Thursday, April 30, 2026

< + > Leading Hospital at Home Programs

In February, Congress extended the Acute Hospital Care at Home program through the end of 2030. The program provides waivers to hospitals to provide inpatient-level care at home to qualified Medicare beneficiaries. The five-year extension will help participating hospitals – in place at more than 400 organizations – demonstrate the value of hospital at home and, according to the American Hospital Association (AHA), provide evidence to other payers that the program can work.

Many hospital at home programs predate the program approved by Congress, which the Centers for Medicare & Medicaid Services (CMS) first launched during the COVID-19 pandemic. Here’s a look at some of these key programs and what makes them successful.

Johns Hopkins Medicine has been operating its hospital at home program since 1994. Positive outcomes were first reported in 2005, including a 32% drop in care costs and a 35% drop in length of stay. Along with clinical care services, Baltimore-based Johns Hopkins now offers social services, home health aides, and help with day-to-day household management. Not surprisingly, the health system’s success has served as a model for Hospital at Home programs around the country.

Advocate Health launched its North Carolina-based program in just 10 days during the pandemic, AHA said, and has achieved a 15% reduction in readmission rate coupled with higher patient satisfaction scores. Patients can transition from a hospital or skilled nursing facility (SNF) to home-based care, and the program covers short- and long-term care.

Atrium Health serves about 90 patients per day in its North Carolina-based hospital at home program, which was also the model for what the health system said is the first-of-its kind pediatric hospital at home. The program also offers transitions to advanced care or palliative care at home.

The Cleveland Clinic Florida program, launched in 2023, has seen some of the highest patient satisfaction scores across all inpatient wards at the health system. It helps that the health system contracts with community-based providers. The health system’s Clinically Integrated Virtual Care (CIViC) Center covers remote monitoring and virtual care.

Kaiser Permanente has reported smoother care transitions and better patient experiences for its program based in Northern California, which provides care for more than 1,000 patients annually. It’s part of a larger care at home strategy for the health system, which in 2021 partnered with Mayo Clinic and Medically Home to found the Advanced Care at Home Coalition.

Los Angeles General Medical Center emphasizes virtual, concierge-level care, though rideshares can be dispatched if patients need to be evaluated at the hospital. The public safety net hospital’s program has reduced inpatient stays by 4 days and saves the system about $5.6 million annually, and leaders say it’s a model for providing “financially responsible” care.

Wisconsin’sMarshfield Clinic Health System is another early adopter (2016), according to the American Medical Association. The Home Recovery Care program covers 30-day medical care or 60-day rehabilitation care. The health system has reported a 44% reduction in readmission rate, a 35% decrease in average length of stay, patient satisfaction of more than 90%, and increased physician satisfaction.

At Mass General Brigham, the readmission rate for the hospital at home program is less than one-third the rate for inpatient care, AHA said. Aling with typical clinical and ancillary services, the hospital offers medically tailored meals and supports in-hone X-rays. The program has also been adapted to provide hospital-level care for veterans experiencing homelessness.

Mayo Clinic Arizona has reported a 35% decrease in readmission rate for hospital at home patients. The program also demonstrates equivalent rates of patient safety and higher rates of patient comfort. Patients receive a technology kit that, in addition to medical devices, can include a direct-dial phone, Wi-Fi extender, and backup power supply.

Mount Sinai Health System launched its program in 2014 thanks to a CMS grant, according to AHA; it built on an existing program providing home-based primary care to homebound New Yorkers. Only 7% of participating patients need to return to the hospital. The program also includes at-home palliative care, dialysis, and infusion.

The Ohio State University Wexner Medical Center has focused on disadvantaged neighborhoods. AHA reported readmission rates are roughly half as high as inpatient care, and 95% of patients rate the experience as 9 or 10 out of 10. Available services include an in-home safety assessment to help reduce the risk of falls.

Oschner Health prevented hospitalization and readmission for 92% of eligible emergency department patients in its initial pilot program, which it subsequently expanded in 2024. Along with covering chronic conditions, the program is available for Louisiana-based patients recovering from a transplant or those with a cancer diagnosis.

Presbyterian Healthcare Services launched its hospital at home program in 2008 in partnership with Johns Hopkins Medicine. Most patients receive two care visits per day for several days before discharge. The cost of care is 42% lower than inpatient hospitalization, AHA reported. The New Mexico-based health system also tripled at-home admissions capacity during the pandemic.

Are there other home health programs that you know about?  Let us know on social media.

#hospital



< + > Koda Health and UPMC Enterprises Collaborate | Click Therapeutics and Boehringer Ingelheim Announce Series D

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.


Koda Health and UPMC Enterprises Collaborate to Prove Out the Value of Advance Care Planning (ACP) at Scale

Backed by Strategic Investment from UPMC Enterprises, Koda Health Scales AI-Enhanced Advance Care Planning Across Complex Populations

Koda Health, an AI-enhanced Advance Care Planning (ACP) platform, today announced a strategic investment from UPMC Enterprises as part of the company’s Series A raise.

The investment reflects UPMC Enterprises’ conviction that digitally guided, values-based advance care planning represents a critical and underbuilt layer of serious illness infrastructure.

Koda’s platform guides patients through condition-specific care planning conversations via video and guided education, helping them document their values, care wishes, medical decision-makers, and treatment preferences. High acuity patients are paired with a dedicated Koda Member Advocate — a clinician with a background in palliative nursing or social work — who provides longitudinal support throughout the care planning process. These advocates ensure advance care plans are complete, surrogates are aligned, and that members receive the care that matters most to them during serious illness. Patient preferences flow directly into clinical workflows, ensuring care teams have access to patient goals at the moments that matter most.

An estimated $200 billion is spent each year on care that patients would not have wanted had they been engaged in their care planning earlier. ACP is proven to close that gap, but has historically been difficult to deliver at scale. Koda Health has demonstrated a 79% reduction in terminal hospitalizations, a 38% reduction in ICU utilization, and a 19% reduction in total cost of care for patients in the last year of life in a third-party validated study.

“UPMC Enterprises’ investment is a meaningful signal, not just to Koda, but to the broader market. It validates that health systems are ready to invest in infrastructure that makes advance care planning work the way it should: proactively, at scale, and with the human support that these conversations require. Having UPMC Enterprises as a strategic investor puts us in a unique position to prove what’s possible,” said Dr. Desh Mohan, Co-Founder and Chief Medical Officer at Koda Health.

“UPMC Enterprises invests in companies building infrastructure that improves how care is delivered for patients who need it most,” said Kathryn Heffernan, Senior Director at UPMC Enterprises…

Full release here, originally announced April 28th, 2026.


Click Therapeutics and Boehringer Ingelheim Announce Series D Investment and Funding to Advance Commercialization of CT-155

Boehringer Ingelheim and Click Therapeutics today announced a strategic agreement to support the commercialization of CT-155, an investigational prescription digital therapeutic that is being studied for the treatment of the experiential negative symptoms of schizophrenia in adults aged 18 years and older. Under the agreement, Boehringer will transfer full product responsibility, including all commercial and marketing authorization rights, to Click Therapeutics. To support this transition, Boehringer has made a $50M Series D strategic investment and provided dedicated commercial funding to help bring CT-155 to patients, if cleared by the FDA. CT-155 was co-developed by Boehringer and Click.

“Boehringer Ingelheim’s selection of Click to deliver CT-155 to patients is powerful validation of our vision and the capabilities we have spent over a decade building,” said David Benshoof Klein, CEO and founder of Click Therapeutics. “We are eager to take the lead with CT-155 and are focused on getting this FDA-designated Breakthrough Device to patients after clearance by the FDA.”

At the core of Click’s commercialization strategy will be the clinical data from the Phase III CONVOKE study (CONVOKE; NCT05838625). The randomized, double-blind, controlled study investigated the effectiveness and safety of CT-155 versus a digital control app as an adjunct to standard of care antipsychotic therapy in people diagnosed and living with schizophrenia experiencing negative symptoms.

The study met its primary endpoint, as presented at the 38th Annual European College of Neuropsychopharmacology (ECNP) Congress, which was change in experiential negative symptoms from baseline to 16 weeks as measured by the Clinical Assessment Interview for Negative Symptoms, Motivation and Pleasure Scale (CAINS-MAP). Treatment with CT-155 demonstrated a Cohen’s D effect size of -0.36 (p value= 0.0003) reflective of a 6.8-point improvement of negative symptoms severity as measured by CAINS-MAP at 16 weeks (vs. 4.2-point in digital control arm), representing a 62% relative improvement.

CT-155 was well-tolerated and demonstrated an adverse event (AE) profile consistent with past studies. The AE rates with CT-155 and the digital control arm were 8.3% vs 13.4%, respectively. There were no trial discontinuations attributed to CT-155 and two (2) for the digital control arm. There were no serious AEs related to either group…

Full release here, originally announced April 9th, 2026.

#koda

Wednesday, April 29, 2026

< + > Measuring Clinical, Operational, and Financial ROI of AI Initiatives

We’ve broken AI down into many pieces to analyze the many different aspects of AI and how it affects the different areas of healthcare organizations. One area we haven’t talked about enough yet is the return on investment of AI initiatives once they’ve been deployed in the real world. Today, we set out to fix this wrong and learn more not only about the financial ROI of AI initiatives but also the clinical and operational ROI.

We’ve reached out to our brilliant Healthcare IT Today Community to ask — how do you measure the clinical, operational, and financial return on investment of AI initiatives once they are deployed in real-world settings? The following are their answers.

Elevsis Delgadillo, SVP, Customer Success at KeenStack
There’s no need to reinvent reporting to measure AI ROI. Most organizations are already tracking the right metrics. In referral management, that might be leakage or time to schedule, and in clinical use cases, it could be outcomes like hospital-acquired sepsis rates. In the revenue cycle, it’s collections and denials. The key is enabling an AI workflow in a specific area and measuring what changes so the impact can be clearly attributed.

Shay Perera, Co-Founder & CTO at Navina
Meaningful ROI in healthcare AI must be assessed through a combination of clinical, operational, and financial metrics. Clinically, we measure factors like improved risk adjustment accuracy and care gap closure rates; operationally, reductions in chart review, documentation, and coding time, and administrative burden, alongside high clinician engagement with the solution; financially, enhanced documentation quality contributes to audit readiness and more predictable revenue under value-based contracts.

Jared Hamilton, Cyber Managing Director at Crowe LLP
Physician feedback is one of the most important measures of return on investment. In clinical settings, we look closely at whether AI tools are meaningfully reducing time spent on documentation and administrative tasks, such as manual charting, and allowing providers to spend more time interacting directly with patients.

That impact shows up not only in efficiency metrics, but also in the patient experience. Most of us have been patients ourselves, and we understand the difference between a provider who is fully engaged in the conversation versus one focused on a keyboard. When AI helps shift attention back to the patient, it delivers both clinical and experiential value, which ultimately supports provider satisfaction and long-term operational and financial returns.

Denis Whelan, CEO at Documo
ROI for AI initiatives is measured using the operational and financial metrics organizations already track. This includes reduced manual processing time, faster referrals and authorizations, fewer document errors, and lower cost per transaction. On the clinical side, teams focus on metrics like improved turnaround times, fewer delays in patient care, and improvements in population health metrics.

For example, one healthcare organization using AI to process inbound documents was able to cut handling time by 40-50% while redeploying staff to higher-value tasks – achieving measurable efficiency gains without adding headcount.

Joe Russolello PT, DPT, MBA, Senior Vice President, Growth at WebPT
ROI only becomes real when it shows up in the clinician’s experience first. Clinically, that means less burnout and higher satisfaction driven by reduced documentation burden.

Operationally, the most consistent metric is time. Often, one to two hours per clinician per week is reclaimed and significantly less after-hours charting. Financial gains follow when those efficiencies reduce denials, accelerate billing cycles, and shrink AR days, with many organizations reaching sustained ROI within the first year.

If AI doesn’t make clinicians’ lives meaningfully easier, the financial returns rarely last.

Deepak Prakash, Co-Founder & CTO at Sonio
Comparing key benchmarks of time, cost, and performance of initiatives prior to AI integration in a health system can show the stark differences in operational efficiencies due to its use, such as lessening clinician documentation burden, greater reimbursement rates, and faster diagnostic results. Yielding earlier-stage diagnostics from AI-powered software allows patients to make more informed decisions, and can be measured in defining the decreased time spent per appointment, higher patient engagement rates, and more personalized care journeys.

Lisa Israelovitch, Co-Founder & Chief Executive Officer at AssistIQ
Real-world settings such as hospitals and other care facilities often drive clear return on investment from integrating AI platforms in their networks, seen through tangible outcomes in areas such as reduced cost per case, lower inventory waste, and time saved per procedure. Setting recurrent assessments around operational efficiencies in the early stages of new AI initiatives creates a useful lens to compare strategy effectiveness with previous benchmarks.

Mohan Giridharadas, CEO at LeanTaaS
In the real world, the ROI of AI centers on whether it changes outcomes in a measurable, sustained way. We measure operational ROI by tracking flow and capacity metrics that reflect day-to-day performance: discharge processing time, ED boarding, transfer declines, length of stay, OR utilization, block utilization, and surgical throughput.

Clinical ROI is often indirect but real: when the system runs with less gridlock, patients get to the right care faster, and clinicians spend less time doing manual workarounds.

Financial ROI comes from unlocked capacity and avoided cost: more admissions and surgeries without building new beds or ORs. Specifically in the perioperative space, Rush University Medical Center increased primetime OR utilization by 4% and improved surgeon block utilization by 12%, enabling 1,705 additional surgeries over three years and delivering a 12x ROI in one recent year.

Patrick Sheehan, Vice President of Value-Based Care at Withings Health Solutions
Real-world ROI from AI in healthcare is realized when it improves both how care is delivered and the outcomes it produces. While operational AI is already delivering measurable efficiency gains, the next frontier of real ROI will come from clinical use cases that directly enable earlier, more confident intervention. Clinical AI is advancing rapidly, enabling earlier identification of patient deterioration and giving care teams the confidence to intervene proactively rather than react to symptoms.

This is especially impactful in heart failure, where disease progression patterns vary widely, and early signs of deterioration are difficult to detect, contributing to avoidable hospitalizations. By improving operational efficiency and enabling earlier intervention, AI helps health systems deliver high-quality, scalable care to complex populations and perform better under value-based care models that reward quality and affordability.

Ben Moore, Chief Innovation Officer at PerfectServe
Now that healthcare is deep into the AI hype cycle, the focus needs to shift from experimentation to solving specific, measurable problems based on the wealth of knowledge we’ve already compiled. When the use case is narrowly tailored, the expected results should be easier to anticipate and track. For example, we’ve done some research that suggests the average clinician may spend 30–40% of their time during a shift just trying to communicate with their colleagues to coordinate patient care. That kind of built-in friction is a perfect target for AI. Train an AI agent with all of the rules from our routing engine and deploy it to stem the number of errant or unnecessary communications that flow throughout a hospital. Deploy another agent to execute emergency shift swaps when a provider has a sudden family emergency and can’t cover a shift.

These applications remove toil and stress from important clinical workflows and give time and peace of mind back to clinicians. And because so many hospital processes are touched by communication and coordination, the opportunities for measurement are extensive. Measurement opportunities span call center efficiency metrics—more efficient patient transfers, higher volumes of urgent calls handled, pre/post analyses of calls misdirected to off-call providers, and engagement surveys tracking provider satisfaction with scheduling flexibility and autonomy. As these AI applications mature, the results will shift from promising to proven.

Greg Farnum, SVP GM, Federal and Strategic Advisory at Audacious Inquiry
Just as early time-and-motion studies made the invisible work of information exchange visible and quantifiable, customer-specific language models have the potential to illuminate ROI in ways generic LLMs cannot. While general AI tools can demonstrate time savings, curated SLMs that truly understand organizational workflows, terminology, and decision frameworks unlock a different level of measurement.

The ROI opportunity with customer-specific models lies in their ability to capture organizational friction that’s currently invisible: the cognitive load of context-switching, the emotional burden of repetitive administrative tasks, and the time lost to information retrieval. Like HIE before it, we need proxy measures first—time saved, burden reduced, experience improved—before we can connect these to hard financial metrics.

Ben Scharfe, EVP for AI at Altera Digital Health
Measuring ROI currently relies heavily on leading indicators that signal long-term financial health. While many measurements are currently soft, we focus on physician and patient satisfaction as primary markers. High satisfaction scores are direct predictors of reduced physician turnover and increased patient retention and referenceability, both of which have material financial impacts. Operationally, we still track chart closure times and clean claim rates. When ambient AI reduces the administrative burden, the return is found in the stability of the workforce and the improved integrity of the patient encounter.

So many great experiences here! Huge thank you to everyone who took the time out of their day to submit a quote to us! And thank you to all of you for taking the time out of your day to read this article! We could not do this without all of your support.

How do you measure the clinical, operational, and financial return on investment of AI initiatives once they are deployed in real-world settings? Let us know over on social media, we’d love to hear from all of you!


#clinical     #measure

< + > The Expanding AI Ecosystem: How PHI Can Quietly Leave the Healthcare Environment

The following is a guest article by Dennis P. Sweeney, MBA, Co-Founder of Vertebrai Solutions Inc., and Consulting Principal at Tellogic Inc.

Healthcare organizations are rapidly adopting artificial intelligence (AI) solutions to support clinical, administrative, and operational workflows. To manage privacy risk and control Protected Health Information (PHI), most healthcare organization deployments follow a familiar pattern. AI systems are hosted inside private, HIPAA-compliant cloud environments under Business Associate Agreements (BAAs) with the major cloud providers.

Hosting in a private HIPAA-compliant cloud environment provides infrastructure safeguards. These architectures, used by legacy healthcare systems with internal interfaces and custom-developed external APIs, manage PHI data exposure concerns. Platforms such as Microsoft Azure and Amazon Web Services provide strong security controls, encryption, audit logging, and established compliance frameworks. With a BAA in place, healthcare leaders can be reasonably confident that protected health information (PHI) stored and processed within those environments is being handled appropriately.

Many organizations deploying large language models (LLMs) believe they have addressed critical privacy concerns. The AI is operating inside a controlled HIPAA environment. Security controls are in place. Compliance requirements are satisfied.

The information technology architecture hosting the system feels safe.

The Valuable AI Work Inside Controlled Environments

AI systems in these healthcare environments are performing valuable work. They summarize patient charts, generate clinical documentation, assist with prior authorization workflows, triage patient messages, support population health analysis, link to research guidelines, and automate administrative tasks that consume large portions of the clinician’s workday. The realization that every system capable of reading the medical record eventually encounters the same reality, Electronic Health Record (EHR) systems are filled with protected health information.

PHI is more than structured data elements. It is a detailed narrative of an individual’s medical history, including diagnoses, medications, laboratory results, imaging findings, clinical notes, and social or behavioral context. Protecting PHI is not only a regulatory obligation under HIPAA, it is also essential to maintaining patient trust and preventing harms such as stigma, discrimination, identity theft, or financial loss resulting from unauthorized disclosure.

The Shifting Question: What Happens After the AI Accesses PHI?

For many healthcare leaders, the central question has historically been whether AI can safely operate within HIPAA-compliant environments. This can be compared to verifying if barn can safely house the farm animals, where the only exit for the farm animals is through the observed front barn door.

A different question is emerging as agentic AI expands in these LLM systems. What happens to patient data after the AI accesses it?

The Rapid Rise of Agentic AI in Healthcare

At the recent HIMSS 2026 conference, numerous vendors prominently promoted their agentic AI solutions, showcasing autonomous agents capable of handling everything from clinical documentation and revenue cycle tasks to patient communications and multi-step care coordination.

LLMs are increasingly being deployed within agentic architectures, where the LLM not only generates responses but also performs actions across multiple systems. Integration frameworks such as the Model Context Protocol (MCP) demonstrate the ease of connecting systems using this new architecture. MCP standardizes secure, structured communication between AI agents and external tools, resources, and data sources, enabling LLMs to discover capabilities, retrieve context, and execute workflows with greater reliability and control. A single AI assistant can retrieve clinical context from the EHR, assemble documentation, query scheduling systems, submit payer requests, and coordinate actions across multiple applications. 

An LLM might call external systems such as pharmacy benefit manager (PBM) databases for real-time formulary and drug-interaction checks, laboratory information systems (LIS) for results verification, revenue cycle management (RCM) platforms for claims processing, telehealth integration services, wearable data aggregators, or third-party population health analytics tools.

Each integration makes the system more useful. This might be compared to the barn housing farm animals; the building is rapidly being renovated to allow more light with new windows and doors, but at the same time, allowing new exits through which the animals might escape. Each agentic AI integration creates new pathways through which patient data can flow. 

Hidden Privacy Risks in Interconnected Ecosystems

A BAA governs how a cloud provider stores and processes PHI within its services. It does not automatically govern how information flows when an AI system communicates with external APIs, third-party software tools, or other connected platforms.

LLM increasingly functions as a bridge between systems by retrieving information from one environment, processing it, and then transmitting relevant context to another system to complete a workflow.

This LLM behavior is exactly what is intended and provides the expected benefit. 

Consider a use case such as prior authorization. The LLM accesses the patient data, including codes, history, and details that make up the patient’s life. It might pull in a quick formulary check from the Pharmacy Benefits Manager (PBM) or verify a lab result and transmit this data to the payer’s Interface. Overall, saving time and speeding up care, but behind the scenes, suspense builds in the quiet; the request can spill more context than planned. External logs gobble fragments of the record. Data is retained outside the controlled HIPAA environment. No malice. Just the task completed. Yet the patient data crossed the line. Slipped away into the unknown.

Figure 1: The Expanding Agentic AI Ecosystem

Agentic AI systems are particularly effective at multi-step workflows that retrieve information, reason about it, and pass structured data between systems, without the user’s intervention. The LLM/AI engine becomes an intelligent conduit through which patient information flows.

Mitigating Risks: The Technical Savior Using PHI Redaction

Mitigating this risk requires architectural safeguards as well as governance oversight.

The most reliable HIPAA Safe Harbor solution is technical PHI redaction. A de-identification layer prevents the LLM from ever receiving the protected data and transmitting it outside the private environment. It replaces the 18 HIPAA identifiers, including names, addresses, phone numbers, and medical record numbers, with pseudonymous tokens. It does this while preserving the clinical facts the LLM needs, including data on labs, vitals, allergies, encounters, diagnoses, clinical notes, and medications. Dates are shifted to maintain sequences without exposing exact values. A secure mapping in the application layer temporarily holds the link back to the original identifiers.

Clinicians act on the provided information, and tokens resolve back. Session ends, mapping gone. No persistent exposure. These safeguards reduce the risk dramatically. The AI flows data safely now. The expanding AI ecosystem? It is now tamed. Patient trust preserved.

Looking Ahead: Balancing Innovation and Protection

The productivity benefit of these systems is real, and their adoption will accelerate in the coming years, if not months. Healthcare leaders need to recognize that AI systems connected to multiple platforms behave differently than traditional software operating within a single controlled private environment.

Once an AI system learns how to navigate the patient chart, it eventually learns how to navigate everything connected to it.

In modern healthcare IT environments, that network of connections and data flows will end up extending farther than most organizations expect.

About Dennis P. Sweeney

Mr. Sweeney is the Co-Founder of Vertebrai Solutions Inc., which released the Vertebrai AI Clinical Assistant at HIMSS26. He is also a Consulting Principal with Tellogic Inc., as a trusted advisor, supporting healthcare organizations for over 30 years, leading the IT & Data/Information strategies, establishing Clinical Integration & Accountable Care Organization programs, leading cross-functional teams, providing program management, technical assessments, business transformation, organizational redesign, software product development, change management, and system implementations.


#ai  #healthcare



< + > This Week’s Health IT Jobs – April 29, 2026

It can be very overwhelming scrolling through job board after job board in search of a position that fits your wants and needs. Let us take that stress away by finding a mix of great health IT jobs for you! We hope you enjoy this look at some of the health IT jobs we saw healthcare organizations trying to fill this week.

Here’s a quick look at some of the health IT jobs we found:

If none of these jobs fit your needs, be sure to check out our previous health IT job listings.

Do you have an open health IT position that you are looking to fill? Contact us here with a link to the open position and we’ll be happy to feature it in next week’s article at no charge!

*Note: These jobs are listed by Healthcare IT Today as a free service to the community. Healthcare IT Today does not endorse or vouch for the company or the job posting. We encourage anyone applying to these jobs to do their own due diligence.



Tuesday, April 28, 2026

< + > MediQuant Reduces Cyber Exposure, Tech Footprint, and Costs with Application Rationalization

Over the decades, IT systems proliferate at health care systems, particularly when individual departments install solutions optimized for their particular use case. Jim Jacobs, CEO at MediQuant, points out that users tend to rely on existing systems and resist having them taken away. But consolidation can help customers meet their defined priorities: reducing cyber exposure, tech footprint, and costs.  A structured application rationalization approach and tool can provide the data needed to make those decisions.

Serving clients since 1999, MediQuant supports what Jacobs calls “responsible AI.” He worries that many organizations move too fast and risk costly mistakes. MediQuant has adopted AI across four pillars: to provide clinical insights and improvements in revenue cycle, to drive improvements in complex implementations, and in identifying more uses for patient data.

MediQuant is also innovating around DICOM, consolidating imaging data from all modalities into a centralized, DICOM-based archive, enabling seamless access to historical studies while reducing costs and eliminating the complexity of fragmented legacy systems.

Check out our interview with MediQuant to learn more about the benefits of application rationalization and the unique ways they’re helping hospitals and health systems get value from their health data archive.

Learn more about MediQuant: https://www.mediquant.com/

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

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

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

MediQuant is a proud sponsor of Healthcare Scene.

#mediquant

< + > The Digital Front Door is Locked for Millions of Patients; Health IT Leaders Hold the Key

The following is a guest article by Mike Barton, VP, Communications at AudioEye

Patient Portal Adoption has Surged, but Accessibility Failures are Locking out the Patients who Need Digital Access the Most

The digital transformation of healthcare has made it easier than ever for patients to manage their own care. For the one in four Americans living with a disability, that promise often falls apart at the first click.

A patient checks her lab results at 10 p.m. She logs into her health system’s patient portal, pulls up the results page, and sees what her doctor ordered. Five minutes, start to finish.

Same portal, different patient. This one is blind. The login form has no labels, so her screen reader can’t tell which field is for her username and which is for her password. She guesses. Gets it wrong. The error message that pops up? Invisible to her assistive technology. She never gets past the front door.

That second scenario is not uncommon. According to the ONC’s 2024 Health Information National Trends Survey, over 75% of individuals now have online access to their medical records. But for the one in four American adults living with a disability, the digital front door to healthcare might as well be bolted shut. These aren’t people opting out of digital health. They’re being shut out by the very tools meant to bring them in.

Where Patient-Facing Digital Tools Break Down

The failures in patient portals aren’t random. AudioEye’s 2025 Digital Accessibility Index analyzed more than 420,000 web pages across 15,000 websites and found that the average healthcare page had 272 accessibility issues. They cluster in the exact workflows patients use most.

  • Keyboard Navigation Failures: Patients with motor disabilities often can’t use a mouse, so they navigate entirely by keyboard; healthcare sites averaged 6.1 keyboard-related violations per page – that’s enough to make logging in or filling out a form a dead end
  • Low Contrast Text: If the color contrast between text and background is too low, people with low vision can’t read it; healthcare pages averaged 69.1 contrast violations per page; lab results, medication instructions, appointment details: all potentially unreadable
  • Broken Links and Forms: Screen readers need properly labeled links and form fields to guide someone through a page; without them, it’s guesswork; healthcare sites averaged 5.4 inaccessible links and 4.0 broken form elements per page

All of this is happening on live patient portals, at organizations that would absolutely describe themselves as patient-centered.

The Regulatory Pressure is Real and Immediate

The updated Section 504 rule from HHS, finalized in May 2024, requires organizations receiving federal financial assistance to meet WCAG 2.1 Level AA across their digital properties (45 CFR Part 84).

59% of business leaders said their organizations would face legal risk if audited today, according to AudioEye’s 2026 Accessibility Advantage Report. Yet only 47% describe their accessibility programs as proactive. The rest are operating reactively or meeting bare minimums. If you’re in health IT, that gap should worry you.

A Practical Fix Roadmap for Stretched Teams

Most patient portal accessibility failures are configuration and content issues. Fixable, if you prioritize the highest-impact areas.

Start with the critical path. Map the five to ten workflows patients use most. Audit those specifically against WCAG 2.1 AA using both automated scanning and manual testing with assistive technology. Automated tools catch roughly two-thirds of issues. The rest — screen reader behavior, keyboard flow logic, cognitive accessibility — requires human evaluation.

Fix login and authentication first. A patient who can’t get past the front door can’t use anything else. Then test and fix form labels, link descriptions, and alt text on high-traffic pages.

Someone has to own it. Nearly half of organizations manage accessibility entirely in-house, but 64% of those teams admit they lack the specialized skills. If nobody owns accessibility as an ongoing practice, it won’t survive the next site update.

Build testing into every release cycle. Every portal update, new feature, and vendor patch can introduce new barriers. The organizations that stay compliant test at every release, not once a year before an audit.

The Real Impact is Patients, Not Compliance

Yes, the Section 504 deadline matters. But fines aren’t the real cost here.

If the disability rate in your community mirrors the national average, approximately 25% of your patients have a disability. Even if only a fraction of those people can’t complete basic portal tasks, you’re talking thousands of patients a year who are functionally locked out. They give up on the portal. Call the front desk instead. Skip the follow-up because the phone line was busy. And slowly drift away from their own care.

#digital

< + > Bioxtreme Announces Strategic Investment Led by Serra Holding | Amperos Health Secures $16M Investment

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.


Bioxtreme Announces Strategic Investment Led by Serra Holding and Introduces Plaxtreme to Accelerate Neurorehabilitation Innovation

Leadership Expansion Across the U.S. and Europe Supports Global Growth of Next-Generation Neurorehabilitation Robotics

Bioxtreme, an innovator in neurorehabilitation technologies leveraging its proprietary error augmentation approach to accelerate motor recovery, today announced a new strategic investment led by Serra Holding, a family office focused on hands-on investment and operational support across the healthcare sector, including hospitals, mental health institutions, and medtech companies. This investment brings the company’s total funding to $15 million to date, accelerating Bioxtreme’s global expansion, strengthening operations in the United States and Europe, and supporting the launch of Plaxtreme, the company’s advanced robotic rehabilitation device engineered to drive neuroplasticity and accelerate motor skill recovery in individuals with neurological conditions.

Plaxtreme is designed to address the restoration of functional hand movement. Combining precision robotics, immersive virtual environments, and Bioxtreme’s proprietary error augmentation technology, Plaxtreme restores grasp and release while accelerating recovery and improving functional outcomes for users. Key capabilities include:

  • Patented Error Augmentation Technology – Amplifies movement errors to trigger the brain’s natural adaptive responses, accelerating motor learning and improving movement accuracy
  • Personalized Adaptive, AI-Based Learning– AI analyzes movement performance in real time, adjusting subtle force demands and therapy parameters; continuously adapts to support progressive learning
  • Supination and Pronation Training- Supports natural forearm rotation for functional movement, improves coordination for daily tasks; functional, ADL-based activities in an interactive, 3D environment; gamified tasks drive engagement and high repetition practice
  • Adaptive Feedback Driven Rehabilitation – Real-time, visual feedback supports continuous progress; automatically adapts difficulty to the patient’s ability
  • Designed for Smooth, OT Workflows – Quick setup with no complex calibration, and seamless left/right and transition; convenient hand positioning for efficient clinical use

Bioxtreme’s portfolio also includes Dextreme, an advanced robotic rehabilitation system for upper-limb recovery that also applies adaptive error augmentation forces to accelerate motor learning and restore functional independence…

Full release here, originally announced April 21st, 2026.


Amperos Health Secures $16M Investment as it Launches Industry’s First AI-Native Denial Management and Revenue Recovery Platform

Helping Providers Resolve Denials Five Times Faster and Cut Denial Rates by 70%

Amperos Health, the first insurance revenue recovery partner capable of working denials end-to-end entirely with AI, announced today that it has closed a $16 million Series A funding round, led by Bessemer Venture Partners, with participation from Uncork Capital and Neo.

The raise comes as Amperos launches the industry’s first AI-native denial management and revenue recovery solution for healthcare providers. Amperos’ agentic capabilities provide end-to-end denial and collection automation, while a team of subject matter experts provides judgment and expertise for complex and difficult-to-recover claims. Amperos then delivers detailed insights into how providers can optimize their billing and collections processes to prevent future denials. To date, Amperos has served over 3,000 clinical locations across all 50 states, driving nearly $700 million of revenue recovered per year across over 500,000 claims.

“Complexity in healthcare revenue cycle management (RCM) should not be the norm, and that’s why our mission at Amperos is to streamline the denial and collections process so providers can focus on what matters most – operating their practices and serving their patients,” said Michal Miernowski, Co-Founder and CEO at Amperos Health. “I’m thrilled to announce our most recent funding round, which will be critical as Amperos accelerates its growth to serve more providers, expands its analytics capabilities, and launches new agentic capabilities in other RCM workflows.”

Denials are rising in healthcare today, with 12% of claims denied in 2024, representing a $262 billion loss in revenue to providers. Providers then spend more than $26 billion annually in recovering these denied claims, of which 70% end up getting paid. And yet, 63% of RCM teams are understaffed, while healthcare administration teams face a 32% annual turnover rate.

These statistics exemplify why Amperos has built a new product that can fill gaps in the RCM workforce while recovering more value in denied revenue. The product manages the full denial management process, from following up through insurance portals and calls to submitting corrected claims, medical records, and appeals.

“Denials are one of healthcare’s fastest-growing pain points: a growing portion of claims denied, hundreds of billions in lost revenue, and RCM teams that are chronically understaffed. It’s a broken process ripe for AI transformation,” said Sofia Guerra, Partner at Bessemer Venture Partners…

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



Monday, April 27, 2026

< + > Health IT Mount Rushmore – Part 1 – Healthcare IT Today Podcast Episode 191

For the 191st episode of the Healthcare IT Today Podcast, we are building our own Mount Rushmore for Health IT! We have so much to discuss that this topic will actually be split up into two episodes. So for part 1, we first talk about who we think should be on the Mount Rushmore of Health IT Technologies. Then we discuss all of the Health IT People we would put on our Mount Rushmores.  Who would you add to our list and who would you remove from our lists?

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

  • Who should be on the Mount Rushmore of Health IT Technologies?
  • Who should be on the Mount Rushmore of Health IT People?

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

We publish a new Healthcare IT Today podcast every ~2 weeks. Thanks to our friends at Healthcare Now Radio, you’ll be able to listen to the latest episodes of Healthcare IT Today on their radio station for the first two weeks. Then, we’ll be publishing each episode as a podcast and YouTube video here after it finishes on the radio.

You can also subscribe to the Healthcare IT Today podcast on any of the following platforms:

Thanks for listening to Healthcare IT Today and if you enjoy the content we’re sharing, please rate the 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 HealthcareITToday.com.

If you work in Healthcare IT, we’d love to hear where you agree and/or disagree with the perspectives we shared. Feel free to share your thoughts and perspectives in the comments of this post, in the YouTube comments, with @Colin_Hung or @techguy on Twitter, 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!

Listen to Our Latest Episodes:



< + > We’re Asking the Wrong Question About Data Privacy in Healthcare

The following is a guest article by John Roach, President at Resultant

Common Misconceptions about Data Regulations are Stifling Healthcare Innovation

At a packed panel discussion at CES on health data privacy earlier this year, I made a confession on stage that made several attorneys in the audience visibly uncomfortable: I think healthcare’s legal departments are often the biggest barrier to innovation, and to better patient outcomes.

Let me explain why I believe this, and why it matters far beyond healthcare.

The Compliance Trap

First, I must acknowledge the complexity. Healthcare organizations face HIPAA, HITECH, state privacy laws, FDA regulations, FTC oversight, and increasingly, sector-specific AI governance rules. It’s genuinely complicated.

But stepping back, as a consumer and as a citizen, I think expectations are straightforward. If an organization is going to collect our data, we expect them to comply with privacy regulations. Full stop. And increasingly, people assume that compliance is not optional or impressive. It’s simply the baseline.

At the same time, there is a growing expectation that if organizations and governments are collecting this data, they have a responsibility to use it to improve services and outcomes. 

This is where things break down.

The General Counsel Problem

I’ve worked closely with a lot of general counsels. And if you ask many of them what their job is, they’ll joke that it’s to keep someone out of jail. The safest way to do that is often to say no.

And while that instinct is understandable, I do not think it is the right default mindset.

Here’s what this looks like in practice: A healthcare system wants to identify patients at high risk for readmission so they can provide preventive care. The data science team can build the model. The clinical team sees the value. But the legal team kills the project. While it doesn’t violate the regulations, it might create risk, and navigating the compliance framework seems too complex.

Meanwhile, that same patient’s behavioral data is flowing freely from their smartwatch to a third-party app to a data broker, with almost no legal protection. The organization that could actually use the data to improve care is paralyzed. The organization selling the data to the highest bidder faces minimal constraints.

The contradiction is absurd.

Reframing the Question

What I’ve seen work is a push from organizational leadership to reframe the question. Not “can we do this?” but “how do we do this responsibly?” That means creating value from data within a complex legal framework, not avoiding the framework altogether.

The most effective organizations change the internal posture from “no” to “yes, but with guardrails.” Yes, we will protect privacy. Yes, we will comply with regulations. And yes, we will still find ways to responsibly use data to improve how we serve people.

Most regulatory frameworks ultimately point back to the same underlying security standards, often those put forth by the National Institute of Standards and Technology. So while it’s harder, it’s not unknowable. The bigger obstacle is organizational courage and the willingness to do the hard work of building proper governance.

Playing the Long Game

Here’s where I’m going to talk out of both sides of my mouth, because I think we have to hold two truths at once.

First, what data are we actually protecting? Historically, no one really envisioned the secondary use of the data being collected. In healthcare, especially, data existed to support transactional and clinical needs. You had to bill correctly. A physician needed to know what happened at the last visit. That was the core purpose.

What we’re realizing now is that this same data has enormous downstream potential to influence health outcomes. But these outcomes also operate on very long-term horizons. The characteristic timeframe for influence can be decades.

That means organizations have to think differently. You need to be extremely thoughtful about what data you collect and why you collect it. It should have a clear purpose and a clear rationale for being maintained.

At the same time, technology is a moving target. There may be things we can do with this data in 10 or 20 years that we cannot imagine today, and those insights may align perfectly with those long health timelines.

So the challenge is holding both truths at once: Be intentional and disciplined about data collection, while recognizing that responsible stewardship today can unlock powerful future value tomorrow.

A Technical Solution to a Trust Problem

There is an emerging approach that actually points the way forward. Historically, organizations would hand over large datasets to researchers or partners and hope their controls were sufficient. That introduces real risk, and it’s one reason legal teams default to “no.”

Instead of moving data to people, we’re increasingly bringing people to the data. Secure, virtual data environments allow researchers to analyze sensitive data where it lives, using familiar tools, without ever taking custody of the raw data.

This addresses both the legal risk and the trust gap. It enables insight while maintaining control. And it changes the calculus for organizations that have been sitting on valuable data, afraid to use it.

Organizations that get this right build trust not by limiting insight, but by designing systems that enable insight safely, transparently, and with clear accountability.

The Stakes

Every industry is facing some version of this challenge: the tension between data’s value and data’s risk. And every organization has lawyers whose job is to minimize liability.

But in healthcare, the stakes are literally life and death. When we fail to use data that could prevent disease, reduce suffering, or catch problems early, people get hurt. When we fail to combine social determinants data with clinical data because it’s “too complex,” we miss the opportunity to address health inequities at their root.

The regulatory environment isn’t going to get simpler. AI is going to make these questions more urgent, not less. And with healthcare costs rising at the fastest rate in 15 years, advanced data analytics could bend that curve. But only if we’re brave enough to use it.

About John Roach

John Roach is President at Resultant, a data and technology consultancy. John started Resultant’s data analytics practice in 2013, which laid the groundwork for capabilities that extend to nearly every client engagement today.  Resultant specializes in data solutions for healthcare organizations across sectors, including Retina Consultants of America (acquired by Cencora), Children’s Hospital Association, and the Indiana Department of Health and Human Services.

#data

< + > Cresora Commerce Launches with Over $4M in Funding | Worki Raises $2.75 Million

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.


Cresora Commerce Launches with Over $4M in Funding to Redefine AI-Driven Commerce Infrastructure

Backed by Nashville Capital Network and Private Investors, Cresora Targets Healthcare First with Expansion Across Industries

Cresora Commerce (Cresora), an AI-native commerce infrastructure platform, today announced its official launch alongside the successful close of its initial funding round totaling more than $4 million. The round includes participation from Nashville Capital Network (NCN) and a group of private investors, with the deal finalized in early 2026.

Headquartered in Nashville, Cresora enters the market at a critical inflection point as enterprise organizations face mounting complexity across payments, reconciliation, and financial workflows—while simultaneously confronting a once-in-a-generation opportunity to streamline operations through AI. Cresora is part of a new class of AI-native platforms purpose-built to dismantle entrenched silos and eliminate inefficiencies in transaction processing, delivering a level of flexibility, intelligence, and speed to market that legacy systems were never designed to support.

Cresora was founded by experienced operators with deep expertise in healthcare tech, payments, and financial infrastructure. The leadership team includes co-founders and other executives who previously built and scaled AxiaMed, a healthcare payments platform acquired by Bank of America in April 2021.

“We have years of experience inside the traditional payment ecosystem, where we saw firsthand how outdated technology, rigid business models, and inflexibility create unnecessary friction for consumers, merchants, and the vertical software companies that support them,” said Kevin Kidd, Co-Founder and Chief Executive Officer at Cresora Commerce. “With the rapid rise of AI and the shift toward an agentic economy, a fresh, nimble approach is now essential. That’s why we created Cresora — to empower business organizations and the vertical software providers they rely on with modern commerce solutions that harness AI-driven efficiencies, improve profitability, streamline workflows, and automate operations and compliance.”

While traditional payment solutions focus on transaction execution, Cresora is designed with a unified orchestration layer that sits between payers and payees—managing the full lifecycle from transaction initiation through settlement, reconciliation, and reporting…

Full release here, originally announced April 21st, 2026.


Worki Raises $2.75 Million to Build the AI Workforce Unifying Infrastructure Layer for Healthcare Workforce Operations

Backed by Redesign Health and Healthliant Ventures, Worki is Building the Connective Layer to Help Health Systems Implement AI, Reduce Administrative Burden, and Navigate Growing Workforce Anxiety

  • Funding Round Led by Redesign Health and Healthliant Ventures Validates Worki’s Approach to Modernizing Healthcare Workforce and HR Operations with its AI Platform
  • Worki Unifies Fragmented Workforce Systems into a Single Job Architecture and Data Context Layer, with Built-In Audit and Governance Powered by AI Agents Throughout the Data Standardization Process; Once Established, Worki Deploys AI Agents that Amplify Existing Workforce Roles with People in the Middle, Accelerating ERP Readiness, Post-Merger System Unification, and Reducing Administrative Burden Across Each Effort
  • The Company’s Task-Role Architecture Creates an Actionable Roadmap that Gives Health System Leaders Visibility into How Work is Performed at the Task Level, Where AI can be Introduced, and What it Means for their Workforce, Replacing Guesswork with Operational Clarity
  • Early Health System Partners Project Millions in First-Year Savings, with Additional Gains as Adoption Scales

Worki, a healthcare workforce infrastructure company, today announced it has raised $2.75 million in pre-seed funding led by Redesign Health, a healthcare venture builder, and Healthliant Ventures, Tanner Health’s venture arm, to help health systems reduce administrative overhead and navigate the shift to AI-driven operations.

Health systems are moving past AI experiments and into real implementation, but many are still figuring out where they’re headed, all while trying to modernize how they operate and reassure their teams about what this means for their jobs. Worki addresses this by providing an infrastructure layer that connects workforce systems and enables AI to be deployed across real roles and workflows, with humans remaining at the center of all tasks.

The investment from Redesign Health and Healthliant reflects growing demand for solutions that bring structure to a fragmented landscape, giving leaders visibility into how work is performed and a way to introduce AI without disrupting their workforce. Early deployments have already shown measurable impact, with health system partners reducing administrative burden and projecting meaningful cost savings as adoption scales.

Central to Worki’s approach is a task-role architecture that maps how work is performed across healthcare administrative and operational functions. This structured mapping creates an actionable contextual layer, a roadmap that identifies precisely where AI agents can augment, automate, or streamline specific tasks within existing roles. Rather than deploying AI broadly and hoping for adoption, the contextual layer provides each agent with the granular intelligence it needs to operate within the boundaries of real workflows…

Full release here, originally announced April 16th, 2026.


#cresora

Sunday, April 26, 2026

< + > Bonus Features – April 26, 2026 – 27% of healthcare orgs deploying AI across multiple functions, 56% of orgs believe operational and technology investment will stabilize finances, plus 29 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.

Reports

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.


#healthcare



Saturday, April 25, 2026

< + > Weekly Roundup – April 25, 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.

Overcoming Barriers to Scaling AI Initiatives. How is the Healthcare IT Today community accomplishing this? Strategies include addressing cultural resistance, aligning workflows, building trust, educating staff, and determining how to calculate ROI. Read more… 

Improving Health With Technology, Behavioral Science, and Human Connection. Chandra Osborn at AdhereHealth talked to Colin Hung about using highly personalized engagement and motivational interviewing to address root causes of problems such as poor medication adherence. Read more…

When Metal Meets Digital: The Best Surprises from SAGES 2026. While attending the annual surgical conference, Colin learned about the digital tools making surgical devices smarter, from algorithms predicting post-operative complications and virtual reality modules assessing surgeon skills. Read more…

Modern Systems Power Financial Stewardship in Rural Healthcare. Bryant Blay at Iowa’s Montgomery County Memorial Hospital + Clinics and Mike Johnson at Multiview ERP explained how financial and revenue solutions can bridge the gap between clinical and back-office systems, supporting strong clinical care and more sustainable financial performance long term. Read more…

Is AI Orchestration the End of “Click Fatigue” in Healthcare? Orchestration works best when it runs in the background, RamSoft’s Vijay Ramanathan told Colin. On the other hand, standalone AI only creates more work. Read more…

Removing Fragmented Vendors and Info-Blocking Risks From Data Migrations. Colin heard from James (Jim) Hammer at Harmony Healthcare IT about the benefits of having one team handle data from legacy extraction straight through to the final archive. Read more…

Why Data Interoperability Should Not Be a Luxury. Every organization should combine its data into a single platform that handles the network, access, and aggregation, ELLKAY’s Gurpreet (GP) Singh told John Lynn. This addresses the current limitations of data exchange. Read more…

Using AI and Integrated Systems to Strengthen a Culture of Safety. Rachini Moosavi at UNC Health and August Calhoun at RLDatix outlined the benefits of connecting safety, workforce, compliance, and operational data on a single platform, including needing 75% less time to report an incident. Read more…

The AI Call Center Surprise at the 2026 eClinicalWorks Enterprise Summit. Colin was impressed that healow Genie can handle non-linear conversations, as an anonymized call played on the keynote stage showed the AI agent pivoting from refilling a prescription to scheduling an appointment. Read more… 

Helping Providers of All Sizes Adopt Epic. Med Tech Solutions’ Kaitlyn Nelson and Imran Siddiqui sat down with John to share how to handle Epic implementations from hosting to training to go-live to archiving legacy systems. Read more…

A Practical Approach to Hospital Downtime and Data Resiliency. Frederick Health CIO Jackie Rice and IPeople Healthcare President Ryan Dickerson discussed their approach of maintaining a secure, on‑premises copy of critical patient data that’s refreshed in near real time to provide reliable access during downtime. Read more…

Improving Email Deliverability, Compliance, and Third-Party Privacy. John connected with Ash Valeski at Proofpoint, which is helping hospitals make sure outgoing email meets the requirements of the receiving side and stopping email that contains sensitive information. Read more…

Transforming Workflows: AI and High-Performance Computing for Efficient Operations. John recapped a HIMSS panel that discussed how AI is changing core clinical workflows, as well as how to innovate in a financially sustainable way. Read more…

Life Sciences Today Podcast: Revolutionizing Clinical Trial Protocols. Danny Lieberman connected with Pedro Coelho at Biorce, which is building AI that fixes clinical trial protocol errors and foresees one-click clinical trials by the end of the year. Read more…

CIO Podcast: A CEO’s View on Healthcare Technology. Dr. Fatih Mehmet Gul at Qatar’s The View Hospital – Cedars-Sinai joined John to talk about the expectations CEOs have when it comes to AI, along with where IT has had a major impact in the hospital. Read more…

How Context-Driven AI is Finally Moving Healthcare Forward. Only 30% of AI pilots in healthcare successfully transition into production environments. Embedding domain experts within live workflows collapses the gap between development and operations and improves the odds of success, said Sathiyan Kutty at Emids. Read more…

The Hidden Compliance and Revenue Gaps in Home Health. ClientCare.pro founder Matt Sauced said agencies are leaving money on the table by treating eligibility verification and exclusion screening as one-time events, and by under-coding comorbidities. Read more…

Why Behavioral Health Spends More Time on Notes Than Any Other Specialty. Unstructured qualitative data means behavioral health providers spend half their time on administrative tasks. Templates, structured workflows, and automated note generation can help, said WellNotes AI founder Robert Botto. Read more… 

How AI-Driven Discharge Planning Can Reduce ED Boarding. Delayed discharges are an efficiency problem and a patient safety issue. The fix is predictive analytics that enables more proactive coordination of care and removes discharge bottlenecks, said Michelle Skinner at TeleTracking Technologies. Read more…

“Who Hosts Your Data?” Is Now a Compliance Question. BAAs establish accountability but doesn’t determine if hosting providers can withstand payer review, according to Kelly Goolsby at Nexcess. Ideally, a cloud partner has a dedicated environment, accessible documentation, and predictable costs. Read more…

This Week’s Health IT Jobs for April 22, 2026: San Francisco-based stealth-stage startup Uptake AI seeks a Founding CTO. Read more…

Bonus Features for April 19, 2026: Behavioral health makes up 66% of all telehealth visits; 70% of healthcare orgs hit with ransomware attacks pay up. Read more…

Funding and M&A Activity:

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



< + > Integration Into the Workflow Is Key to Ambient Scribe Success

The first year that Central Oklahoma Family Medical Center deployed the Sunoh.ai ambient transcription software, it was getting very littl...