Monday, August 10, 2026

< + > CIO Podcast – Episode 119: Improving Through Data and Research with Eric Lee

For the 119th episode of the CIO podcast hosted by Healthcare IT Today, we are joined by Eric Lee, MD, Chief Health Information Officer at AltaMed Health Services, to talk about improving with data and research! We kick this episode off with Lee sharing his experience with the KLAS Arch Collaborative. Next, we discuss some of the results Lee saw from the survey. Using that same survey, we then get into what Lee has done or is looking to do based on the results. Then Lee shares a recent successful project he’s worked on at AltaMed, and we dig into what went into the project and what made it a success. We then dive into AI to discuss what we now understand about AI in healthcare and what we are still trying to figure out. Lastly, Lee passes along the best piece of advice he’s been given in his career.

Here’s a look at the questions and topics we discuss in this episode:

  • What’s been your experience with the KLAS Arch Collaborative?
  • What are some of the results you saw from the survey?
  • What have you done or what are you looking to do based on these results?
  • What’s a recent project you’ve worked on at AltaMed that was a success? What went into the project and what made it a success?
  • What do we now understand about AI in healthcare, and what are we still figuring out?
  • What’s the best piece of advice you’ve been given in your career?

Now, without further ado, we’re excited to share with you the next episode of the CIO Podcast by Healthcare IT Today.

We release a new CIO Podcast every ~2 weeks. You can also subscribe to the Healthcare IT Today podcast on any of the following platforms:

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We appreciate you listening!

Listen to the Latest Episodes



< + > What Makes a CIE Work? Five Lessons from the Field

The following is a guest article by Mark Taylor, VP of Product Strategy at Ready Computing

Community Information Exchanges (CIE) are often described as technology initiatives. In practice, the successful ones are much more than that. A CIE works when it helps real people coordinate care across health, social care, government, and community-based organizations without forcing every partner to abandon the systems and workflows they already use.

The goal is not just to exchange data. It is to make it easier to identify needs, connect people to services, close the loop on referrals, measure outcomes, and support the organizations doing the work.

Our experience supporting social care and whole-person care initiatives across New York State’s 1115 Waiver, Georgia’s statewide CIE infrastructure through GaHIN, and the Connect2 network in Washington State has shown that the strongest CIEs share five core traits.

1. They Start with the People and Services, Not the Technology

A CIE should be designed around how people actually move through care. That means understanding where needs are identified, how referrals are made, who follows up, and what information frontline teams need at each step.

In New York’s 1115 Waiver work, the challenge is not simply collecting HRSN screening data. It is helping social care networks operationalize screening, eligibility, referrals, consent, service delivery, and reporting across many different organizations.

The same principle applies in Washington State’s Connect2 network. The value of the platform is not just that data can move. It is that organizations can coordinate around people in a more consistent, connected way.

A working CIE supports the journey from need to service, not just the movement of records.

2. They Connect Existing Systems Instead of Replacing Them

Community networks are diverse by nature. Hospitals, health plans, HIEs, government agencies, social care organizations, and community-based providers often use different tools. A CIE that requires every participant to adopt one new system creates friction before the work even begins.

The stronger model is interoperability. Let organizations keep the systems that already support their operations, while creating a shared infrastructure for exchange, orchestration, and oversight.

This is central to the work we support across these networks. In Washington State, secure, standards-based exchange powers the Connect2 infrastructure. In Georgia, the work with GaHIN supports broader statewide infrastructure that connects health and social care data across a complex ecosystem.

A CIE works when it becomes the connective layer, not another silo.

3. They Build Trust Through Governance, Consent, and Compliance

CIEs handle sensitive information across organizations that may have different responsibilities, regulations, and levels of technical maturity. Trust is essential.

That trust depends on clear rules for participation, strong privacy and consent management, secure hosting, and compliance practices that give partners confidence. This is especially important when social care data is being connected with clinical or payer data.

In New York’s 1115 Waiver environment, consent, eligibility, and service documentation are not side issues. They are foundational to making the model work at scale. In Georgia, statewide exchange requires a similar focus on governance, security, and reliability.

A CIE cannot succeed if participants do not trust how data is protected, shared, and used.

4. They Make Frontline Workflows Easier

The success of a CIE depends heavily on adoption. If the platform adds administrative burden, frontline organizations will struggle to use it consistently.

That means the system needs to support practical workflows: screening, referral management, eligibility checks, service documentation, status updates, closed-loop communication, reporting, and escalation. It also needs to work for organizations with different staffing levels and technical resources.

The best CIEs reduce duplicate entry, make the next step clear, and help teams see what has already happened. They also provide flexibility, because the workflow for housing support may look different from food assistance, transportation, home modifications, or substance use disorder-related services.

A CIE works when it makes coordination simpler for the people doing the coordinating.

5. They Prove Value Through Data, Reporting, and Outcomes

CIEs need to show impact. That means capturing not only referrals, but whether needs were met, services were delivered, gaps remain, and outcomes improved.

For social care networks under the NYS 1115 Waiver, reporting and payment-related workflows are critical. For statewide efforts like GaHIN, the ability to reduce silos and provide a broader view of community health needs is essential. For Connect2, the value lies in creating the infrastructure needed to support more coordinated, community-centered care across the network.

The strongest CIEs create visibility at multiple levels: for care teams, for network operators, for funders, and for policymakers. They help answer practical questions: Who needs help? What services are available? What happened after the referral? Where are the gaps? What is working?

A CIE becomes sustainable when it can demonstrate measurable value.

A successful CIE is not defined by a single platform, referral tool, or data standard. It is defined by whether it helps communities work together more effectively.

The most effective CIEs are built around people, designed for interoperability, grounded in trust, aligned with frontline workflows, and measured by outcomes. Across New York State, Georgia, and Washington State, one lesson is clear: CIEs work when they connect more than systems. They connect organizations, services, and people around a shared model of care.

About Mark Taylor

Mark Taylor is VP of Product Strategy at Ready Computing, a healthcare technology leader with experience advancing interoperability and connected care across complex health and social care networks. He focuses on how technology can help organizations coordinate services, address social needs, and support more connected models of care.



< + > RevealDx Announces Distribution Agreement and Investment | Prosper Medical Raises $16M

Check out today’s featured companies who have recently raised a round of funding, and be sure to check out the full list of past healthcare IT fundings.


RevealDx Announces Distribution Agreement and Investment from 4DMedical

4DMedical to Distribute RevealAI-Lung in the US, Europe, Australia, and New Zealand

RevealDx, a leader in AI characterization of lung nodules, announced today, following World Lung Cancer Day, a distribution agreement and strategic investment of $3.4 million by 4DMedical (ASX: 4DX), expanding access to its flagship product, RevealAI-Lung. RevealAI-Lung has received MDR Certification, TGA Approval, and FDA clearance. In the transaction with 4DMedical, Chestnut Partners, Inc. served as the exclusive financial advisor to RevealDx.

This news follows 4DMedical’s recent acquisition of Austrian-based Contextflow. 4DMedical, a global medical technology company, is revolutionising respiratory care through advanced imaging and artificial intelligence. Contextflow offers advanced chest CT technologies that automate the identification of lung nodules. RevealAI-Lung has been integrated into the Contextflow platform and is already operational at several clinical sites across Europe.

The RevealDx technology characterizes incidental lung nodules by producing a Malignancy Similarity Index (mSI), a score that helps radiologists make more informed follow-up recommendations to assist in cancer diagnosis. The company has validated the software on over 1,500 patients from a variety of cohorts.

The RevealAI-Lung CADx device offers several key capabilities, including:

  • Significant improvement in Radiologist reader performance
  • Use of real-world NLST data as our reference population
  • Clinically relevant malignancy scoring
  • First-ever integration directly into PACS, vastly improving workflow
  • Proven generalizability across exam types and patient populations

“We are excited to announce our new partnership with 4DMedical,” said Chris Wood, CEO at RevealDx. “As we recognize World Lung Cancer Day, this milestone underscores our commitment to helping clinicians identify potentially malignant lung nodules earlier and with greater confidence. The incredible team at 4DMedical and the resources they bring will expand our reach and benefit patients.”

Andreas Fouras, Founder and CEO at 4DMedical, said, “For 4DMedical, this is about more than adding products. It is about building a connected ecosystem for cardiopulmonary care. CT:VQ gives physicians physiological insight into how the lung is actually functioning. By surrounding that capability with disease detection and AI-powered risk stratification, we can help health systems identify the right patients earlier and ensure they receive appropriate care. The result is a platform that has the potential to improve outcomes for patients while increasing utilization of advanced functional imaging across vital disease areas.”

In addition to its recent regulatory milestones, RevealAI-Lung is reimbursable by Medicare in the United States under CPT codes 0721T and 0722T, helping to support broader clinical adoption.

About RevealDx

RevealDx has developed RevealAI-Lung, the first Medical Imaging AI software to achieve reimbursement in both the US and EU. The company has published several studies demonstrating significant improvement in both early cancer detection as well as reduction in false positives. Studies show that by integrating this patented technology into routine clinical use, healthcare providers can more effectively triage lung nodules. For more information, contact sales@reveal-dx.com.

Learn more at reveal-dx.com

About 4DMedical

4DMedical Limited (ASX:4DX) is a global medical technology company revolutionising respiratory care with advanced imaging and artificial intelligence. Its patented XV Technology transforms standard scans into rich, functional insights that allow physicians to detect, diagnose, and monitor lung disease earlier and with greater precision.

4DMedical’s expanding software portfolio includes the FDA-cleared XV Lung Ventilation Analysis Software (XV LVAS), CT LVAS, and the ground-breaking CT:VQ solution designed to set new benchmarks in cardiothoracic imaging by combining ventilation and perfusion analysis.

Delivered seamlessly through a Software-as-a-Service (SaaS) model, 4DMedical’s solutions integrate into existing hospital infrastructure, enhancing physician productivity and enabling more personalised patient care. With the addition of advanced AI capabilities from its 2023 acquisition of Imbio and 2026 acquisition of contextflow, 4DMedical continues to push the boundaries of medical imaging to redefine how respiratory disease is understood and treated worldwide.

Learn more at 4dmedical.com

Originally announced August 3rd, 2026.


Prosper Medical Raises $16M to Bring AI-powered Concierge Care to All

Prosper Medical today announced $16 million in financing to scale its AI-powered concierge primary care platform. The company was founded by Ryan McQuaid and James Wantuck, MD, who previously built and sold PlushCare, one of the country’s first direct-to-consumer telehealth platforms, for $450 million. Now they’re back, and they’re using AI to address one of healthcare’s most persistent challenges: delivering personalized, seamless primary care at scale.

While telemedicine made healthcare more convenient, McQuaid and Wantuck came away with a larger realization: convenience alone doesn’t solve the primary care crisis. The real problem is a trusted relationship. Most Americans don’t have a physician who knows them well, really listens to them, and cares about them. That kind of care has always existed, but for most people it’s been out of reach, and Prosper was built to change that.

“When we built PlushCare, we learned that making appointments easier wasn’t enough,” said Ryan McQuaid, Co-Founder and CEO at Prosper Medical. “The real challenge is everything that happens after a patient leaves the visit. Following up on test results, finding the right specialist, collecting comprehensive health data, and preventing major problems before they arise. AI finally gives us a way to deliver that level of care and personalization at a scale that wasn’t possible before.”

The goal isn’t to replace physicians, but to supercharge them in caring for their patients. Prosper’s platform maintains continuity across every patient interaction, aggregates all of your health data, coordinates care, and ensures important data signals and communication don’t get lost between appointments. The result is a Prosper doctor who arrives with context, Prosper AI that can intervene earlier, a Care Concierge Team, and a healthcare experience that feels far more personal than traditional primary care.

Unlike many concierge or membership-based healthcare services, Prosper is designed to be accessible to more than only the ultra-wealthy…

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



Sunday, August 9, 2026

< + > Bonus Features – August 9, 2026 – 57% of home- and community-based providers evaluating AI tools, 28% of patients have put off canceling an appointment because it required a phone call, plus 25 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.

News and Stats

Partnerships

Products

Implementations

Company News

People

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, August 8, 2026

< + > Weekly Roundup – August 8, 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.

Keeping the Patient at the Center of Large-Scale Technology Deployment. John Lynn connected with Lindsey Bengfort at NTT Data to discuss trying to manage the pace of change with AI, especially from the start of a pilot to the time to ramp up adoption. Read more…

Turning Data Into Actionable Insights. Renee Wiczorek at Truven by Merative gave John a demo of the company’s dashboards and insights, which help organizations evaluate program benchmarks and determine where investments will have the biggest impactRead more…

Integrating Back-Office Systems With Clinical and Front-End Applications. The Healthcare IT Today community is solving this challenging problem with flexible infrastructure, platforms, device-level security, ambient documentation, and AI agents embedded in clinical workflows. Read more…

Life Sciences Today Podcast: Scaling Physical Therapy Without New Clinics. Danny Lieberman connected with Dr. Ashok Gupta at TheraNow, which uses virtual physical therapy to help health systems expand capacity without adding buildings or staff. Read more…

Healthcare IT Today Podcast: Leadership Succession. In light of Sumit Rana leaving Epic, John and Colin Hung discussed whether a company’s leadership and succession plan matters to customers, along with how to ensure a smooth path forward. Read more…

The Growing Gap Between Healthcare Risk and Healthcare Governance. AI can help organizations improve threat detection, prioritize alerts, and streamline security operations, but AI cannot compensate for fragmented governance or inconsistent risk management practices, noted Sam Peters at IO. Read more…

How to Maintain Patient Care During Communications Outages. Lori Stone at First Responder Network Authority, the overseer of national broadband network FirstNet, explained how FirstNet supports direct communications and acts as backhaul for Wi-Fi and other systems. Read more…

The Denial Economy Is Asymmetric. Knowing That Can Start to Fix the Issue. John Beene at Soupy Audit explained why providers don’t audit Recovery Audit Contractor extrapolations – and why they should respond by flagging risks, tracking payer activity, and monitoring changes in demand. Read more…

Taking a New Approach to Physical Security in Healthcare. It’s difficult for humans to continuously monitor live video for potential signs of security threats. Shikhar Shrestha at Ambient.ai described agentic physical security that can reason about what’s happening, decide if it matters, and initiate the right response. Read more…

How Trust-Centric Design Reduces Patient Stress and Retains Users. Yuliia Apanasenko at Phenomenon Studio provided four user experience principles that help reduce uncertainty and guide patients toward the next step in their care journey without leaving them to figure it out themselves. Read more…

This Week’s Health IT Jobs for August 5, 2026: Houston-based Texas Children’s Hospital seeks a CISO. Read more…

Bonus Features for August 2, 2026: Vizient projects 8% increase in healthcare IT spending for 2027; 70% of clinicians chart outside of working hours. Read more…

Funding and M&A Activity:

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



Friday, August 7, 2026

< + > How TheraNow Scales Physical Therapy Without New Clinics – Life Sciences Today Podcast Episode 73

We’re excited to be back for another episode of the Life Sciences Today Podcast by Healthcare IT Today. My guest today is Dr. Ashok Gupta, Founder and CEO at TheraNow. In this episode, I speak with Dr. Gupta about why the real bottleneck in physical therapy isn’t quality — it’s access. Dr. Gupta explains how TheraNow built a virtual physical therapy model that helps health systems expand capacity without adding buildings or staff, and why 99% of the company’s revenue now comes from hospitals and their outpatient networks. Our conversation covers the shift from pre-COVID resistance to post-COVID reimbursement, the operational moat created by combining software with a 39-state clinician network, and why fragmented tools fail when they don’t fit clinical workflows. 

We also dig into a core industry anti-pattern: putting care in the wrong physical location, where even parking and travel time become barriers to treatment.

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

  • Tell me about your personal journey – how did you end up in this?
  • You have different kinds of customers—individual clinics, healthcare plans, healthcare providers— so how do you create value?
  • Is compliance better or worse when you operate online?
  • I saw on your website you have four different kinds of customers. Out of the four, where do you make the most money?
  • Considering that you’re not the only person with this idea, what is your moat?
  • Are the physical therapists who work for you on your payroll, or are they contractors?
  • What are three things you want to do for your customers, which are healthcare/hospital systems, in the next twelve months?
  • What are three things you want to do for your customers in the next twelve months?
  • 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.

Be sure to subscribe to the Life Sciences Today Podcast on your favorite podcasting platform:

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!



< + > The Growing Gap Between Healthcare Risk and Healthcare Governance

The following is a guest article by Sam Peters, Chief Product Officer at IO

Healthcare organizations are moving quickly to adopt artificial intelligence. From clinical documentation assistants and patient communication tools to operational automation and decision support systems, AI is becoming embedded throughout healthcare workflows. The promise is significant: greater efficiency, reduced administrative burden, and improved experiences for both patients and providers.

What many organizations are discovering, however, is that the challenge is not simply adopting AI. It is governing risk in an environment where technologies, vendors, and regulatory expectations are evolving faster than many oversight processes were designed to accommodate. Healthcare organizations were already managing increasingly complex technology environments, growing third-party dependencies, persistent cybersecurity threats, workforce shortages, and expanding compliance obligations. AI is arriving on top of those existing realities, adding another layer of complexity and forcing leaders to examine whether their governance practices are capable of keeping pace with a rapidly changing risk landscape.

Governance Was Already Under Pressure

Much of the conversation around AI assumes healthcare is confronting an entirely new category of risk. In practice, many organizations are encountering familiar governance challenges that have simply become more visible as AI adoption accelerates. Fragmented oversight, limited resources, growing supplier dependencies, and difficulty maintaining visibility across complex technology environments have all been longstanding concerns for healthcare leaders.

Recent research from IO’s State of Information Security report reflects this reality. While 47% of healthcare organizations identified AI-driven phishing as a significant threat and 51% cited AI-generated misinformation and disinformation as a growing concern, the underlying pressures were already present. More than half (51%) reported budget constraints affecting security initiatives, 47% identified information security skills shortages, and 55% experienced a third-party or supply chain incident during the past year.

AI is changing the speed and scale at which these risks can materialize. Threat actors can automate activities that previously required significant time and expertise, while healthcare organizations are simultaneously under pressure to evaluate and deploy AI-enabled technologies faster than many governance processes were designed to support. The result is an environment where risks evolve more quickly than traditional oversight models can track.

The challenge extends to the defensive side as well. While AI has the potential to help healthcare organizations improve threat detection, prioritize alerts, and streamline security operations, it cannot compensate for fragmented governance or inconsistent risk management practices.

Annual Assessments Cannot Keep Pace

For years, healthcare organizations have relied on annual risk assessments, periodic compliance reviews, and point-in-time audits to evaluate security, privacy, and operational risks. Those practices remain important, but they were developed for environments where major technology changes occurred over months or years. Today’s healthcare technology ecosystem operates very differently.

AI-enabled platforms receive frequent updates, vendors continuously introduce new capabilities, and data flows evolve as systems become more interconnected. A healthcare organization’s risk profile can look very different at the end of the year than it did when the annual assessment was conducted. Yet many governance programs still rely heavily on periodic reviews that provide only a snapshot of risk at a particular moment in time.

This becomes even more challenging because AI-related risks rarely fit neatly within a single department. A clinical documentation assistant, patient engagement platform, or operational AI tool may simultaneously create cybersecurity, privacy, compliance, third-party risk, and patient safety considerations. Governance structures built around isolated functions often struggle to maintain visibility into risks that span multiple teams and evolve continuously.

Many healthcare leaders are finding that annual assessments remain valuable, but snapshots alone are no longer sufficient. Organizations increasingly need mechanisms for ongoing assessment, communication, and accountability that provide visibility into how risks change over time.

Governance Must Become an Operational Function

The challenge becomes even more complex in healthcare’s highly interconnected vendor ecosystem. Most organizations are not building AI systems themselves. They are acquiring capabilities from software providers, cloud platforms, medical device manufacturers, and specialized healthcare technology vendors. As those suppliers introduce new functionality and update existing products, healthcare organizations must understand how those changes affect their own risk posture.

This is why governance is increasingly becoming an operational function rather than a compliance exercise. Across cybersecurity, privacy, operational resilience, and emerging AI governance requirements, regulators and executive leadership teams are looking for evidence that organizations understand and manage risk continuously, not just during audit cycles. The expectation is shifting from demonstrating compliance at a specific point in time to demonstrating ongoing awareness, accountability, and resilience.

For healthcare leaders, the priority should be strengthening the fundamentals: governance, resilience, supplier assurance, workforce capability, and risk management. Frameworks such as ISO 27001, ISO 27701, and ISO 42001 can provide useful structure, but what matters most is establishing repeatable processes that help organizations assess, communicate, and adapt to risk as conditions change.

The organizations that realize the greatest value from AI are unlikely to be the ones deploying the most tools. They will be the organizations that can confidently understand and manage risk as their environments evolve. As AI adoption continues to accelerate, governance must evolve from a periodic compliance activity into an ongoing operational discipline—one that enables organizations to innovate while maintaining trust, accountability, and resilience.

About Sam Peters

Sam Peters is Chief Product Officer at IO and has more than 20 years of experience in cybersecurity, privacy, risk management, and governance. He previously served as Chief Information Security Officer and Data Protection Officer, leading programs focused on ISO 27001, privacy governance, and emerging AI governance frameworks.



< + > AI Plus Larger Data Sets Drive Workflows to the Cloud and to the Edge

The sudden emergence of AI models for all sorts of healthcare procedures, along with advanced hardware such as NVIDIA’s GPU processors, crea...