Why Hospital Dashboards Tell the Future But Operations Remain Stuck in the Past
Over the past decade, health systems have poured sustained capital and attention into data infrastructure. Enterprise warehouses consolidated fragmented reporting environments. Interoperability initiatives linked EHR instances that had operated in parallel for years. Population health platforms brought predictive modeling into conversations about utilization and risk. Dashboards became ubiquitous, appearing in service line reviews, access meetings, ... Read More
<img width="1500" height="1000" src="https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-1500x1000.jpg" alt="Why Hospital Dashboards Tell the Future But Operations Remain Stuck in the Past" class="wp-image-95737" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-1500x1000.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-300x200.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-290x193.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-768x512.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-1536x1024.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/04/Osama-Usmani_headshot-2048x1365.jpg 2048w" sizes="(max-width: 1500px) 100vw, 1500px" /> Osama Usmani, Founder and CEO, Salubrum Over the past decade, health systems have poured sustained capital and attention into data infrastructure. Enterprise warehouses consolidated fragmented reporting environments. Interoperability initiatives linked EHR instances that had operated in parallel for years. Population health platforms brought predictive modeling into conversations about utilization and risk. Dashboards became ubiquitous, appearing in service line reviews, access meetings, finance updates, and clinical leadership forums. In technical terms, most large systems are no longer constrained by data scarcity. If anything, they operate amid an abundance of signal that existing planning processes were never redesigned to absorb. That abundance has not translated evenly into decision authority. In many organizations, intelligence still functions primarily as a reporting layer. Dashboards are reviewed quarterly. Predictive models are circulated before planning sessions. The discussion is often informed by them. The decisions that follow, however, are more frequently anchored in precedent, historical patterns, and negotiated compromise. Capacity planning, network configuration, and access management tend to move on established trajectories even when forward-looking indicators suggest pressure building elsewhere in the system. The constraint is not technical capability. It is sequencing. The Missing Owner of the Intelligence Layer Health systems have constructed sophisticated data environments, supported by governance committees that standardize definitions and regulate access. Analytics teams routinely generate risk stratification models, referral leakage analyses, and demand projections. Those outputs travel across the enterprise. What remains less consistently defined is who has the authority to act on them before staffing plans, capital allocations, or contracting strategies are finalized. One reason the gap persists is structural. The intelligence layer rarely has a clearly designated owner in the way data governance does, or in the way the EHR platform does. Responsibility is distributed across departments like IT and finance. Some of it lives in population health. Much of it depends on informal coordination between analytical and operational leaders who already carry full portfolios of responsibility. When that coordination works, it’s because specific individuals maintain it. When those individuals leave, the capability thins quietly. The impact may not surface until a planning cycle is already underway. When Analytics Maturity Outpaces Action The consequences are visible across service lines. Most large systems can identify bottlenecks in specialty scheduling. They can quantify referral leakage by region. They can project demand growth for high-acuity programs with reasonable confidence. Yet capacity adjustments often occur only after strain becomes measurable in lagging indicators. Hiring plans expand in response to backlogs. Clinic hours are extended once wait times are established. Network realignment follows volume shifts that have already materialized. A similar pattern appears in population health. Predictive models flag rising-risk cohorts months in advance. Resource allocation for care management, however, is frequently tethered to budget cycles and historical caseload distribution. The modeled signal is discussed. It is rarely allowed to reconfigure staffing or outreach strategy in real time. Over time, modeling capability improves while the organization’s ability to reposition resources in response advances more slowly. It is now common for service line leaders to monitor near real-time dashboards that track referral flow, payer mix changes, readmissions, and appointment utilization. Data visibility is not in question. What remains uneven is the translation of that visibility into upstream planning, particularly when commitments around staffing, clinic expansion, or capital deployment are already in motion. By the time insight is widely acknowledged, the cost of altering direction has often increased. Reporting Versus Governance In many systems, intelligence serves as validation after the fact. Performance is reviewed. Variances are explained. Corrective action plans are drafted. This rhythm reinforces a posture that is reactive even when predictive models are available. Part of the difficulty lies in organizational design. Analytics teams frequently report through IT or finance, while operational authority rests with clinical and service line leadership. Insights must cross departmental boundaries before they influence execution. That movement takes time. The window for anticipatory adjustment narrows. The distinction becomes clearer when compared with clinical workflows. Decision support tools embedded in the EHR have altered how care is delivered at the point of encounter. Quality committees, safety oversight groups, and clinical governance bodies provide structured pathways through which analytical outputs shape behavior. Outside the clinical encounter, the same clarity is harder to find. Network design, access management, care coordination sequencing, and geographic capacity planning often rely on analysis, but the integration of that analysis into formal decision rights is less systematic. Repositioning Intelligence in the Planning Cycle Integrating intelligence more deliberately into operational sequencing does not necessarily require new technology. It requires clarity about when decisions are made and how analytical output enters that timeline. Predictive modeling can inform annual capacity planning before mid-year strain forces incremental fixes. Referral leakage analysis can shape contracting strategy ahead of renegotiation cycles rather than after share has eroded. Access forecasting can influence staffing assumptions before recruitment begins. None of these adjustments depend on more dashboards. They depend on whether modeled projections carry binding authority at defined points in the planning calendar. Repositioning intelligence in this way is rarely frictionless. Service lines may resist ceding discretion to centralized modeling functions, particularly when projections influence resource allocation. Data definitions that were once technical details become contested once they determine capital distribution or staffing growth. The tension that follows is organizational. Health systems that manage the transition effectively tend to address decision rights explicitly. They clarify where projections are advisory and where they are determinative. They align analytics leadership more closely with operational authority so that insight does not remain isolated within reporting structures. From Descriptive to Structural Authority Health systems are not short on predictive capability. The more persistent challenge is institutional design. In many organizations, the intelligence layer has evolved incrementally, without being formalized as a governance function with clear ownership and defined integration into workflow. Additional modeling sophistication will not resolve that misalignment on its own. The next stage of digital maturity is likely to hinge less on technical advancement and more on whether intelligence is granted structural authority within planning cycles. Until that authority is clarified, even advanced analytics environments will continue to describe reality more often than they shape it. About Osama Usmani Osama Usmani is the Founder and CEO of Salubrum, a healthcare demand-intelligence company. He works with health systems, specialty providers, and healthcare organizations on data-driven commercialization strategy and patient acquisition infrastructure.
Why Abridge is Embedding NEJM and JAMA Directly into the EHR
What You Should Know The Partnerships: Enterprise AI platform Abridge has secured multi-year content partnerships with the NEJM Group (publisher of the New England Journal of Medicine) and the American Medical Association (publisher of the JAMA Network). The Workflow Shift: The integration allows clinicians to ask complex clinical questions and receive evidence-based answers directly within ... Read More
<img loading="lazy" width="1500" height="742" src="https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-1500x742.png" alt="Why Abridge is Embedding NEJM and JAMA Directly into the EHR" class="wp-image-95763" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-1500x742.png 1500w, https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-300x148.png 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-290x143.png 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-768x380.png 768w, https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-1536x759.png 1536w, https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-2048x1013.png 2048w, https://hitconsultant.net/wp-content/uploads/2026/04/Abridge-515x255.png 515w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Partnerships: Enterprise AI platform Abridge has secured multi-year content partnerships with the NEJM Group (publisher of the New England Journal of Medicine) and the American Medical Association (publisher of the JAMA Network). The Workflow Shift: The integration allows clinicians to ask complex clinical questions and receive evidence-based answers directly within their existing workflow. Historically, finding this literature required breaking focus, leaving the EHR, and searching external databases. The Context Engine: The Abridge Clinical Decision Support (CDS) system will now surface insights that are grounded in both elite peer-reviewed research and the specific patient context captured during the ambient listening phase of the encounter. Context-Aware Insights in Real Time Historically, clinicians seeking reliable research during an encounter had to step away from the patient, open separate tools, and perform manual searches. The Abridge platform solves this “workflow friction” by integrating content from the New England Journal of Medicine, JAMA, and 11 specialty journals directly into its AI-powered system. This integration supports the “full arc” of the clinical encounter: Pre-visit Preparation: Helping clinicians review relevant data before entering the room. During the Conversation: Capturing the patient interaction and surfacing cited insights to clinical questions in real time. Post-visit Documentation: Generating structured notes and grounding them in peer-reviewed evidence and patient context. “Clinicians are managing more complexity than ever,” said Dr. Shiv Rao, CEO and Co-Founder of Abridge. “We are committed to ensuring that [scientific] standard is integrated into the clinical encounter as contextual insight grounded in the patient conversation.” Grounding AI in Trusted Evidence As AI increasingly shapes clinical decision-making, the necessity for “grounded” information—data backed by peer-reviewed science rather than just statistical probability—has become paramount. “Our role is to ensure [AI] is grounded in trusted, peer-reviewed evidence,” noted David Sampson, Vice President and Chief Publishing Officer at NEJM Group. By delivering this evidence into the course of care, Abridge aims to inform physician-patient judgment with the highest scientific standards available. Availability and Expansion Abridge is currently projected to support over 100 million patient-clinician conversations this year across 250 of the largest health systems in the U.S. Current Availability: Abridge’s clinical decision support is already live with context-aware insights from Wolters Kluwer’s UpToDate. Upcoming Integrations: Content from the NEJM Group and JAMA Network is expected to become generally available within the platform in the coming months.
Sonire Therapeutics Raises $18M to Transform Pancreatic Cancer Treatment
What You Should Know The Raise: Clinical-stage medical device company Sonire Therapeutics has announced an $18M Series A financing round. The round was led by Santé Ventures, with participation from Fast Track Initiative (FTI), Nomura SPARX Investment, and SBI Investment. The Technology: Sonire has developed a proprietary High-Intensity Focused Ultrasound (HIFU) therapy system for the ... Read More
<img loading="lazy" width="1500" height="423" src="https://hitconsultant.net/wp-content/uploads/2026/04/Sonire_Logo.jpg" alt="Sonire Therapeutics Raises $18M to Transform Pancreatic Cancer Treatment" class="wp-image-95767" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Sonire_Logo.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/04/Sonire_Logo-300x85.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Sonire_Logo-290x82.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Sonire_Logo-768x217.jpg 768w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Raise: Clinical-stage medical device company Sonire Therapeutics has announced an $18M Series A financing round. The round was led by Santé Ventures, with participation from Fast Track Initiative (FTI), Nomura SPARX Investment, and SBI Investment. The Technology: Sonire has developed a proprietary High-Intensity Focused Ultrasound (HIFU) therapy system for the non-invasive thermal ablation of solid tumors. The Clinical Target: The company is initially focusing on pancreatic cancer, a notoriously lethal disease with a 5-year survival rate of only 12% and very limited local therapy options. The device received an FDA Breakthrough Device Designation in 2024. The Workflow Disruption: Unlike conventional ultrasound-guided HIFU systems, Sonire’s solution provides clear real-time visualization, requires no anesthesia, and can be performed on an outpatient basis in roughly 20 minutes. It also only requires one physician to administer, drastically lowering the staffing burden. A New Approach to Lethal Solid Tumors Pancreatic cancer remains a devastating diagnosis with a 5-year survival rate of just 12%. Current local therapy options are limited, leaving a high unmet medical need for patients. Sonire’s proprietary HIFU system is designed to prolong survival when combined with chemotherapy, offering a safer alternative to traditional surgery or radiation. Unlike conventional ultrasound-guided systems, Sonire’s technology provides several key clinical advantages: Enhanced Visualization: Patented noise-cancellation and cavitation bubble visualization allow for clear, real-time imaging of the treatment site. Outpatient Convenience: The procedure typically takes only 20 minutes, requires no anesthesia, and is performed on an outpatient basis. Operational Efficiency: The system is robot-assisted and requires only one physician to administer, reducing the staffing burden and cost for hospitals. Precision Engineering: Advanced multi-focus scanning enables precise thermal ablation of tumors. Landmark Clinical Progress The funding will support the completion of the SUNRISE-I randomized controlled trial in Japan. This study is the world’s first of its kind to evaluate HIFU combined with chemotherapy specifically for pancreatic cancer. Early foundational work using a prototype system demonstrated a 66% disease control rate in patients with advanced pancreatic and biliary tract cancers. With 25 issued patents and its 2024 FDA Breakthrough Device Designation, Sonire is now expanding its corporate footprint from Tokyo to its new headquarters in Palo Alto, California. Scaling for Global Impact “Our goal is to deliver a new standard of care that gives patients more time and better quality of life,” said Tohru Satoh, President and CEO of Sonire Therapeutics. As the company prepares for U.S. clinical and regulatory milestones, it aims to prove that next-generation acoustic engineering can solve the core challenges of precision and workflow that have historically limited the field of oncology.
Osteoboost Health Raises $8M for FDA-Cleared Bone Density Device
What You Should Know The Raise: Osteoboost Health has closed an $8M financing round led by Ambit Health Ventures, with participation from Emmeline Ventures, Disrupt Health Impact Fund, Esplanade Ventures, and Portfolia. The Device: The FDA-cleared “Osteoboost” device is a wearable belt worn low around the hips. It delivers targeted, precisely calibrated vibration therapy directly ... Read More
<img loading="lazy" width="720" height="720" src="https://hitconsultant.net/wp-content/uploads/2026/04/image-5.png" alt="Osteoboost Health Raises $8M for FDA-Cleared Bone Density Device" class="wp-image-95780" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/image-5.png 720w, https://hitconsultant.net/wp-content/uploads/2026/04/image-5-300x300.png 300w, https://hitconsultant.net/wp-content/uploads/2026/04/image-5-290x290.png 290w, https://hitconsultant.net/wp-content/uploads/2026/04/image-5-100x100.png 100w" sizes="(max-width: 720px) 100vw, 720px" /> What You Should Know The Raise: Osteoboost Health has closed an $8M financing round led by Ambit Health Ventures, with participation from Emmeline Ventures, Disrupt Health Impact Fund, Esplanade Ventures, and Portfolia. The Device: The FDA-cleared “Osteoboost” device is a wearable belt worn low around the hips. It delivers targeted, precisely calibrated vibration therapy directly to the lumbar spine and hips (the regions most vulnerable to fracture). The Clinical Gap: The device targets osteopenia, the precursor to osteoporosis. Nearly 44 million Americans live with low bone density, and bone loss accelerates rapidly during menopause. Currently, there are no approved drug therapies for osteopenia, leaving patients with few proactive options beyond calcium and exercise. The Science: The vibration therapy was inspired by NASA-funded research. In a double-blinded clinical trial, patients who used the device 3 times per week for 30-minute sessions over a 12-month period slowed bone density loss by 85% in the spine and 55% in the hips. A First-of-Its-Kind Solution for Osteopenia While nearly 54 million Americans live with osteoporosis or low bone density, few proactive options exist for women during menopause, when bone loss accelerates rapidly. Osteoboost is a class II prescription medical device and stands as the first and only FDA-cleared, non-drug treatment clinically proven to treat low bone density in postmenopausal women with osteopenia. “The cost of osteoporosis to society is enormous, but this is not a condition that begins at diagnosis,” said Laura Yecies, CEO of Osteoboost Health. “This funding advances Osteoboost’s vision of building a complete bone health solution and changing the trajectory of bone health for millions.” Proven Clinical Impact The device, worn around the hips, delivers precisely calibrated, low-magnitude vibration therapy to the lumbar spine and hips—the areas most vulnerable to fracture. Inspired by NASA-funded research, a double-blinded clinical trial at the University of Nebraska Medical Center proved the device’s efficacy: Spine: Slowed bone density loss by 85%. Hips: Slowed bone density loss by 55%. Usage: Results achieved by patients using the device at least three times per week for 30-minute sessions. Addressing an Underfunded Market The financing comes at a critical time for women’s health. Despite the immense need, a 2026 World Economic Forum report highlighted that the sector receives only 6% of private healthcare capital. Osteoboost addresses a significant “gap” in care for peri- and post-menopausal women who have osteopenia but do not yet qualify for approved drug therapies. A Comprehensive Ecosystem for Bone Health Beyond the wearable device, the company is building a holistic ecosystem through Wellen by Osteoboost. This asynchronous video training platform, developed by physical therapists, has shown remarkable results: Strength: Users improved lower-body strength by 22.8% after 18 sessions. Fall Risk: Nearly 80% of participants at elevated risk improved to average or above-average levels. Osteoboost, which was named one of TIME’s Best Inventions of 2025, has already been prescribed by more than 2,500 unique physicians across leading academic medical centers since shipping began in May 2025.
The Clinical Resolution Gap: Why AI Can’t Fix Broken MSK Care Platforms
Chris Cato, DC, Chief Population Health Officer at Airrosti
For years, clinicians have complained about the same thing: they became doctors to care for patients, not to stare at screens. The electronic health record inserted a keyboard into the most important relationship in medicine. Now, for the first time in decades, artificial intelligence (AI) is beginning to remove it. Ambient listening technology is giving ... Read More
<img loading="lazy" width="800" height="800" src="https://hitconsultant.net/wp-content/uploads/2026/04/Dr.-Chris-Cato-Airrosti-Headshot.jpg" alt="The Clinical Resolution Gap: Why AI Can’t Fix Broken MSK Care Platforms" class="wp-image-95734" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Dr.-Chris-Cato-Airrosti-Headshot.jpg 800w, https://hitconsultant.net/wp-content/uploads/2026/04/Dr.-Chris-Cato-Airrosti-Headshot-300x300.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Dr.-Chris-Cato-Airrosti-Headshot-290x290.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Dr.-Chris-Cato-Airrosti-Headshot-768x768.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/04/Dr.-Chris-Cato-Airrosti-Headshot-100x100.jpg 100w" sizes="(max-width: 800px) 100vw, 800px" /> Chris Cato, DC, Chief Population Health Officer at Airrosti For years, clinicians have complained about the same thing: they became doctors to care for patients, not to stare at screens. The electronic health record inserted a keyboard into the most important relationship in medicine. Now, for the first time in decades, artificial intelligence (AI) is beginning to remove it. Ambient listening technology is giving providers back the focused attention that documentation demands have quietly eroded. That is not a minor workflow improvement. It is a restoration of something fundamental to good care. And yet, the most important question in healthcare AI right now is not what it is fixing. It is what it’s not fixing, and whether the industry has the discipline to tell the difference. Improving the experience of care delivery is not the same as improving the outcomes of care itself. In a healthcare economy where employers and health plans are ultimately evaluated on total cost and clinical results, conflating the two carries real consequences. Acceleration Is Not the Same as Improvement AI excels at the mechanics of healthcare delivery. It increases speed, sharpens triage, automates clinical documentation, and surfaces patterns humans might miss. It improves access and reduces administrative overhead in ways the system has needed for years. None of that is trivial. But the critical question is not whether AI makes healthcare faster. It is whether AI improves resolution, modifies disease trajectories, produces outcomes that are durable rather than temporary, and reduces total cost of care over time. Those questions remain largely unanswered, and the industry’s enthusiasm for AI’s operational gains has made it easier to avoid asking them. Until AI is embedded within models that are accountable for durable outcomes, it will improve workflow more reliably than it will improve health. What MSK Reveals About the Resolution Gap Musculoskeletal (MSK) care offers a revealing case study. MSK is one of the largest cost drivers in employer-sponsored health plans, accounting for roughly 17 cents of every healthcare dollar, and it has become one of the most active categories for AI-enabled digital health investment. It is also a space where the gap between what a platform measures and what an employer actually needs has become unusually visible. Many digital MSK platforms track logins, exercise completion, range of motion, chat engagement, and app adherence, and by digital health standards the engagement data can look compelling. But employers and health plans are not purchasing engagement. They are evaluating episode duration, imaging avoidance, surgery deflection, downstream utilization, and total cost of care. Between those two sets of metrics, there is a gap that AI-guided digital platforms have not closed. The reason is biological. MSK dysfunction is frequently physical and structurally driven, and when tissue is compromised, behavioral guidance alone cannot correct the underlying problem, however intelligent or personalized that guidance may be. AI can shape behavior. It cannot perform the corrective intervention that compromised tissue actually requires. When the required mechanism is physical, a digital-first model will optimize engagement while condition driving cost continues unresolved. Engagement is not resolution. And the two do not automatically converge. The Risk of Scaling Partial Care OpenAI, Google, Microsoft, and a growing field of digital health companies are deploying AI copilots, clinical decision support tools, generative intake systems, and risk stratification platforms across the care continuum. These capabilities genuinely improve access. They reduce the friction of entering the healthcare system and support clinical workflows in ways that providers benefit from. But access without accountability for what happens downstream does not solve the cost problem. It accelerates the referral cycle. When AI optimizes the front end of care without improving resolution at the point of intervention, the underlying driver of cost remains untouched. Amplification without resolution does not improve care. It scales partial care, and partial care delivered at greater speed and volume does not become less partial. Digital-First Models Optimize Engagement. Resolution-First Models Optimize Outcomes. MSK is high volume, high cost, highly variable, and historically resistant to durable resolution. In that sense, it is not an exception to the broader healthcare AI story, but a clarifying lens for it. The same dynamic that produces an engagement gap in digital MSK applies across condition categories where the required clinical mechanism cannot be delivered through a screen. Digital-first models are optimized for reach, scalability, and consistent delivery of guidance and education. In the right context, they support better outcomes. But when MSK dysfunction requires clinical intervention, durable improvement demands more than guided exercise and behavioral nudges. It requires a clinician who is accountable for functional restoration. Resolution-first care models are built around that accountability, with digital tools supporting the delivery of outcomes rather than substituting the clinical work that produces them. Employers evaluating MSK vendors are increasingly in a position to see that distinction clearly. The Next Breakthrough Will Not Be AI-First AI is entering care delivery with enormous promise, and the early gains in workflow efficiency, clinical documentation, and provider experience are real. Better technology matters. But better technology does not automatically produce better outcomes. Outcomes are driven by accountability to resolution, and that is something no platform delivers on its own. That is a meaningful start. The next breakthrough in healthcare will not be AI-first. It will be outcome-accountable and supported by AI. Care models rebuilt around accountability for resolution, with AI supporting the delivery of those outcomes throughout, represent a genuine clinical advance. AI deployed as a layer on top of models that were never accountable for outcomes will accelerate whatever those models already produce, including their limitations. The breakthrough healthcare is waiting for will not be measured in app downloads, engagement scores, or AI adoption rates. It will be measured in something far simpler: whether patients actually recover, and whether the total cost of care finally begins to fall. About Chris Cato, DC Chris Cato, DC, is Chief Population Health Officer at Airrosti, where he leads national strategy and partnerships with employers, health plans, health systems, and ACOs to advance value-based musculoskeletal care. With more than 28 years of healthcare experience, he focuses on scaling clinically proven models that improve outcomes, reduce total cost of care, and reshape how organizations approach muscle and joint health. Chris is a recognized thought leader in employer-sponsored MSK strategy and population health innovation, frequently contributing insights on care navigation, resolution-focused treatment, and the future of value-driven healthcare.
AliveCor Secures CE Mark for Kardia 12L AI-Powered ECG System in Europe
What You Should Know The Milestone: AliveCor, a global leader in AI-powered cardiology, has secured a CE Mark (Conformité Européenne) for its Kardia 12L electrocardiogram (ECG) system, allowing it to be distributed across the European Economic Area. The Hardware Shift: The Kardia 12L effectively replaces the traditional, bulky 10-electrode ECG cart. It utilizes a unique ... Read More
<img loading="lazy" width="1500" height="1500" src="https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-1500x1500.jpg" alt="AliveCor Secures CE Mark for Kardia 12L AI-Powered ECG System in Europe" class="wp-image-95766" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-1500x1500.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-300x300.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-290x290.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-768x768.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-1536x1536.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-2048x2048.jpg 2048w, https://hitconsultant.net/wp-content/uploads/2026/04/Kardia-12L-ECG-System_Square-100x100.jpg 100w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Milestone: AliveCor, a global leader in AI-powered cardiology, has secured a CE Mark (Conformité Européenne) for its Kardia 12L electrocardiogram (ECG) system, allowing it to be distributed across the European Economic Area. The Hardware Shift: The Kardia 12L effectively replaces the traditional, bulky 10-electrode ECG cart. It utilizes a unique single-cable, five-electrode design, runs on batteries, and weighs just 0.13 kg (0.3 lbs). The AI Engine: The device is powered by the KAI 12L AI algorithm. Using just the reduced leadset, the AI is cleared to detect 35 cardiac determinations, including 14 arrhythmias and 21 morphologies. Crucially, this includes life-threatening conditions like acute myocardial infarction (heart attacks) and cardiac ischemia. The Clinical Workflow: Because the hardware is simplified to five electrodes, patients do not need to fully disrobe during a reading. Research indicates this design yields a nearly 30% reduction in ECG acquisition time compared to standard 12-lead setups. The Rollout: Following its U.S. launch in June 2024, the CE Mark clears the way for AliveCor to immediately deploy the technology to healthcare providers in France, Germany, Italy, Spain, and the United Kingdom, with additional countries following shortly. A New Standard for Point-of-Care Diagnostics The Kardia 12L system is designed to replace bulky, traditional ECG carts with a pocket-sized, battery-operated device weighing just 0.13 kg (0.3 lbs). Unlike standard setups that require 10 electrodes and significant patient disrobing, the Kardia 12L uses a simplified five-electrode, single-cable design. Key advantages of the system include: Rapid Acquisition: Clinical research has shown a nearly 30% reduction in ECG acquisition time compared to traditional setups. Diagnostic Depth: Powered by KAI 12L AI, the system can detect 35 cardiac determinations, including 14 arrhythmias and 21 morphologies. Life-Saving Detection: The AI is specifically cleared to identify acute myocardial infarction (MI) and common types of cardiac ischemia in real time. Expanding Global Access Since its U.S. FDA clearance in June 2024, the Kardia 12L has already been adopted in India, Australia, Canada, and several other nations. To date, the system has identified over 4,000 instances of MI and ischemia globally. In Europe, the launch aligns with the EU Cardiovascular Health Plan, which prioritizes early detection and prevention of cardiovascular diseases—the leading cause of mortality in the region. Availability The Kardia 12L will initially be available to healthcare providers in the following countries: France Germany Italy Spain United Kingdom Expansion into additional European countries is expected to follow shortly. While the device is highly portable, it is intended strictly for use by healthcare professionals in settings ranging from hospitals and urgent care centers to pharmacies and rural clinics. “Our priority is to get this life-saving technology into the hands of as many clinicians as possible, especially in settings where traditional, bulky ECG carts simply aren’t practical,” said Simona Esposito, Senior Vice President of Sales, Global Markets at AliveCor.
HHS Launches $4M EMPOWER Prize Challenge to Enhance Living Kidney Donation
What You Should Know The Challenge: The U.S. Department of Health and Human Services (HHS) has launched the 2026 KidneyX EMPOWER Prize Challenge, a $4M national competition to accelerate innovations supporting living kidney donors. The Core Problem: The math surrounding kidney disease is incredibly bleak. Over 100,000 Americans are waitlisted for a kidney, and more ... Read More
<img loading="lazy" width="800" height="418" src="https://hitconsultant.net/wp-content/uploads/2026/04/KidneyX-Empower.jpeg" alt="HHS Launches $4M EMPOWER Prize Challenge to Revolutionize Living Kidney Donation" class="wp-image-95769" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/KidneyX-Empower.jpeg 800w, https://hitconsultant.net/wp-content/uploads/2026/04/KidneyX-Empower-300x157.jpeg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/KidneyX-Empower-290x152.jpeg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/KidneyX-Empower-768x401.jpeg 768w" sizes="(max-width: 800px) 100vw, 800px" /> What You Should Know The Challenge: The U.S. Department of Health and Human Services (HHS) has launched the 2026 KidneyX EMPOWER Prize Challenge, a $4M national competition to accelerate innovations supporting living kidney donors. The Core Problem: The math surrounding kidney disease is incredibly bleak. Over 100,000 Americans are waitlisted for a kidney, and more than a dozen die each day waiting. Despite being one of the most effective treatments, the number of living kidney donors has remained virtually flat at fewer than 7,000 per year for two decades. The Innovation Targets: The $4 million prize seeks solutions across five specific barriers: Public Awareness, Donor Interventions (addressing surgery fears), Donor Readiness (BMI management, smoking cessation, financial planning), Donor-Centered Outcomes (long-term tracking), and Center Practices (reducing administrative delays). Breaking Barriers to Living Donation The EMPOWER Prize Challenge, managed through the Kidney Innovation Accelerator (KidneyX), directly targets the financial, logistical, and educational hurdles that prevent potential donors from coming forward. The competition seeks practical solutions in five key areas: Public Awareness & Mentorship: Building community-based models to identify and support potential donors. Donor Interventions: Creating educational tools to address surgical fears and long-term health concerns. Donor Readiness & Eligibility: Helping donors overcome barriers like BMI management, smoking cessation, and financial planning. Donor-Centered Outcomes: Implementing long-term monitoring strategies to ensure the well-being of donors after their procedure. Center Practices: Sharing successful best practices to reduce administrative delays across different geographic regions. Modernizing the Kidney Care Data Infrastructure In tandem with the prize challenge, the Office of the National Coordinator for Health Information Technology (ONC) is partnering with the nephrology community to improve data standardization. This effort aims to: Enhance Interoperability: Enable seamless and secure data exchange across the kidney care ecosystem. Support Decision-Making: Provide clinicians and patients with better tools for clinical coordination and research. Modernize Transplantation: Improve the national organ procurement system to ensure more equitable access to life-saving transplants. About KidneyX KidneyX is a public-private partnership between HHS and the American Society of Nephrology (ASN). Since its inception, KidneyX has awarded over $25M to more than 70 winners to transform the prevention, diagnosis, and treatment of kidney disease. Innovators interested in participating in the $4M challenge can find more information and apply at kidneyxempowerchallenge.org.
CMS Establishes New Billing Code for AI-Driven Calcium Analysis on CT Scans
What You Should Know The Reimbursement Milestone: Effective April 1, 2026, the Centers for Medicare and Medicaid Services (CMS) has established a new national billing code and payment pathway under the Hospital Outpatient Prospective Payment System (OPPS) for the algorithmic analysis of coronary artery calcium (CAC) and aortic valve calcium (AVC) on chest CT scans. ... Read More
<img loading="lazy" width="1200" height="630" src="https://hitconsultant.net/wp-content/uploads/2026/04/image-4.png" alt="CMS Establishes New Billing Code for AI-Driven Calcium Analysis on CT Scans" class="wp-image-95771" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/image-4.png 1200w, https://hitconsultant.net/wp-content/uploads/2026/04/image-4-300x158.png 300w, https://hitconsultant.net/wp-content/uploads/2026/04/image-4-290x152.png 290w, https://hitconsultant.net/wp-content/uploads/2026/04/image-4-768x403.png 768w" sizes="(max-width: 1200px) 100vw, 1200px" /> What You Should Know The Reimbursement Milestone: Effective April 1, 2026, the Centers for Medicare and Medicaid Services (CMS) has established a new national billing code and payment pathway under the Hospital Outpatient Prospective Payment System (OPPS) for the algorithmic analysis of coronary artery calcium (CAC) and aortic valve calcium (AVC) on chest CT scans. The FDA Clearance: In tandem with the CMS news, Bunkerhill Health received FDA clearance for Bunkerhill Contrast CAC and Bunkerhill Contrast AVC. These are the first and only AI algorithms cleared to detect and quantify calcium on contrast-enhanced, routine non-gated chest CT scans. The Agentic Workflow: The algorithms live within Carebricks, Bunkerhill’s agentic AI platform. When the AI detects dangerous calcium levels, Carebricks allows the health system to deploy “AI agents” to automatically initiate cardiology referrals, coordinate follow-up care, and message providers. Expanding Diagnostic Capabilities via FDA Clearance In tandem with the reimbursement milestone, Bunkerhill received FDA clearance for Bunkerhill Contrast CAC and Bunkerhill Contrast AVC. These represent the first and only AI algorithms cleared to detect and quantify calcium on contrast-enhanced, routine non-gated chest CT scans. This clearance significantly expands the utility of imaging that patients already receive. Previously, automated calcium quantification was largely limited to non-contrast scans; now, clinicians can capture these highly actionable findings from routine studies performed at scale for a wide range of clinical indications. A New National Reimbursement Pathway Bunkerhill led the submission to CMS through the New Technology APC pathway, engaging directly with the agency to define a framework for AI-enabled cardiovascular analysis. “Establishing a reimbursement pathway is an important step toward broader adoption of AI in clinical care,” said Nishith Khandwala, co-founder and CEO of Bunkerhill Health. The new framework provides health systems with the financial clarity needed to incorporate AI-driven insights into their standard clinical workflows. From Insights to Action: The Carebricks Platform The new algorithms are deployed via Carebricks, Bunkerhill’s “system of action.” This AI platform allows health systems to build and deploy AI agents that do more than just analyze images: Holistic Reasoning: Agents use Large Language Models (LLMs) and FDA-cleared algorithms to reason across a patient’s entire medical history. Real-World Execution: Beyond detection, these agents can trigger referrals, coordinate follow-up care, send notifications to providers and patients, and place medical orders. Rapid Deployment: Carebricks enables clinical teams to design and test new AI-driven processes in days rather than months. Collaborative Innovation The algorithms were developed through a research consortium involving top-tier academic institutions, including UCSF, Emory University, and MedStar Health. This multi-institutional approach ensured that the AI was validated across diverse clinical environments, preparing it for immediate impact in health systems nationwide.
Wavelet Medical Secures $7M to Scale AI Fetal Brain Monitoring Globally with Aegis Ventures
What You Should Know The Raise & Partnership: Wavelet Medical, an AI-powered fetal brain monitoring startup spun out of Yale, has raised $7M in seed funding and entered into a co-creation partnership with the venture studio Aegis Ventures. The Solution: Wavelet has developed the first non-invasive, AI-powered fetal electroencephalography (EEG) monitoring platform. Instead of looking ... Read More
<img loading="lazy" width="1500" height="795" src="https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring-1500x795.jpg" alt="Yale Startup Wavelet Medical Raises $7M to Optimize Fetal Brain Monitoring Wavelet Medical Raises $7M Seed Round with Aegis Ventures for Non-Invasive Fetal EEG Platform Wavelet Medical Secures $7M Seed Round to Scale AI Fetal Monitoring Globally" class="wp-image-95760" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring-1500x795.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring-300x159.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring-290x154.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring-768x407.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring-1536x814.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/04/Wavelet-Medical-Advanced-Fetal-Brain-Monitoring.jpg 1844w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know The Raise & Partnership: Wavelet Medical, an AI-powered fetal brain monitoring startup spun out of Yale, has raised $7M in seed funding and entered into a co-creation partnership with the venture studio Aegis Ventures. The Solution: Wavelet has developed the first non-invasive, AI-powered fetal electroencephalography (EEG) monitoring platform. Instead of looking at the heart, Wavelet measures the organ that directly reflects neurological status: the brain. The Tech Architecture: The device uses sensors placed on the mother’s abdomen. Proprietary AI algorithms—engineered by co-founder and Head of Science Dr. Jose Cortes-Briones—reconstruct the fetal EEG from these abdominal signals to identify auditory-evoked brain responses that signal neurological distress in real time. The Traction: The platform is currently being piloted across three major clinical sites: Yale University, LA General Hospital/USC, and South Korea’s Yonsei University Health System. Non-Invasive Fetal EEG Founded by Liz Golden, Dr. Emily Lee, and Dr. Jose Cortes-Briones, Wavelet has developed the first non-invasive, AI-powered fetal electroencephalography (EEG) platform. Historically, capturing fetal brain activity from outside the womb was considered impossible. Wavelet’s proprietary AI algorithms reconstruct EEG signals captured through the mother’s abdomen to identify auditory-evoked brain responses that signal distress in real time. “Until recently, noninvasive fetal EEG from the maternal abdomen was not feasible,” says Dr. Cortes-Briones. “We are now harnessing AI to reconstruct fetal EEG and translate it into quantitative markers of fetal distress.” A Strategic Partnership for Global Scale Wavelet is moving from a laboratory discovery at Yale to a global commercial entity through a pivotal partnership with Aegis Ventures. As a new Aegis portfolio company, Wavelet has secured $7M in seed funding to accelerate product development and clinical adoption. Aegis Ventures, a New York-based venture studio, identified maternal-fetal medicine as a sector primed for predictive AI innovation. The partnership was facilitated through Yale Ventures and is supported by the Aegis Digital Consortium, which includes leading health systems like Yale New Haven Health. Redefining the Standard of Care Clinical leaders suggest this technology could be the most significant evolution in fetal monitoring in over 50 years. Precision Diagnostics: By measuring direct brain activity, Wavelet aims to detect hypoxia earlier than traditional methods. Reduced Interventions: High predictive value could significantly lower the rate of avoidable C-sections. Global Demand: International partners, including Yonsei University in Asia, anticipate high demand from parents concerned about neurodevelopmental delays. Wavelet is currently undergoing testing at three clinical sites, including LA General and USC, as it prepares for expanded clinical trials. “This isn’t about building a device,” says CEO Liz Golden. “It’s about building a new category in maternal health—one grounded in data, precision, and prevention.”
Finding the Right Five Percent: How Machine Learning Is Reshaping Care Management
Mary Bacaj, Ph.D., President of Value-Based Care at Conifer Health Solutions
Population Health Has a Precision Problem Population health programs continue to rely on blunt tools. Many risk stratification approaches emphasize historical utilization—basic risk scores or vendor-generated models that explain who was expensive—rather than identifying emerging clinical risk. These methods struggle to detect deterioration early enough to influence outcomes. At the same time, care management teams face persistent ... Read More
Mary Bacaj, Ph.D., President of Value-Based Care at Conifer Health Solutions Population Health Has a Precision Problem Population health programs continue to rely on blunt tools. Many risk stratification approaches emphasize historical utilization—basic risk scores or vendor-generated models that explain who was expensive—rather than identifying emerging clinical risk. These methods struggle to detect deterioration early enough to influence outcomes. At the same time, care management teams face persistent resource constraints. Organizations cannot provide intensive support to every member. Clinical capacity must be allocated deliberately, and success depends on identifying which members need intervention early—before preventable hospitalizations and escalating costs occur. Clinical Informatics Meets Analytics The difference between managing volume and managing risk is anticipation. Effective population health programs must estimate disease severity and future cost before clinical decline occurs. Predictive accuracy has become both a clinical and financial necessity. This has led some organizations to integrate clinical informatics more directly into analytic development. When clinical reasoning informs how models are built—and analytics, in turn, inform care strategy—risk identification becomes more actionable. Rather than treating predictive models as static tools layered onto workflows, this approach allows care management strategy and analytic design to evolve together. From Claims to Disease A growing body of work supports a disease-centered view of risk. Traditional analytics treat claims as isolated events, counting visits, procedures, or prescriptions as separate indicators of utilization. In contrast, disease-based approaches aggregate medical and pharmacy claims into unified profiles that reflect how conditions progress over time. For example, laboratory testing, neuropathy treatment, specialist visits, and medication patterns can be evaluated as components of a single disease burden rather than unrelated transactions. These profiles create a consistent unit of analysis at both the disease and member level, reflecting current clinical complexity and revealing where risk is accumulating—allowing care teams to intervene earlier and more precisely. Why Machine Learning Matters (and What It Actually Means Here) Machine learning enhances this framework by improving pattern detection in complex, nonlinear clinical data. For decades, healthcare analytics relied primarily on linear regression models. While effective with limited variables, these methods struggle in populations with multiple interacting conditions. In diseases such as heart failure, traditional models explain only a modest share of future cost variation. Machine learning models can incorporate broader variable sets and identify relationships that linear approaches miss. When designed carefully, they improve predictive performance without sacrificing interpretability or operational stability. As a result, organizations are increasingly applying these methods to complex, high-cost conditions where earlier intervention yields the greatest clinical and financial impact. Cost as a Proxy for Severity: Finding the Members Who Truly Need Help Improved prediction allows projected cost to function as a practical proxy for clinical severity. While morbidity scoring and documentation practices vary widely across populations, elevated expected cost remains strongly correlated with complexity, instability, and care coordination needs. By identifying members whose annual costs are likely to reach six figures before deterioration occurs, care teams can intervene earlier with targeted, support-intensive engagement. This precision is essential when resources are limited and only a small fraction of the population can receive high-touch care. If only 5% of members can receive intensive intervention, the credibility of a population health program depends on ensuring it is the right 5%. This precision becomes critical when resources are limited and support-intensive engagement is required with only a small fraction of the population. The central operational question is straightforward: if only 5% of members can receive high-touch intervention, how do organizations ensure it’s the right 5%? Accurate risk stratification is the foundation of any credible answer. Agility Matters in a Changing Clinical Environment Analytic models must keep pace with evolving clinical practice. New diagnoses, therapies, and treatment pathways emerge faster than many analytic frameworks can adapt. Organizations that maintain tighter integration between clinical expertise and model development are better positioned to keep risk stratification aligned with current standards of care. Translating Analytics into Action: Empowering Care Management Nurses The true value of predictive analytics is realized at the point of care management. When insights are delivered directly to nurses and care coordinators—showing disease severity, likely trajectories, and which members are most likely to benefit from immediate outreach—analytics move from reporting to decision support. This alignment allows care teams to focus time and attention where it matters most, reducing avoidable admissions, lowering inpatient utilization, and improving the member experience. More importantly, it supports a sustainable operating model in which clinical judgment and data-driven insight reinforce one another. Precision, Not Volume, Defines the Next Era of Population Health Analytics and predicting population health trends will continue to evolve to become more precise. Even with better analytics, the clinical and member interaction is the driving force in behavior change and supporting members along their healthcare journey. Making those interactions more impactful and precise will define the next era of population health. About Mary Bacaj, Ph.D. As President of Value-Based Care (VBC) for Conifer Health Solutions, Mary Bacaj is responsible for leading the company’s business unit that delivers population health management and financial risk management services to more than 250 organizations. Conifer VBC is uniquely positioned as a partner to employers and unions, risk-bearing healthcare providers and health plans. Mary joined Conifer Health in 2014 as Vice President of Strategy to help the company identify and implement solutions that ensure individuals receive the right care at the right time, while healthcare providers are aligned to improve the health of the population. She is a recognized subject matter expert in pay-for-performance programs, hospital and physician alliances, and healthcare reform. Prior to joining Conifer Health, she was an Engagement Manager at McKinsey & Company, where she worked with senior executives at health systems and health technology companies on strategic challenges, such as population health management, hospital and physician mergers and acquisitions, and risk-based contracting. REFERENCES CMS Medicaid Innovation Accelerator Program (IAP) – Risk Stratification factsheet (risk stratification to identify beneficiaries with complex needs and high costs; prioritizing resources). Centers for Medicare & Medicaid Services. Medicaid Innovation Accelerator Program: Risk Stratification Factsheet. https://www.medicaid.gov/state-resource-center/innovation-accelerator-program/iap-downloads/program-areas/factsheet-riskstratification.pdf AHRQ Evidence Summary – Management of High-Need, High-Cost Patients. Agency for Healthcare Research and Quality. Interventions to Improve Outcomes for High-Need, High-Cost Patients: An Evidence Summary. https://effectivehealthcare.ahrq.gov/sites/default/files/related_files/Evidence%20Summary.pdf STRATIS Health – Population Risk Stratification & Patient Cohort Identification. Stratis Health. Population Risk Stratification and Patient Cohort Identification. Published July 2020. https://stratishealth.org/wp-content/uploads/2020/07/3-Population-Risk-Stratification-and-Patient-Cohort-Identification.pdf National Association of Community Health Centers (NACHC) – Risk Stratification Action Guide. National Association of Community Health Centers. Risk Stratification Action Guide. https://www.nachc.org/wp-content/uploads/2023/07/Action-Guide_Risk-Stratification.pdf AHRQ – Care Management and Coordination Implementation Guide. Agency for Healthcare Research and Quality. Care Management and Coordination. https://www.ahrq.gov/ncepcr/care/coordination/mgmt.html Systematic Review of Interventions for High-Need, High-Cost Patients. Schickedanz A, McCarthy D, et al. Interventions to Improve Outcomes for High-Need, High-Cost Patients: A Systematic Review. J Ambul Care Manage. 2023;46(1):1-13. https://pmc.ncbi.nlm.nih.gov/articles/PMC9849489/ National Care Coordination Intervention RCT (2025) – Example citation. Smith J, Patel R, Lee C, et al. Randomized Trial of Care Coordination for High-Need, High-Cost Patients. JAMA Netw Open. 2025;8(4):e2055281. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2835521
Ultralight Raises $9.3M to Launch AI-Native Operating System for Healthcare
What You Should Know: The Rebrand and Raise: Vibrant Practice has officially rebranded to Ultralight and announced a $9.3M funding round to build an AI-native operating system for modern medicine. The Backers: The round was led by The General Partnership, with participation from Wisdom Ventures, Anthemis Group, Emerson Collective, GSBackers, and notable angel investors, including ... Read More
<img loading="lazy" width="1500" height="1215" src="https://hitconsultant.net/wp-content/uploads/2026/04/ultralight-1500x1215.jpg" alt="" class="wp-image-95753" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/ultralight-1500x1215.jpg 1500w, https://hitconsultant.net/wp-content/uploads/2026/04/ultralight-300x243.jpg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/ultralight-290x235.jpg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/ultralight-768x622.jpg 768w, https://hitconsultant.net/wp-content/uploads/2026/04/ultralight-1536x1244.jpg 1536w, https://hitconsultant.net/wp-content/uploads/2026/04/ultralight.jpg 1573w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know: The Rebrand and Raise: Vibrant Practice has officially rebranded to Ultralight and announced a $9.3M funding round to build an AI-native operating system for modern medicine. The Backers: The round was led by The General Partnership, with participation from Wisdom Ventures, Anthemis Group, Emerson Collective, GSBackers, and notable angel investors, including former Surgeon General Vivek Murthy. The DPC Tipping Point Direct Primary Care (DPC) practices tripled among family physicians in a single year. Consumers are driving a $6.8 trillion wellness economy, voting with their wallets for physicians who actually know them. Furthermore, DPC memberships are now HSA-eligible, removing a massive financial barrier for patients seeking continuous, personalized care. However, running these modern, subscription-based clinics on legacy software designed for fee-for-service billing is incredibly painful. Technology in the exam room has historically felt heavy and cumbersome, turning highly trained physicians into data-entry clerks who spend their evenings charting. Technology That Feels “Ultralight” Healthcare technology shouldn’t feel heavy, cumbersome, or intrusive. The company’s new name, Ultralight, represents what we believe medical tech should be: Invisible Infrastructure: The technology works in the background, allowing the clinician to stay present and the patient to feel truly seen. Ending “Keyboard Burnout”: Clinicians should not spend their evenings on administrative tasks and charting. Unified Operations: Replace the “Frankenstein” stack of disconnected tools with a single, AI-native operating system. Recent Traction/Milestones Scale: Live in 75 clinics, supporting hundreds of physicians and thousands of patients. System Replacement: 60% of the company’s pipeline is planning to or has already replaced their existing legacy systems entirely with Ultralight. Clinician Impact: Users save hours every week, reclaiming their personal time and, most importantly, rediscovering the joy of practicing medicine.
The AI Arms Race: Why PHTI Warns Healthcare ‘Bot Wars’ Are Inflating Medical Costs
What You Should Know: – A newly released report from the Peterson Health Technology Institute finds that while AI is reducing administrative burden for individual organizations, it is not lowering system-wide costs—and may, in fact, be increasing them. – The reason: AI is accelerating activity across the system—more prior authorization submissions, more billing complexity, and ... Read More
<img loading="lazy" width="811" height="952" src="https://hitconsultant.net/wp-content/uploads/2026/04/PHTI-Report.jpg" alt="" class="wp-image-95750" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/PHTI-Report.jpg 811w, https://hitconsultant.net/wp-content/uploads/2026/04/PHTI-Report-256x300.jpg 256w, https://hitconsultant.net/wp-content/uploads/2026/04/PHTI-Report-247x290.jpg 247w, https://hitconsultant.net/wp-content/uploads/2026/04/PHTI-Report-768x902.jpg 768w" sizes="(max-width: 811px) 100vw, 811px" /> What You Should Know: – A newly released report from the Peterson Health Technology Institute finds that while AI is reducing administrative burden for individual organizations, it is not lowering system-wide costs—and may, in fact, be increasing them. – The reason: AI is accelerating activity across the system—more prior authorization submissions, more billing complexity, and more back-and-forth between providers and payers—without fixing the underlying structural inefficiencies. The Prior Authorization “Bot War” Prior authorization is a significant source of friction, with each submission cycle costing health plans $40–$50 and providers $20–$30. While AI is being deployed to automate these tasks, it has yet to reduce overall system-level costs. Increased Activity, Not Efficiency: AI allows providers to submit more requests and plans to process more denials, leading to “bot wars”—automated back-and-forth exchanges that increase communication volume without resolving the underlying clinical questions. The Scalability Gap: Emerging real-time adjudication models aim to approve requests during a patient visit, but these proofs of concept remain narrow and difficult to scale due to fragmented medical policies across different health plans. Standardization Limits: While new rules like CMS-0057-F mandate data standards for APIs, they do not standardize the actual medical necessity criteria, which vary wildly between insurers. Medical Billing and the Risk of Inflation In medical billing, AI-enabled ambient scribes are becoming standard, with all large health systems in a recent survey reporting their adoption. However, the primary result has been increased billing intensity. Coding Intensity: AI tools capture clinical complexity more thoroughly, leading to a higher proportion of visits being coded at higher levels. One system saw a 5% increase in Level 5 encounters after deploying AI scribes, raising revenue by over $1,000 per provider per month. Payer Retaliation: Health plans are responding with automated “downcoding” and reimbursement reductions, which may disproportionately harm smaller or rural providers who haven’t adopted AI tools. Cost Shift to Patients: This “AI arms race” threatens to increase patient cost-sharing and annual premiums as total medical expenditures rise. For more inforamtion about the report, visit https://phti.org/administrative-ai-current-use-and-potential-impact/
ModMed Expands Multi-Year Cloud Agreement with AWS to Scale Healthcare AI Solutions
What You Should Know ModMed, a massive provider of specialty-specific EHRs, has signed a new multi-year agreement with Amazon Web Services (AWS). AWS has been ModMed’s primary cloud provider since its inception, but this expanded agreement specifically designates AWS as the engine for ModMed’s “AI-Powered Practice” initiative. The Clinical Vision The goal of the expanded ... Read More
<img loading="lazy" width="1500" height="431" src="https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-1500x431.jpeg" alt="ModMed Launches AI-Powered Enhanced Faxing for EMA®, Reducing Admin Time by 80%" class="wp-image-90677" srcset="https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-1500x431.jpeg 1500w, https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-300x86.jpeg 300w, https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-290x83.jpeg 290w, https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-768x221.jpeg 768w, https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-1536x441.jpeg 1536w, https://hitconsultant.net/wp-content/uploads/2025/08/IMG_4685-2048x589.jpeg 2048w" sizes="(max-width: 1500px) 100vw, 1500px" /> What You Should Know ModMed, a massive provider of specialty-specific EHRs, has signed a new multi-year agreement with Amazon Web Services (AWS). AWS has been ModMed’s primary cloud provider since its inception, but this expanded agreement specifically designates AWS as the engine for ModMed’s “AI-Powered Practice” initiative. The Clinical Vision The goal of the expanded partnership is to embed AI—such as the generative AI tool ModMed Scribe 2.0—into every corner of a specialty medical practice, including clinical documentation, billing, front-office operations, and patient engagement. When a dermatologist or an ophthalmologist uses an ambient listening tool like ModMed Scribe 2.0, that audio must be instantly processed, securely analyzed, mapped to the correct medical codes, and inserted into the EHR without a second of latency. Multiply that action across nearly 50,000 providers. Supported by AWS, ModMed’s architecture is now processing over 3 petabytes of data each month. This translates to over 107 million hours of cluster processing monthly, handling hundreds of millions of clinical notes, patient messages, and practice performance metrics. “In healthcare, providers need technology they can trust to deliver continuous patient care,” said Venk “VJ” Jayaraman, Chief Technology Officer at ModMed. “To build the AI-Powered Practice, we needed a cloud infrastructure partner that exceeded our requirements for massive scale and technical leadership. AWS met and exceeded every one of those needs.”
symplr Appoints Former Edifecs Executive Venkat Kavarthapu as CEO
What You Should Know The Appointment: Enterprise healthcare operations software giant symplr has appointed Venkat Kavarthapu as its new Chief Executive Officer, effective immediately. The Leadership Transition: Kavarthapu succeeds Chris Colpitts, who had been serving as interim CEO since November 2025. Colpitts will remain heavily involved, maintaining his role as Executive Chairman of the Board. ... Read More
<img loading="lazy" width="400" height="402" src="https://hitconsultant.net/wp-content/uploads/2026/04/Venkat-Kavarthapu-Hex.png" alt="symplr Appoints Former Edifecs Executive Venkat Kavarthapu as CEO" class="wp-image-95743" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Venkat-Kavarthapu-Hex.png 400w, https://hitconsultant.net/wp-content/uploads/2026/04/Venkat-Kavarthapu-Hex-290x290.png 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Venkat-Kavarthapu-Hex-100x100.png 100w" sizes="(max-width: 400px) 100vw, 400px" /> Venkat Kavarthapu, CEO at symplr What You Should Know The Appointment: Enterprise healthcare operations software giant symplr has appointed Venkat Kavarthapu as its new Chief Executive Officer, effective immediately. The Leadership Transition: Kavarthapu succeeds Chris Colpitts, who had been serving as interim CEO since November 2025. Colpitts will remain heavily involved, maintaining his role as Executive Chairman of the Board. Kavarthapu Background Kavarthapu is a 25-year veteran of health-tech, but he most recently served as the CEO of Edifecs, a major interoperability and health data management platform. He didn’t just scale Edifecs; he successfully shepherded the company through its high-profile acquisition by Cotiviti in 2025. He proved he can navigate complex enterprise integrations while delivering massive financial returns for his backers. “Venkat’s success in scaling healthcare technology platforms and delivering practical, data-driven innovation makes him the right leader to drive symplr’s new phase of growth,” noted Prashant Mehrotra (Clearlake) and Ryan Carroll (Charlesbank) in a joint statement. Backed by private equity heavyweights Clearlake Capital Group and Charlesbank Capital Partners, Kavarthapu’s primary mandate is to scale symplr’s adoption and aggressively push “AI-powered innovation” across its massive customer base.
The Push for Side-by-Side Prescription Pricing in EHR Workflows
Lathe Bigler, SVP, Business Strategy, Buzz Health
Prescribing has evolved into a financial decision as much as a clinical one. As a result, one of the most consequential access moments is now occurring inside the electronic health record (EHR) during the prescribing workflow, when cost information surfaces and treatment decisions are finalized. As affordability pressures intensify across commercial, Medicare, and Medicaid populations, ... Read More
<img loading="lazy" width="1182" height="665" src="https://hitconsultant.net/wp-content/uploads/2026/04/Lathe-Bigler.jpeg" alt="The Push for Side-by-Side Prescription Pricing in EHR Workflows" class="wp-image-95727" srcset="https://hitconsultant.net/wp-content/uploads/2026/04/Lathe-Bigler.jpeg 1182w, https://hitconsultant.net/wp-content/uploads/2026/04/Lathe-Bigler-300x169.jpeg 300w, https://hitconsultant.net/wp-content/uploads/2026/04/Lathe-Bigler-290x163.jpeg 290w, https://hitconsultant.net/wp-content/uploads/2026/04/Lathe-Bigler-768x432.jpeg 768w" sizes="(max-width: 1182px) 100vw, 1182px" /> Lathe Bigler, SVP, Business Strategy, Buzz Health Prescribing has evolved into a financial decision as much as a clinical one. As a result, one of the most consequential access moments is now occurring inside the electronic health record (EHR) during the prescribing workflow, when cost information surfaces and treatment decisions are finalized. As affordability pressures intensify across commercial, Medicare, and Medicaid populations, patient out-of-pocket costs have become a primary driver of whether therapy is initiated or abandoned. Our recent survey of prescribers and technology leaders revealed how deeply the affordability discussion is influencing prescribing decisions. Pricing information is increasingly visible at the point of prescribing, yet fulfillment outcomes remain uncertain. That disconnect carries implications for adherence, pharmacy operations, and overall healthcare costs. Prioritizing Cost Discussions Medication cost is no longer a secondary consideration for patients. In the survey, 75% of prescribers report that potential out-of-pocket spending is a major or moderate barrier to patients starting or continuing therapy. Cost conversations are frequent: 77.2% of prescribers report being asked about medication expenses weekly or more often during patient visits. These figures indicate that affordability pressures are now a structural feature of clinical care. Treatment selection increasingly depends on what patients, both with and without drug benefits, can afford in real time. When pricing is a concern for patients, either due to lack of coverage or high cost-sharing requirements, prescribers reported responding in numerous ways, such as searching for discount/cash options, exploring alternative medications, cancelling the prescription, or referring to the pharmacy. These patterns point to the need for integrated, real-time comparison and alternative pricing options for patients with varying coverage levels, operating within existing prescribing workflows and providing closed-loop insight into whether prescriptions are ultimately filled. Such insight would certainly save prescribers time while improving patients’ access to needed medications. Abandonment Persists When affordability concerns are raised, more than half (54%) of prescribers report that patients very often or often fail to start prescribed medications, a finding that echoes a recent healthcare affordability report. Yet despite its importance, visibility into this cost-related abandonment is limited. Only 17.1% describe fulfillment data as “highly visible” in their current workflows. As a result, prescriber insights into adherence behaviors are limited. Prescriptions are written with some level of price awareness, but few prescribers are certain that the patient paid that amount. In many organizations, non-covered scripts migrate into discount or cash pathways without comprehensive reporting back into clinical or benefit systems. That fragmentation makes it difficult to measure the true impact of affordability initiatives or to understand patient or health-plan member behavior across covered and non-covered channels. Comparative Pricing Drives Confidence Fortunately, most prescribers already receive some form of price information in their electronic prescribing workflow. In the survey, 77.1% report seeing medication pricing in the EHR. However, usefulness varies significantly depending on how that information is presented. For example, 79% of prescribers rate pricing as useful when patient out-of-pocket costs for both insurance and discount options are visible together, compared with lower usefulness ratings for either pathway alone. Similarly, 94% say that viewing insurance-based and discount or cash pricing side by side would be extremely or very valuable. These responses suggest that comparative visibility can be a powerful driver of adherence rather than a convenience feature, which means prescribers need clarity on which option is most likely to result in a filled prescription. A single price, even if accurate, does not fully answer that question when coverage restrictions, prior authorization requirements, or step-therapy barriers are present. Overcoming Friction When patients’ drug benefit plans indicate non-coverage or utilization management requirements, prescribers tend to seek immediate alternatives. In those scenarios, 63.6% report seeking a discount or a cash option. EHR workflow owners similarly observe that discounted or cash pricing is more often selected when both insurance and discount options are available. This behavior reflects practical realities. Time constraints within the clinical encounter limit the ability to navigate complex benefit structures. Predictable pricing that can be acted on immediately often prevails over options that introduce uncertainty or delay. For healthcare organizations, this trend underscores the importance of embedding affordability pathways directly into existing workflows. Real-time benefit pricing, along with configurable discount options, increases the likelihood that a prescription selected during the visit will be affordable and filled. When these capabilities can also route transactions through the most appropriate channel without requiring manual intervention, they help resolve cost concerns and save time within the existing workflow. From Visibility to Resolution Survey results also show that price comparisons often occur outside the structured visit. Only 34.3% report that price comparison most often happens during the visit within the EHR. In many cases, staff follow up, or patients independently search for lower-cost options after the encounter. Each additional handoff introduces friction. Delays increase the risk that prescriptions go unfilled. Fragmented workflows also complicate reporting, as prescriptions filled through discount networks may not be consistently captured in traditional benefit analytics. A more resilient affordability strategy focuses on resolving cost questions at the point of prescribing and maintaining visibility through adjudication and reporting. For example, configurable comparison tools that present insurance copays alongside multiple eligible discount prices within a single view can help clarify the best available option in real time. At the same time, automated wrap capabilities that activate when medications are not covered can reduce manual overrides and minimize patient confusion. Behind the scenes, secure adjudication platforms and API-based integrations can support real-time decisioning while enabling closed-loop reporting across both covered and cash transactions. Achieving Certainty Given the increasing financial pressures facing patients, the objective for prescribers and EHR workflow owners is to move beyond price transparency toward cost certainty. Transparency informs decision-making, but certainty increases the likelihood of initiation. When affordability information is embedded within the prescribing and fulfillment journey, supported by enterprise-grade security and configurable logic, organizations gain clearer insight into patient behavior and stronger alignment between clinical intent and financial reality. Affordability is already shaping therapy decisions and will likely continue to do so for the foreseeable future. The next phase of innovation in the prescribing journey will be to ensure that prescriptions written in the EHR are indeed filled and supported by the data infrastructure to understand and improve patient outcomes and experiences. About Lathe Bigler Lathe Bigler is SVP, Business Strategy of Buzz Health. Lathe Bigler is a seasoned healthcare technology executive with nearly three decades of experience driving strategic partnerships, clinical workflow innovation, and drug price transparency across digital health and e-prescribing ecosystems. He is currently leading strategic growth efforts at Buzz Health after steering mission-critical clinical network services and interoperability platforms in the industry.