adjustment, and integration into an already complex environment. Physicians and their staff spend an average of 13 hours each week on prior authorizations alone, and 89% say the process significantly or somewhat increases burnout, according to the AMA’s 2024 survey of 1,000 practicing physicians. Adding more technology to that environment, even technology designed to reduce burden, carries its own cognitive cost. The push-pull of adopting new platforms is itself a source of fatigue that rarely appears in vendor ROI projections.

What Is ‘Credentialing’ and Why Is It Such a Hidden Area of Stress for Physicians?

Credentialing is the formal process by which hospitals, health systems, and insurance networks verify a physician’s qualifications, confirming their medical degree, training, licensure, board certifications, and work history before granting privileges to practice. It is a necessary safeguard, but in practice it has become one of the most time-consuming administrative hurdles in medicine, often taking 90 to 180 days at a single institution. For health IT leaders already investing in tools to reduce documentation burden and improve physician satisfaction, credentialing represents a critical gap in the stack. There is little standardization across hospitals or payers, meaning the same documents are submitted, verified, and re-verified repeatedly with no shared infrastructure to streamline the process, a problem that technology is well-positioned to solve, but one that rarely appears on the AI investment roadmap.

The consequences show up directly in the burnout and retention data that health systems are trying to address. McKinsey’s research found that 51% of physicians identify schedule flexibility as a key retention factor, yet the administrative friction around credentialing makes that flexibility nearly impossible to act on. When a physician wants to pick up a shift at a new facility, cover in an underserved area, or diversify how they work, a months-long credentialing process becomes a hard barrier. For organizations serious about workforce mobility and physician retention, modernizing credentialing workflows is not a back-office concern; it is a frontline priority. The same energy being directed toward AI-powered documentation tools needs to extend to the infrastructure that determines whether physicians can access work opportunities in the first place.

Looking Ahead – Addressing What Physicians Actually Need  

The data on what physicians actually need has been consistent for years. McKinsey’s physician survey found that physicians dissatisfied with their schedules report burnout at a rate of 66%, compared to 52% for those working more than 60 hours per week. Schedule control matters more than hours worked (Medford-Davis et al., 2024a). The same research found that 87% of physicians say the ability to take time off is important, and 77% cite finding coverage when needed as a key factor, neither of which is addressed by a documentation tool.

What physicians actually want is simpler: the ability to work where they want, when they want, without a months-long administrative process standing between them and the opportunity. We have been trained since residency to pick up extra work, cover shifts, and contribute across settings. The physicians I see who are most engaged are not necessarily the ones with the best documentation tools. They are the ones who have some degree of control over their schedule and their career.

For health IT leaders, this distinction matters because it changes what you should be building and buying. Tools that reduce documentation burden are worth pursuing, but they should be scoped accurately. They improve efficiency, they may improve satisfaction at the margin, and they will not solve systemic burnout. The organizations that will make a real dent in physician retention are the ones investing in workforce flexibility alongside AI, giving physicians meaningful schedule control and direct access to opportunities without the administrative friction that currently sits between a qualified physician and the work they want to do.

McKinsey’s retention research found that 51% of physicians identify schedule flexibility as a key retention factor, yet only 59% of workplaces are actively pursuing such enhancements. That gap, between what physicians say they need and what health systems are actually building, is where the next generation of workforce tools needs to focus.

I think AI is going to revolutionize healthcare. I really do. But I don’t think we’re solving the right problems yet. The tools that are going to make a real difference are the ones that give physicians back some control over how and where they work, not just tools that let us write notes faster while we see more patients.

We went into medicine to take care of patients. The tools that actually help us do that are the ones that give us back some control over how we work.

About Marc Ayoub

Marc Ayoub, MD, is the Founder of Saile and an Assistant Professor of Neurosurgery at the Donald & Barbara Zucker School of Medicine. A practicing neurocritical care physician, he built Saile as a healthcare staffing and credentialing platform that functions like a universal credential passport and direct-to-facility marketplace; so clinicians can take their file anywhere, plug into shifts faster, and help facilities unlock local talent without relying on expensive, legacy agency models.

Aidoc Raises $150 Million Series E Led by Goldman Sachs to Scale Clinical AI for Earlier, Safer Diagnoses

The Funding Accelerates Expansion of Aidoc’s Clinical Foundation Model and Enterprise AI Platform to Combat Diagnostic Harm and Improve Efficiency Across Health Systems

Aidoc, a global leader in clinical AI, has raised $150 million in Series E funding led by Growth Equity at Goldman Sachs Alternatives. The round had participation from General Catalyst, SoftBank Vision Fund 2, and NVentures (NVIDIA’s venture capital arm). The round brings total funding to over $500 million, less than a year after a growth round led by General Catalyst and Square Peg. This underscores the pace of Aidoc’s momentum and the accelerating demand for enterprise-scale clinical AI.

Diagnostic errors and delays contribute to at least 400,000 deaths each year in the United States, driven by rising imaging volumes, workforce shortages, and growing clinical complexity. While AI has long promised to reduce that burden, most tools have tackled one use case at a time, limiting their impact at scale.

As hospitals seek broader, system-wide solutions, the market is shifting toward clinical AI deployed across entire health systems. Foundation models have made that shift technically possible by enabling expanded coverage across conditions and imaging modalities from a single architecture. Translating that capability into regulated, real-world care, however, has proven far more complex. Aidoc developed its own clinical foundation model, CARE, and deployed it through its enterprise platform, aiOS. Earlier this year, CARE received a landmark first FDA clearance for a comprehensive double-digit foundation model-based triage system in clinical imaging. Today, the company analyzes more than 60 million patient cases annually and is deployed across nearly 2,000 hospitals, signaling a new phase in the adoption of clinical AI.

“By 2030, every complex diagnostic decision should be supported by AI that enables earlier detection and reduces preventable error,” said Elad Walach, Co-Founder and CEO at Aidoc. “We feel a deep responsibility to deploy CARE safely and at scale across health systems. This funding accelerates comprehensive disease coverage and advances end-to-end AI across CT and X-ray, spanning the full workflow, including pixel to draft report within two years.”

As clinical AI moves to enterprise deployment, a determining factor is governance and regulatory discipline. In large, complex health systems, scale requires not only advanced technology but the oversight and accountability needed to operate safely in real-world care.

“Aidoc pairs advanced technology with regulatory rigor in a way that few companies have achieved,” said Christian Resch, Partner at Growth Equity at Goldman Sachs Alternatives…

Full release here, originally announced April 29th, 2026.

Iterative Health Closes $77 Million Series C to Accelerate the Future of Clinical Research

Led by Intrepid Growth Partners and GV (Google Ventures), Funding Advances Iterative Health’s Position as the Leading Multispecialty Clinical Research Network

Iterative Health, a healthcare technology and services company powering the acceleration of clinical research, today announced the close of a $77 million Series C financing round. The round was led by Intrepid Growth Partners and GV (Google Ventures), joined by new investors EDBI (arm of SG Growth Capital, the investment platform of EDB and Enterprise Singapore) and a prominent family office, and participation from existing investors such as Insight Partners and Obvious Ventures.

Clinical trials are critical in bridging scientific discovery and patient care; however, systematic challenges delay the delivery of new therapies to patients who need them most. More than half of research sites enroll one or fewer patients per study, and nearly 90% of US-based trials fail to meet enrollment targets on time, underscoring the constraints on sites operating in an increasingly complex research environment.

Iterative Health is addressing these challenges by building a high-performing, multispecialty clinical research network that embeds research directly into clinical care. Unique from traditional research networks, the company places site success at the center of trial execution. By combining centralized operations, expert staffing, proprietary AI technology, and deep clinical trial expertise, Iterative Health developed a proven site-serving model for sustained site success and reliable trial execution. Sponsors and CROs gain centralized access to industry-leading sites and diverse patient populations, accelerating trials to advance the future of care.

Today, Iterative Health’s global network includes more than 100 research sites across North America, Europe, India, and Australia, as well as partnerships with over 40 pharmaceutical, biotech, medical device, and contract research organizations. Compared to industry benchmarks for IBD trials, the network delivers 2x faster site activation, reducing startup timelines by up to 3 months, and 3x higher patient enrollment rates, with an average of more than two IBD patients randomized every business day across the global site network.

“Every delay in a clinical trial is a delay for patients whose outcomes depend on faster access to innovation. By keeping our physician partners and their patients at the center of our model, we’ve built a system that delivers high-performance site execution at scale,” said Jonathan Ng, MBBS, Founder and CEO at Iterative Health…

Full release here, originally announced April 30th, 2026.

Partnerships

• CareQuest Innovation Partners and PDS Health are collaborating to expand blood pressure screening and patient consultation in dental settings.
• Talkdesk Healthcare Experience Cloud is now integrated with Epic Caboodle, the company’s enterprise data warehouse.
• SEQSTER and Astute are partnering to help organizations access patient data across clinical settings.
• The Veeva Vault Platform is now connected to Snowflake‘s AI Data Cloud for Healthcare & Life Sciences.
• Training programs from Skilltrade are now available in ShiftMed‘s workforce optimization platform.
• Care management and remote monitoring technology from ThoroughCare is now integrated with Withings smart scales.
• Decision support technology from VisualDx is now integrated with Perplexity‘s Premium Health Sources.

Products

• Artera unveiled its AI Services Model for specialty care, FQHCs, IDNs, and federal agencies.
• Assort Health launched Assort Activate, which delivers personalized patient outreach across channels.
• Diagnostic testing company BillionToOne launched Unity Confirm to help analyze fetal DNA.
• Substance use disorder patient engagement application CaredFor launched its post-discharge Measurement Based Care platform.
• Google announced Chrome Enterprise Premium, which extends Chrome with enterprise-grade security and management capabilities for healthcare.
• Infinitus Systems launched Lens to help organizations evaluate AI agent calls and human-led calls using the same criteria.
• Mental healthcare provider Lyra Health updated its Empower platform with AI capabilities for members, providers, and employers.
• RxUtility launched Mimi, an AI agent for understanding medication cost options. It’s free to use while in beta.
• Tether launched QVAC MedPsy, a medical language model designed to run directly on smartphones, wearables, and other devices with limited processing power.
• VisiQuate launched Policy Pulse to help healthcare organizations identify payer policy changes before they go into effect and understand their likely operational and financial impact.
• WEDI launched a testing directory for organizations to find testing partners for the CMS Advancing Interoperability and Improving Prior Authorization Final Rule, which has a January 1, 2027 deadline.
• Zyter announced Zyter Praxis to help health plans embed automated workflows into enterprise operations.

Implementations

• Georgia-based Wellstar Health System selected BD to support medication dispensing and infusion.
• Massachusetts-based Holyoke Medical Center is partnering with IKS Health in an effort to improve clinical and revenue optimization.
• The Africa Clinical Research Network selected Oracle Life Sciences to launch its first clinical trial, which aims to predict the absence or occurrence of severe pre-eclampsia-related maternal and fetal outcome.
• Pennsylvania’s St. Luke’s University Health Network chose RapidAI to support imaging analysis in stroke care in the operating room.

Company News

• A RevSpring survey found 58% of patients would look for a new provider if they were unhappy with appointment or billing communication.
• Color’s Virtual Cancer Clinic earned ASCO Certified status.
• Transplants.org debuted as a patient education and care navigation platform for organ and stem cell transplantation.

People

• Heart and lung disease detection company Eko Health appointed Dr. Steven R. Steinhubl as Chief Medical Officer.
• Independent medical practice software maker AdvancedMD appointed Brandon Russell as Chief Customer Officer.
• Radiology workflow orchestration vendor NewVue named Patrick Zientara as Chief Revenue Officer.

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.

Happy Mother’s Day, everyone!

Hearing Firsthand How AI Is Being Applied in Healthcare. John Lynn attended Navina’s Ascend 2026 User Event, where sessions emphasized AI done right looks through the lens of the clinician, value-based care is a struggle, and officials at ONC and CMS are more than willing to listen. Read more…

The Quintuple Aim of Value Based Care Enabled by The Garage.  John also had the opportunity to attend the FUSE 2026 User Event put on by The Garage.  The conference focused on value based care and how organizations can leverage policy, process, and technology to achieve better value based care outcomes. Read more…

Unpacking Smart Data Archiving Features. Mike McGuire at MediQuant sat down with John to talk about using AI to gather insights from legacy data sources – including summarizing archived data, analyzing DICOM images, and even retrieving patients’ financial files. Read more…

Ensuring Successful Epic Go-Live With Real-Time Training Dashboards and Personalization. Dr. Rajeeb Khatua at ReMedi Health Solutions and Dr. Sara Helvey at Care New England discussed how specialized training paired with robust metrics contributed to successful Epic implementation. Read more…

Intelligent Monitoring Catches Accidental and Malicious Email Breaches. Brittany Quemby chatted with Andrew Goodman at Proofpoint about monitoring incoming and outgoing communication, with the latter bolstered by analysis of typical behavior for each user. Read more…

Life Sciences Today Podcast: Replacing the Microsoft Word Protocol. Danny Lieberman caught up with Scott Chetham at Faro Health, which built an AI platform that can do in 60 minutes what previously took multiple clinical trial design experts three weeks. Read more…

CIO Podcast: Balancing Hospital Needs, Technology, and Innovation. Nitin Agarwal at Pennsylvania’s Wayne Memorial Hospital joined John to discuss the intersection of AI, interop, EMR, ERP, and hospital operations. Read more…

The Speed of Trust: Why Healthcare IT Fails the “Midnight User.” Digital health tools struggle with retention when they’re harder to use that a search bar, said Lineo Chale at Perkily. Organizations need to build tech to support the high-stakes situations when users need answers they can actually act on. Read more…

From Visibility to Automation: The Next Evolution of RTLS in Healthcare. HT Snowday at Midmark RTLS said the value of real-time location services is what the data enables, from process automation to safety alerts to actionable operational insights. Read more…

Healthcare Needs More Than the Model Context Protocol. MCP addresses communication between agents and data sources but isn’t a framework for coordination, noted Adam Farren at Canvas Medical. Healthcare needs an AI orchestration layer with the EHR as its hub. Read more…

Why MDM Implementations Fail, and How to Get Them Right. Boiling the ocean is one of the most consistent drivers of MDM failure, said Verato’s Cheryl Griffin. Successful projects start small, but with clearly defined objectives that build trust and allow for deliberate scaling. Read more…

Beyond Data Exchange: The Next Era of Interop Is Inside Clinical Workflows. True interoperability is surfacing relevant information and predictive, prescriptive recommendations at the exact moment a decision needs to be made, according to Jonathan Shoemaker at ABOUT Healthcare. Read more…

This Week’s Health IT Jobs for May 6, 2026: Ohio-based Summa Health is looking for a CISO. Read more…

Bonus Features for May 3, 2026: 81% of patients repeat the same personal information multiple times to the same provider, plus 61% of orgs have made outsourced managed services a core part of IT strategy. Read more…

Funding and M&A Activity:

• Life sciences commercial execution support company AcuityMD raised $80 million in Series C funding.
• Claims and denials management company Joyful Health raised $22 million in funding.
• Clinical decision support platform Almanac Health raised a $10 million seed round.
• Prior authorization and medical-necessity automation company Ethermed raised $8.5 million in Series A funding.
• Wearable vendor ŌURA acquired Galen AI, a personal health companion.
• IKS Health acquired TruBridge, which provides healthcare technology solutions for rural and community hospitals.
• Specialty practice software maker ModMed acquired Bonsai Health, an agentic AI patient engagement platform.
• Medical imaging IT and cybersecurity company Sectra acquired Oxipit, a provider of autonomous AI for radiology.

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

This week’s Fun Friday is a bit of satire about the Canadian healthcare system.  If you listen to the Healthcare IT Today podcast, then you’ve probably heard Colin and I compare the US healthcare system to Canada in many episodes.  As you’d expect, there are pros and cons to every system.  I’m sure this points out some of the cons, but it’s pretty funny.

Full Disclosure: We love our Canadian healthcare friends starting with Colin and Brittany on the Healthcare IT Today team.

Thanks to everyone for supporting Healthcare IT Today.  We’ll be back next week with more great healthcare IT content.  Have a great weekend!

From a published Merck study showing $130M in cost avoidance to becoming the first company to automate study builds directly into Veeva, Faro Health is quietly becoming the backbone of protocol design for 6 of the top 10 pharma companies. We also dig into the future of vertical integration in drug development — from molecule discovery all the way through automated clinical monitoring.

Check out the main topics of discussion for this episode of the Life Sciences Today podcast:

• What is an Australian doing in the US, working in clinical development? How did that happen?
• Tell us what you’re doing at Faro Health.
• Who are your sponsors, and how do you create value for them?
• How do you capture value? What is your business model?
• What’s your superpower?
• What are three things you want to do for your sponsors in 2026?
• I’ve been thinking about vertical integration, on and off, for the past ten years. How great would that be?
• What is the biggest anti-pattern in the industry?

Subscribe to Danny’s newsletter to get strategic patterns for life science leaders building a defensible business.

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Along with the popular podcasting platforms above, you can Subscribe to Healthcare IT Today on YouTube.  Plus, all of the audio and video versions will be made available to stream on Healthcare IT Today. As a former pharma-tech founder who bootstrapped to exit, I now help TechBio and digital health CEOs grow revenue—by solving the tech, team, and go-to-market problems that stall your progress. If you want a warrior by your side, connect with me on LinkedIn.

If you work in Life Sciences IT, we’d love to hear where you agree and/or disagree with our takes on health IT innovation in life sciences. Feel free to share your thoughts and perspectives in the comments of this post, in the YouTube comments, or privately on our Contact Us page. Let us know what you think of the podcast and if you have any ideas for future episodes.

Thanks so much for listening!

In the rush to digitize healthcare, the industry has fallen into a “complexity trap.” We frequently celebrate the launch of robust platforms capable of managing everything from electronic records to wellness tracking, yet we often overlook the most critical metric of all: the time-to-value for a concerned user. When a health question arises in the middle of the night, a user isn’t looking for a “comprehensive digital ecosystem.” They are looking for a bridge between their symptoms and a credible, immediate solution.

The Psychology of the Search Bar

The reason most digital health tools struggle with long-term retention isn’t a lack of engineering; it’s a failure to compete with the simplicity of a search bar. When professional tools feel like a chore to navigate, buried behind multi-step registrations or cluttered dashboards, users default to general search engines.

This creates a dangerous feedback loop. Search algorithms are optimized for engagement and clicks, not clinical validity. For the average person, a simple search for a persistent symptom doesn’t lead to evidence-based advice; it leads to a rabbit hole of worst-case scenarios and unverified anecdotes. This “Dr. Google” effect places an immense burden on the healthcare system, as clinicians must spend valuable consultation time undoing the misinformation their patients gathered online.

Closing the 17-Year Knowledge Gap

The challenge isn’t limited to patients. The medical community faces a staggering “evidence lag”—the reality that it takes nearly two decades for breakthrough clinical research to become standard bedside practice. This gap exists because the latest peer-reviewed data is often buried in fragmented journals or locked behind paywalls, making it inaccessible during the high-pressure moments of care.

To solve this, we must move away from “feature-heavy” apps and toward specialized decision-support tools. This is where the intersection of AI and evidence-based medicine becomes transformative.

The Evolution of Clinical Decision Support

Modern healthcare IT must prioritize tools like AskFleming that are calibrated for clinical reasoning rather than surface-level summaries. By pulling directly from PubMed, clinical trials, and systematic reviews, these platforms can surface the specific level of evidence behind every answer in seconds.

When we integrate these referenced answers at the point of care, we empower both the provider and the patient. Instead of a clinician navigating “40 open tabs” to verify a protocol, they can access cited research instantly. Instead of a parent spiraling into anxiety over an unverified blog post, they can access information grounded in peer-reviewed reality.

Building for Utility, Not Just Presence

The future of healthcare IT isn’t about who has the most features; it’s about who provides the most clarity. We need to build tools that respect the user’s time and the gravity of their questions.

If we want to see real retention and clinical impact, we must start building for the “midnight moment”—the high-stakes, high-stress window where a user needs an answer they can actually act on. By shortening the distance between the laboratory and the living room, we don’t just build better apps; we build a more informed, safer healthcare system.

About Lineo Chale

Lineo Chale is a Health Information Manager at Perkily. She specializes in digital health and healthcare IT, focusing on using AI to simplify complex health decision-making for patients and clinicians alike. She is passionate about closing the gap between clinical research and everyday patient care. You can connect with her on LinkedIn.

AcuityMD Raises $80M for AI Augmentation to Medtech Sales Platform

AcuityMD has raised $80M to advance its provision for assisting medtech companies in accelerating the adoption of their products across healthcare settings and geographic markets.

The Boston-based company’s Series C financing round was led by existing investor StepStone Group. VC firms Benchmark, Redpoint Ventures, ICONIQ, and Atreides Management also participated.

Used by 16 of the top 20 medtech companies, AcuityMD’s platform identifies metrics including physicians, facilities, networks, procedures, and reimbursement dynamics. Aggregating this data alongside medtech companies’ internal data, including contracting information, product indications, territory structure, and CRM activity, companies can better estimate commercial execution and reach the right end markets for their products.

With the fresh funding in hand, which brings AcuityMD’s total funding to date to over $160m, the company plans to augment its existing platform with artificial intelligence (AI) with the launch of AcuityAI. According to AcuityMD, its AI platform’s overall aim is to avail medtech company sales representatives with more streamlined insights.

As well as advancing its AI capabilities, AcuityMD also intends to use the funding towards deepening the medtech ontology of its data model, and to expand the platform beyond commercial pursuits, with a view to accelerating adoption across the full product lifecycle.

AcuityMD CEO, Mike Monovoukas, commented, “AI will transform medtech, but only with the right context, deeply embedded in the workflows where decisions are made. AcuityMD is that context layer, serving the rep in the field, the commercial leader planning territories, and the teams launching the next generation of innovation.”

AI is having an appreciable impact on driving efficiencies in the broader healthcare space…

Full release here, originally announced April 22nd, 2026.

Almanac Health Raises $10 Million to Empower Clinicians Across Specialties with Safe, Research-Validated Clinical AI

Seed Round Led by F-Prime, with Participation from General Catalyst and Lightspeed Venture Partners; General Catalyst Previously Led the Pre-Seed Round

Almanac Health, a research-validated clinical AI platform and evidence-based clinical decision support company founded by physician-researcher Cyril Zakka, MD, whose work at Stanford introduced retrieval-augmented generation to clinical medicine, has raised $10 million in a seed round led by F-Prime, with participation from General Catalyst and Lightspeed Venture Partners. General Catalyst previously led the company’s pre-seed round with participation from Soma Capital. This financing brings Almanac Health’s total funding to nearly $12 million and will accelerate the company’s mission to bring safe, evidence-grounded AI to clinicians and health systems.

Almanac Health is a unified clinical AI platform for clinical decision support that brings specialist-grade knowledge to every clinician at the point of care. It is designed to work within existing electronic health record (EHR) systems, governed by institutional controls, and grounded in peer-reviewed evidence. The platform is currently undergoing rigorous clinical validation in academic medical center settings.

“There is no shortage of technologies promising to transform medicine. But few are grounded in real evidence, built with integrity, and deserving of trust from the people and organizations using them. Almanac Health’s goal is to build clinical AI held to that standard. Validated through research, with incentives aligned with clinicians and patients. We’re focused on getting that right,” said Cyril Zakka, MD, Founder and CEO at Almanac Health.

Cyril Zakka, MD, has worked at the intersection of medicine and AI across clinical practice, academic research, and industry. After earning his MD, he went on to conduct machine learning research at Stanford, where he developed the first retrieval-augmented generation system for clinical medicine, an approach to grounding AI in trusted medical knowledge that has since been widely adopted across clinical AI. That work, published in NEJM AI, became one of the journal’s most-cited papers and established the foundational approach used by most clinical evidence AI products today. He subsequently led health AI at Hugging Face, the largest open-source AI platform, before founding Almanac Health.

“Cyril is one of the rare founders who has both the clinical training and the technical depth to build AI that clinicians will actually trust, as well as the discipline to validate it before deploying it. Almanac Health represents what we believe the next generation of healthcare AI should look like: grounded in research, governed by institutions, and built with incentives that put clinicians and patients first,” said Carl Byers, Partner at F-Prime.

The funding will allow the company to grow its team across clinical medicine…

Full release here, originally announced April 23rd, 2026.