What You Should Know: 

– CentralReach, the leading provider of Autism and IDD Care Software for ABA and multidisciplinary organizations, unveiled CR ClaimCheckAI, an artificial intelligence solution designed to streamline and revolutionize the claims process.

– With the launch of CR ClaimCheckAI, CentralReach continues its mission to empower healthcare providers with powerful, user-friendly tools that seamlessly integrate into daily workflows. 

Transforming Accuracy, Compliance, and Speed

CR ClaimCheckAI stands out as the industry’s first fully-integrated, proprietary AI solution for claims management. It empowers providers with:

• Enhanced Accuracy: Automatic analysis of claims against payer rules and comprehensive compliance checks minimize errors and denials.
• Improved Speed: Submission times are accelerated by automatically fixing common issues like mismatched names, locations, and service times.
• Boosted Compliance: Pre-submission quarantining of non-compliant claims allows for corrections before submission, reducing audit risk.

Optimizing the Entire Workflow

Unlike third-party solutions, CR ClaimCheckAI seamlessly integrates within the CentralReach platform, eliminating the need for:

• Logging into separate systems
• Transferring files
• Performing cumbersome manual tasks

This streamlined approach empowers providers to:

• Reduce Administrative Burden: Automatic error correction frees up valuable staff time for patient care.
• Increase Clean Claim Rates: Fewer errors lead to faster reimbursements and improved cash flow.
• Minimize Audit Risk: Proactive compliance checks ensure claims meet regulatory standards.

A Significant Leap Forward

Traditionally, many autism and IDD care providers struggled with limited resources for claims review. Manual checks often covered only 5-10% of claims, leaving a significant portion vulnerable to errors and delays.

CR ClaimCheckAI addresses this challenge by:

• Automating Comprehensive Reviews: AI analyzes every claim in seconds, a task requiring multiple full-time staff members traditionally.
• Prioritizing Accuracy: Complete claim reviews ensure all submissions meet payer and regulatory requirements.

High Demand for Groundbreaking Solution

Due to the immense demand for CR ClaimCheckAI, access is currently waitlisted. Providers are encouraged to sign up today to secure their spot.

“With increasing compliance mandates and payer scrutiny, improving claims performance is top of mind for all providers in the Autism and IDD Care market. Current solutions like ad hoc manual checks or  the use of clunky, disconnected 3^rd party tools do not enable providers to materially improve performance without significant manual processing that they can ill afford to do. CR ClaimCheckAI solves these issues and represents a significant leap forward in our commitment to leveraging technology to improve healthcare administration,” said Chris Sullens, CEO of CentralReach. “By fixing a multitude of issues automatically and embedding the quarantine process within a provider’s current workflow, CR ClaimCheckAI will greatly enhance clean claims rates from the outset, accelerate reimbursements, and reduce operational burdens, that will in turn allow providers to scale their services faster and more effectively. It’s the first step toward our vision of creating the only fully integrated real time clean claims workflow in the industry, so stay tuned for more enhancements in the coming year.”  

What You Should Know: 

– Blue Earth Diagnostics, a Bracco company and leader in innovative PET radiopharmaceuticals, announced a data-sharing agreement with Siemens Healthineers. 

– This collaboration focuses on anonymized data from Blue Earth’s Phase 3 LIGHTHOUSE trial of POSLUMA® (flotufolastat F 18) injection, used for imaging prostate cancer.

Optimizing AI for Improved Prostate Cancer Detection

Siemens Healthineers will leverage the anonymized clinical data and images from the LIGHTHOUSE trial to enhance its AI-powered analytics for prostate cancer. This will lead to:

• More Precise Image Quantification: AI algorithms will be refined to provide more accurate measurement of prostate cancer lesions detected by POSLUMA PET scans.
• Enhanced Image Interpretation: Advanced AI tools will be developed to assist healthcare professionals in interpreting PET scans, potentially leading to earlier and more precise diagnoses.

About POSLUMA®

POSLUMA, previously known as 18F-rhPSMA-7.3, is a recently approved radiopharmaceutical for PET imaging of prostate cancer. It targets the Prostate-Specific Membrane Antigen (PSMA), a protein often overexpressed by prostate cancer cells. This targeted approach allows for more effective detection of prostate cancer compared to traditional imaging methods.

Details of the LIGHTHOUSE Trial

The LIGHTHOUSE trial was a large-scale clinical study involving over 350 men with newly diagnosed prostate cancer. It evaluated the safety and effectiveness of POSLUMA PET imaging in identifying prostate cancer lesions.

Blue Earth Diagnostics: A Leader in rhPSMA Technology

Blue Earth Diagnostics holds exclusive worldwide rights to the radiohybrid Prostate-Specific Membrane Antigen (rhPSMA) diagnostic imaging technology. This technology has the potential to revolutionize prostate cancer diagnosis and treatment.

“Blue Earth Diagnostics is committed to helping men with prostate cancer across the care continuum, and we recognize the importance of AI in advancing healthcare,” said David Gauden, D.Phil., Chief Executive Officer, Blue Earth Diagnostics. “AI-based algorithms have the potential to streamline the PET/CT analytical workflow for hospitals and imaging centers by efficiently providing physicians with information critical to patient management and care. Blue Earth Diagnostics has a long-standing relationship with Siemens Healthineers, a leading medical technology company pioneering breakthroughs in healthcare.”

What You Should Know: 

– Rad AI, a leader in generative AI for healthcare, announced today it has raised $50M in Series B financing, bridging its total capital raised to over $80M. 

– The round was led by Khosla Ventures, with participation from prominent investors including WiL (World Innovation Lab), ARTIS Ventures, OCV Partners, Kickstart Fund, and Gradient Ventures (Google’s AI-focused fund).

Revolutionizing Radiology Reporting

Rad AI’s solutions are already making waves in the healthcare industry. Used by over a third of US health systems and 9 of the 10 largest radiology practices, their technology saves physicians significant time and improves patient care.

Pioneering generative AI in healthcare since 2018, Rad AI automates report generation, allowing radiologists to customize reports with their own language and style. This frees them from the burden of dictation, a task that consumes 75% of their time, often for reports on over 100 patients daily.

Leading the Way in AI-powered Reporting

Today, Rad AI offers cutting-edge solutions like Rad AI Reporting, the industry’s leading AI-powered tool for radiology reporting workflow. Additionally, Rad AI Continuity simplifies patient follow-up, with adoption by many of the nation’s largest health systems. Combined, these solutions positively impact nearly 50 million patients annually.

Reduced Burnout, Improved Care

Rad AI’s AI models take over repetitive tasks like dictation and follow-up management. This frees up valuable time for physicians, reduces burnout, and allows them to focus on what matters most – providing exceptional patient care. Hospitals using Rad AI’s solutions have seen:

• A dramatic increase (from 30% to over 85%) in patient follow-up rates for critical findings, ensuring timely diagnoses and treatment, especially for new cancers.
• Doubled report creation speed, often with a 90% reduction in dictated words, leading to less fatigue and burnout for radiologists.
• A near 50% reduction in report errors for complex cases, ultimately improving the quality of care provided.

“At Rad AI, we’ve built the most widely adopted generative AI solutions in healthcare, saving physicians time and improving patient care. Rad AI has become a mission-critical part of health system workflows over the past five years. This strategic funding round further cements our position as the leading AI-driven workflow platform in healthcare.”-Doktor Gurson, co-founder and CEO of Rad AI

What You Should Know: 

– BrightInsight, Inc., a provider of compliant digital health solutions, today announced its collaboration with Google Cloud to leverage cutting-edge generative AI (gen AI) technology. 

– The enhanced partnership aims to optimize BrightInsight’s research and development efforts and significantly enhance its Disease Management Solution for both patients and healthcare providers.

Addressing Challenges in the Patient Journey

Across various therapeutic areas, patients often face hurdles throughout their treatment journey. These challenges include navigating access and financial barriers, transitioning between treatment options, managing complex treatment schedules, and tracking symptoms and treatment effectiveness.

Improving Patient Education and Support with AI

BrightInsight is tackling these challenges head-on by integrating Google Cloud’s Gemini and MedLM gen AI models within its Disease Management Solution. This integration offers several key benefits:

• AI-powered Chatbot: A chatbot powered by Gemini provides patients with improved access to approved educational content. Patients can receive immediate answers to their questions by leveraging a vast library of clinically validated information, eliminating the need to search through multiple documents.
• Enhanced Patient Support: The chatbot also serves as a first-line support system, offering quick and specific answers to patient inquiries regarding app usage.

Optimizing BrightInsight’s Internal Operations

BrightInsight is also utilizing Gemini Code Assist to streamline its internal R&D processes in three ways:

• Developing and Operating Google Cloud Components: Gemini Code Assist helps BrightInsight’s development team work more efficiently when building and managing Google Cloud components.
• Improved Troubleshooting: The technology assists in troubleshooting issues more effectively, saving valuable time and resources.
• Enhanced Analytics and Insights: By leveraging gen AI, BrightInsight can generate more insightful data analytics for its customers.

Leveraging MedLM for Improved Patient Data Management

Furthermore, BrightInsight is utilizing MedLM to summarize, analyze, and make patient data from companion apps more usable for clinicians. This allows for more impactful and data-driven conversations between patients and providers. For example, healthcare professionals can quickly identify missed medication doses or abnormal readings, enabling them to have focused discussions with their patients.

Prioritizing Security and Compliance

As BrightInsight advances its gen AI-based solutions, the company remains steadfastly committed to responsible implementation. Their platform and Disease Management Solution adhere to the highest security, privacy, and compliance standards, achieving certifications against global regulations. The integration of AI will follow the same rigorous approach, ensuring patient data protection.

“We have invested a lot in building best-in-class technology and hiring top engineering talent,” said Ashish Agrawal, chief technology officer, BrightInsight. “Partnering with Google Cloud and leveraging its AI technologies will enable BrightInsight to supercharge its solutions to achieve our vision of transforming patient outcomes through digital technologies.”

What You Should Know:

–              Suki, the leader in voice artificial intelligence (AI) technology for healthcare, today announced it has been awarded a national group purchasing agreement for AI scribes with Premier, Inc.

–              Effective May 1, 2024, the new agreement allows Premier members, at their discretion, to take advantage of special pricing and terms for Suki pre-negotiated by Premier for AI scribes.  

Empowering Premier Members: Introducing Suki Assistant for Streamlined Clinical Documentation

Premier members now have access to Suki Assistant, an AI-powered tool designed to alleviate administrative burdens for clinicians. Utilizing generative AI technology, Suki passively listens to conversations between patients and clinicians, automatically drafting clinical notes. Additionally, it simplifies other time-consuming tasks such as ICD-10 and HCC coding, providing answers to queries, and facilitating dictation. Suki seamlessly integrates with major EHR systems like Epic, Cerner, Meditech, and Athena, ensuring support for all documentation workflows by synchronizing note content in real-time. Clinicians have the flexibility to either pre-chart within the EHR and finalize notes with Suki or commence note-taking with Suki and incorporate pertinent information, such as vitals, from the EHR. Upon completion, the note content is transmitted back to the EHR, updating relevant sections accordingly. On average, clinicians complete notes 72 percent faster with Suki, while health systems witness up to 9X ROI due to enhanced efficiency, increased reimbursements facilitated by detailed documentation, and heightened encounter volumes, among other benefits.

Premier stands as a prominent healthcare improvement organization, bringing together an alliance of approximately 4,350 U.S. hospitals and 300,000 other providers to revolutionize healthcare delivery. Through integrated data and analytics, collaborative efforts, supply chain solutions, consulting services, and more, Premier facilitates superior care and outcomes at reduced costs. The provider selection process at Premier is rigorous, evaluating candidates based on various criteria including quality, capacity to deliver value, and the level of service and support offered.

This announcement marks the latest in a series of achievements and partnerships that solidify Suki’s position as a leader in the AI assistant category. Notably, Suki received a remarkable rating of 93.2/100 in a KLAS assessment and has established collaborations with industry leaders such as Amwell and MEDITECH. Currently deployed across 30+ specialties and all clinical settings, including ambulatory care, telehealth, skilled nursing facilities/home health, and inpatient facilities, Suki continues to expand its reach and impact.

“We are thrilled to work with Premier as their exclusive solution for AI scribes,” said Heather Miller, VP of Partnerships for Suki. “Premier’s mission to improve the health of communities is very much aligned with Suki’s goal of making healthcare technology invisible and assistive so clinicians can focus on what matters most: their patients.  We look forward to helping Premier’s members reduce their administrative burden with the quality and value they expect from Premier-selected solutions.”

What You Should Know: 

– ARC Innovation, the innovation arm of Sheba Medical Center, Israel’s leading medical center and a six-time Newsweek World’s Best Hospital awardee, today announced its participation in the Trustworthy & Responsible AI Network (TRAIN). 

– The consortium brings together healthcare luminaries dedicated to integrating responsible AI practices effectively within the healthcare landscape.

AI Transforming Healthcare Landscape

AI is rapidly transforming healthcare, impacting everything from patient education and support to diagnostics, precision medicine, clinical decision-making, and drug development. However, as AI becomes increasingly pervasive, so too does the need for robust guidelines and standards to ensure its responsible and impactful use.

TRAIN: A Collaborative Effort for Responsible AI Implementation

The Trustworthy & Responsible AI Network (TRAIN) was unveiled at the recent HIMSS Global Health Conference. This consortium unites leading academic healthcare institutions, health systems, and technology providers such as Duke Health, Vanderbilt University Medical Center, Microsoft, and ARC Innovation at Sheba Medical Center. By working collaboratively, TRAIN seeks to establish a framework for the responsible use of AI in healthcare, ensuring patient safety, ethical considerations, and optimal clinical outcomes.

“AI is a transforming force within healthcare, with new solutions developed daily, bringing considerable benefits to every aspect of health,” said Professor Eyal Zimlichman, MD, Chief Innovation and Transformation Officer at Sheba Medical Center and Founder and Director of ARC Innovation. “In order to effectively implement AI technologies, innovation must be balanced with responsibility and trust. AI cannot be implemented without safeguards, and only through rigorous quality and safety controls can health systems adopt these new solutions.”

TRAIN members will collaborate to enhance the quality and reliability of AI in healthcare by sharing best practices, enabling registration of AI used for clinical care through a secure online portal, and providing resources for assessing outcomes of AI implementation, while ensuring privacy preservation throughout the deployment phases. The consortium will also support the establishment of a federated national AI outcomes registry to document real-world results concerning algorithm effectiveness, safety, and refinement.

When it comes to the patient experience, time isn’t on our side. U.S. adults spend the equivalent of an entire workday each month coordinating care for themselves and/or their family, according to a Harris poll. The same poll found that 56% of American adults wait more than a week for an appointment, while many others skip healthcare altogether, with 30% saying they don’t have the time and 25% saying it takes too long to get an appointment. Even when patients get an appointment, they wait again (in the waiting room, exam room, and to be checked out) which affect patient satisfaction scores.

The good news is that AI tools are ready to make significant improvements to the patient experience, especially when it comes to giving patients and clinicians their time back. Doing so increases access and leads to better healthcare experiences and outcomes. For providers, better patient experiences also mean higher productivity and improved performance metrics, thanks in part to a 2020 rule from CMS that links the quality of the patient experience with reimbursement. But in order to understand how best to deploy AI tools, we first need to discuss the barriers to care.

What’s standing in the way?

The healthcare system is facing a “perfect storm” of increased demand for services, a workforce shortage, a burned-out labor pool, and rising costs. Healthcare providers are also producing, managing and consuming more data than they ever have before. Today, healthcare data makes up 30% of the world’s data volume, which is impossible for physicians, nurses, clinical assistants and other industry professionals to handle with paper or spreadsheet-based processes. The trillion-dollar US health care industry won’t be able to simply throw people and money at the problem. Instead, the industry needs to use AI and other technologies to do more with less.

On the demand side, the U.S. has an aging population. According to the Office of Disease Prevention and Health Promotion, people age 65 years and older made up 17 percent of the population in 2020, but by 2040 that number is expected to grow to 22 percent, increasing demand for healthcare services. An aging population also impacts the supply of healthcare services. According to the American Nurses Association, nurses are retiring faster than new nurses can be trained. Meanwhile, an aging physician population, along with burnout from the pandemic, prompted the AMA to declare, “the physician shortage crisis is here.” Worse, these supply and demand challenges are further exacerbated by rising healthcare costs. According to a PwC report, in 2024 the industry is facing a 7% year-over-year cost increase, up from 5.5% and 6% in 2022 and 2023, respectively. In addition, more patients are searching for value-based care, which requires healthcare providers to spend more time managing patients proactively, instead of reacting once there is a problem that needs to be addressed. With these combined challenges, it’s no wonder healthcare workers are pressed for time, more stressed and retiring early.

But while this perfect storm undermines the ability to deliver great patient experiences, physicians and healthcare systems also have to consider the challenges around consumer expectations. The paradigm shift is also here, patients are now consumers of healthcare services and demand the same service and attention they get from other industries along with empathy, sympathy and precision medicine. They expect omnichannel communications that flow seamlessly between text, email, and in-person visits. This includes timely responses and status updates, as well as always-on customer service. In other words, patients expect healthcare experiences to mirror the digital experiences encountered everywhere else in their busy lives. But that expectation isn’t being met, according to the Harris poll, which found that 65% of respondents said coordinating and managing healthcare is “overwhelming” and “time-consuming.” 

How AI tools can improve the patient experience

While it’s tempting to think about the futuristic aspects of AI, it’s important to ground any discussion of AI tools in the here and now in order to improve the patient experience. It’s important to use AI tools as a supplement, not a replacement, for human interaction. After all, the goal is to free up time to focus on people and communicate in a timely manner. A Journal of Public Health article is instructive. The authors identified a range of factors that influence patient experience, then grouped them into three interconnected themes:

• Providing safe, timely, and effective treatment 
• Fostering human connections with caring and attentive staff
• Providing a comfortable and healing environment   

Broadly speaking, healthcare providers should measure every AI tool against the impact it has on one or more of these themes. But, for the sake of clarity, let’s address three situations where AI can return time to patients and providers: when accessing care, during provider visits, and after the visit. 

Access

AI tools are especially promising here because so many of the things support staff do to move patients through the system, like scheduling and providing standardized instructions, are ripe for automation. This approach to administrative activities frees up time for physicians to provide value-based proactive, rather than reactive, care.

In fact, automated communication tools that can benefit from AI upgrades are already in use. Improvements to scheduling, routing patients to the correct provider, and instructing patients on what they need to do to prepare for routine procedures, like colonoscopies, are all within our reach. 

If deployed thoughtfully, these tools can super-charge support staff by freeing them up to address specific non-routine issues. But remember, these AI chat tools need to be safe, which means they must be trained on approved, evidence-based data sets, rather than the open web. Moreover, AI-driven communication solutions need to personable, helpful, and easy to use in order to make the best use of a patient’s time.

The visit

Consider an AI tool most doctors are probably already familiar with: transcription. Obviously, an AI transcription tool needs to be HIPAA compliant, but it also needs to make patients feel like their privacy is of the utmost concern. In other words, patients need to be able to trust AI tools as much as they trust the providers who use them. 

How does AI transcription improve the patient experience? Transcription frees up doctors and nurses to spend more time with their patients and sufficiently explain new treatments, the latest test results and other key details. But it’s not just about having more time, it’s about creating quality time when doctors are able to focus on the patient, not the chart. Moreover, an AI tool can integrate communications from other channels (phone, email, text, etc.) into in-person visits, so that providers have the full picture and patients feel listened to, without needing to repeat themselves. 

These kinds of tools also have a positive impact on the healthcare system because AI transcription decreases routine work for providers and administrative staff. AI as the adjunctive faculty takes barriers to care and turns them into improved quality, value, informed decisions and satisfaction. With those extra hours, providers can see additional patients, improving both access and quality of care for everyone. 

After the visit

AI tools can also make a big difference for patients after they leave the doctor’s office or hospital. Currently, providing patients with discharge instructions or instructions for medication is time-consuming, impersonal, and insufficient. Anecdotally, patients see this whenever a prescription is filled at the pharmacy, waiting around for an overworked pharmacist to read us boilerplate instructions. If the patient doesn’t have any questions, it’s just a waste of time and money. But if patients do have questions, it’s often difficult to get timely answers. An AI tool that walks patients through these kinds of instructions on their own time, with accurate information pulled from doctor-approved sources, would be more efficient and cost effective. 

AI also provides a more personal experience because it has unlimited time to repeat instructions and provide answers to follow-up questions that deal with relevant patient information. For example, 87% of hospitals report using pre-translated discharge instructions for patients who don’t speak English. That means non-English speakers are denied the opportunity for personalized discharge instructions. An AI tool could quickly and cost-effectively translate a provider’s personalized discharge instructions, as well as translate question responses, for millions of Americans who cannot access care in their preferred language.

AI Creates the Patient Experience Demanded Today

AI will transform healthcare, but as technology leaders think about next steps, it’s critical to use these tools to provide care that meets today’s patient expectations for quality. Prioritizing personalization that scales to meet rising demand should be the foremost priority. Likewise, healthcare providers need always-on communications tools to expand access to patients who don’t have the time to navigate the current system. Finally, the industry must prioritize AI tools that reduce costs so that human healthcare providers aren’t seen as bottlenecks in a bureaucracy, but instead as trusted and compassionate healers.  

About Michael Zacharski

Michael Zacharski, CEO of Brand Engagement Network (BEN), is a seasoned executive with 20+ years of experience driving growth and innovation in the technology industry. Throughout his career, he has founded and operated multiple businesses, contributing to various utility patents that underpin advertising technology and omnichannel communications. He holds a bachelor’s degree from New York University.

What You Should Know: 

– RapidAI, a global leader in AI-powered solutions for combating life-threatening vascular diseases, announced today the FDA 510(k) clearance for its innovative AngioFlow™ by RapidAI solution. 

– The technology empowers interventional care teams with real-time, AI-driven insights directly within the interventional suite, aiming to improve patient outcomes for stroke and other vascular emergencies.

Faster, More Informed Decisions in Stroke Care

Stroke is a time-sensitive medical emergency where rapid intervention is crucial for minimizing brain damage and long-term disability. AngioFlow™ by RapidAI addresses this critical need by leveraging validated deep learning AI to generate clear, easy-to-understand perfusion maps within minutes. These maps visualize areas of reduced blood flow in the brain, allowing specialists to make faster and more informed decisions regarding treatment strategies.

Key Benefits of AngioFlow™ by RapidAI

• Improved Clinical Confidence: Real-time AI insights directly within the interventional suite enhance physician confidence during critical procedures.
• Enhanced Workflow Efficiency: Streamlines workflow by potentially reducing the need for redundant imaging, saving valuable time in patient care.
• Reduced Healthcare Costs: Minimizes unnecessary imaging, particularly beneficial in rural facilities and large hospital networks with long transfer times.
• Potentially Improved Patient Outcomes: Faster and more informed treatment decisions can lead to better patient outcomes.

Enhancing Vascular Care with AI

AngioFlow™ by RapidAI represents a significant leap forward in AI-powered solutions for vascular care. This innovative tool empowers healthcare professionals with real-time, actionable intelligence, enabling them to deliver the best possible care to stroke and other vascular disease patients.

“We are pleased to expand our stroke AI imaging portfolio, the broadest in the industry, to include this new module. With AngioFlow™ by RapidAI, we can now support stroke AI imaging along the entire patient pathway, from the initial non-contrast CT scan all the way to the interventional suite,” said Karim Karti, CEO of RapidAI. “Already registered and used in Japan and Europe, we believe this technology will make a significant difference in the lives of U.S. stroke patients.”

Though AI has successfully been utilized in healthcare for decades, a Pew Research Center survey revealed that 60% are uncomfortable with their provider relying on AI for their own healthcare. 

This dichotomy is therefore likely due in part to a lack of awareness and understanding around the technology. Before the public is forced to understand complex, revolutionary, future-state technological developments in healthcare, they must understand how the technology is safely used today.  Examples of this technology in motion include: 

• The pulse oximeter, also called a plethysmograph or pleth, uses AI to calculate blood oxygen saturation based on the difference in transmission of red and infrared light in pulsating blood. It was developed in 1972 and widely adopted in clinical practice in the 1980s and 1990s.
• The MRI (magnetic resonance imaging) scanner has been widely used and incorporated AI since the 1980s to detect conditions including brain tumors, multiple sclerosis, strokes, and infections. Modern AI applications for MRI can improve the speed and quality of scans and help with interpretation and diagnosis.
• The echocardiography machine, widely used with AI since the 1980s, uses sound waves to show how blood flows through the heart to search for heart conditions. According to this article in the Journal of Imaging, “Artificial intelligence can use raw echocardiography images/videos to automatically provide structural or functional measurements but also to identify disease states. This ability is based on AI’s capacity to automatically analyze features from images that may be too subtle to be detected by the human eye.”
• AI also can accurately identify normal and abnormal chest X-rays, according to this article and this study. 
• Other recent studies show that AI has a 100% success rate in spotting melanomas and a 20% better success rate than human radiologists in detecting breast cancer.

These are just a few of the many AI applications present in medical devices today. Each is an assistive technology that provides accurate measurements to health professionals, enabling them to chart the next steps more effectively. None of the technologies mentioned replace human jobs, but instead, enable healthcare professionals to be more accurate and efficient at their jobs, ensuring the best level of patient care possible. 

Beyond using AI for measurements and image interpretation, the next frontiers of AI in healthcare include information systems, some patient interaction, and even possibly robotic surgery. Here are some guidelines to help ensure accurate and safe AI deployments in new applications:

Start With The Back Office

In addition to developing patient-care applications, there is much that AI can do to help with time-consuming back-office administrative tasks that also improve patient care. These include:

• Clinical data abstraction: AI can be used as an assistive technology to automate painstaking and time-consuming data entry, with a required human in the loop to verify accuracy. This enables healthcare professionals to spend more time on patient care, and less on repetitive manual data entry. AI can also mine the hyperscale data sets of clinical registries and share anonymized treatment approaches including comorbidities and medical histories. This can help improve outcomes for current patients with similar conditions to those successfully treated in the past. 
• Drafts of clinical summaries: Generative AI systems such as GPT can save time by instantly creating drafts of clinical summaries, also called patient-visit or after-visit summaries, based on physicians’ notes. Generative AI correspondence is also a possibility, but like any AI application in healthcare, should never be sent directly to patients without human review, due to the possibility of inaccuracies or hallucinations.

Only Develop AI Applications That Can Access Sufficient Supporting Data

AI requires statistically significant data to operate; small data sets are insufficient for AI algorithms to be accurate. A condition or procedure that involves only 50 patients per year across the United States won’t provide enough data for AI to evaluate, compute a patient pathway or indicate whether, for example, a treatment is a normal or abnormal practice for the population with that condition. AI applications should operate on vast data sets and as wide a sample of the population as possible.

AI Applications for Patient Care Require Many Trials.

AI applications for patient care should not be immediately dismissed as too risky so that progress is not hampered. There are, however, potential quicker wins with back-office applications versus patient care applications (which generally require many trials before being put into practice). All patient-care AI applications should help clinical professionals do their job, as they are not equipped (and never will be) to replace them. Accuracy is paramount, and a human in the loop is essential to operate and interpret AI applications for patient care.

AI Is Not New

Although AI may be perceived as generally new, it was invented in the 1950s and has been included in software for medical devices since the 1970s. Almost all medical devices include AI software, except purely analog devices such as analog stethoscopes and hypodermic needles. If the public were more aware of facts like these, it is likely that some of the concerns regarding AI use in healthcare may subside. 

There currently is an explosion of interest and investment in AI, which is now featured in the marketing materials of most healthcare technology vendors. Before this “AI mania,” which was partially fueled by the launch of ChatGPT in November 2022, AI was usually simply called “software.”

About Matt Hollingsworth

Matt Hollingsworth is the co-founder of Carta Healthcare. His passion for improving patient care developed while helping his mother, a five-time cancer survivor, navigate the U.S. healthcare system and communicate her conditions to providers.

In 2017, Matt Hollingsworth founded Carta Healthcare, dedicated to creating a healthier future by advancing the technology surrounding data practices in healthcare. Today, Carta Healthcare is a leader in delivering improved data-gathering solutions to healthcare systems related to a patient’s diagnosis, treatment, and outcomes. Carta Healthcare’s solutions have revolutionized the processes surrounding registry databases, resulting in markedly faster data collection, superior quality of data, and considerable cost savings for healthcare providers.

Matt holds an MBA from Stanford University, where he also worked in the Systems Utilization Research for Stanford Medicine (SURF Stanford Medicine) lab, researching methods for using information technology to reduce equipment waste and improve patient care. It was through his work at Stanford that he and colleagues founded Carta Healthcare. Before receiving his MBA and founding Carta Healthcare, he was a researcher at CERN (Conseil Européen pour la Recherche Nucléaire) and a member of the team that discovered the Higgs boson, an important discovery in particle physics. Matt received bachelor’s and master’s degrees in physics from the University of Tennessee, Knoxville.

About Dr. Andrew Shin

Andrew Shin, MD, is an Associate Professor in the Division of Cardiology at Lucile Packard Children’s Hospital at Stanford University and the Executive Medical Director, Innovations & Clinical Effectiveness for Stanford Children’s Health. His research has leveraged microsystems, improvement science and high-reliability to better understand the intersection between the quality and efficiency of healthcare delivery. As the Medical Director for Systems Design for Utilization Research for Stanford (SURF MEDICINE), Dr. Shin translates his research to continuously improve the value of healthcare utilizing high-throughput advanced analytics such as machine learning and artificial intelligence. He completed his pediatric residency, along with a dual fellowship in pediatric cardiology and pediatric critical care at Boston Children’s Hospital. Dr. Shin is the Associate Medical Director for Cardiovascular Intensive Care Services and serves as a board member for Pediatric Congenital Heart Association, Carta Healthcare and as liaison for the American Heart Association’s Leadership Committee of the Council on Quality of Care and Outcomes Research.

What You Should Know:

–              Opmed.ai, the AI optimization platform for healthcare, announced today the successful raise of $15M in series A funding.

–              The round was co-led by NFX and Grove Ventures, with Secret Chord Ventures, the Impact investor Sir Ronald Cohen, and Unbox Ventures also participating

Revolutionizing Healthcare Efficiency: Opmed.ai’s AI-Powered OR Optimization Solutions

The funding announcement arrives amidst a critical shortage in healthcare labor, with projections indicating a deficit of 3.2 million healthcare professionals by 2026. Meanwhile, hospitals grapple with escalating labor costs, which surged beyond 20% last year. Operating Rooms (ORs) constitute a substantial portion, accounting for 40% of a hospital’s expenses while generating 60-70% of its revenue, often serving as the primary driver of profitability. Nonetheless, the inefficiencies in OR scheduling, facilitated through archaic spreadsheets or predominantly manual methods, compound these challenges.

Enter Opmed.ai, specializing in optimizing healthcare operations, with a primary focus on OR efficiency, leveraging advanced AI technology. The company’s optimization engine rapidly assesses billions of permutations, customized to forecast based on industry-specific variables, automatically generating alternative schedules that vastly enhance resource utilization. Considering that each idle minute potentially translates to revenue losses ranging from $50 to $150, with empty ORs incurring costs of $1,000 per unused hour, the impact of this technology is profound. By adopting Opmed.ai, hospitals stand to gain over $1 million per OR in additional revenue annually, while concurrently slashing costs by $500,000 and fortifying resilience against unforeseen disruptions.

Despite the intricate nature of ORs and healthcare environments at large, Opmed.ai boasts an implementation timeframe of merely two to four weeks. Once deployed, it identifies over and underestimations, addresses gaps, anesthesia durations, turnover times, and other pertinent factors, subsequently generating optimized alternative plans. These plans account for staffing, equipment, preferences, add-ons, and various other considerations, streamlining the process for scheduling professionals with just a few clicks. Moreover, the platform facilitates the creation of longer-term quarterly and yearly block allocation plans, driving OR utilization up by 10% and yielding compounded savings and revenue. Remarkably, the return on investment for hospitals typically materializes within a mere 3-4 months.

Founded by Dr. Mor Brokman Meltzer, Avi Paz, and Prof. Baruch Barzel, Opmed.ai presents an innovative healthcare optimization engine, harnessing AI and network science to revolutionize healthcare scheduling and resource allocation, commencing with operating rooms.

“Opmed.ai is a perfect representation of the next generation of great AI platforms. They solve a complex issue with a highly specialized vertical solution that has no alternative that comes close,” said Renana Ashkenazi, General Partner of Grove Ventures. “Adding to the attractiveness of the investment is the fact that the ROI is so clear and significant, even from an early stage. We’ve seen the millions of dollars it has saved and generated in hospitals where it’s already deployed, and as impressed as we were, the hospitals’ enthusiasm has been even greater. We look forward to helping the Opmed.ai team rapidly expand in both the hospitals and use cases they serve.”

What You Should Know: 

– Anatomy, a leading platform for automating financial operations in healthcare, today announced the launch of its innovative AI-powered Healthcare Lockbox. 

– This solution tackles a significant pain point for healthcare organizations by automating check digitization and converting Explanation of Benefits (EOBs) into standardized 835 electronic remittance advice documents.

The Problem of Manual Payments in Healthcare

Traditionally, processing healthcare payments involved a significant amount of manual effort. Anatomy reports that a staggering 27% of healthcare payments are still received and processed manually, a figure that has actually increased in recent years (up from 24% three years ago). This reliance on manual processes creates a bottleneck for healthcare organizations, leading to:

• Increased labor costs associated with data entry and check processing.
• Delays in cash flow due to slow processing times.
• Potential errors in data entry.

Anatomy’s AI-powered Solution

The Anatomy Healthcare Lockbox tackles these challenges head-on by leveraging the power of artificial intelligence. Here’s how it works:

• Automated Check Processing: Paper checks are securely digitized, eliminating the need for manual data entry.
• AI-powered EOB Conversion: Anatomy’s AI technology automatically converts Explanation of Benefits documents into standardized 835 electronic remittance advice documents (ERA).
• Streamlined Reconciliation: The system facilitates automated reconciliation, ensuring accuracy and minimizing errors.

Strategic Partnership with CheckAlt

To enhance its solution, Anatomy has partnered with CheckAlt, a recognized leader in secure and efficient lockbox solutions. This collaboration brings together Anatomy’s expertise in AI-powered data extraction with CheckAlt’s proven track record in check processing and HIPAA-compliant facilities.

Benefits for Healthcare Organizations

By automating the tasks associated with payment processing, the Anatomy Healthcare Lockbox offers a range of benefits for healthcare organizations, including:

• Reduced Labor Costs: Free up staff from tedious data entry tasks, allowing them to focus on more strategic initiatives.
• Improved Cash Flow: Faster processing times lead to quicker access to funds.
• Enhanced Accuracy: Automation minimizes human error in data entry.

“We are thrilled to partner with CheckAlt to deliver this transformative lockbox solution to the healthcare industry,” said Sasha King, Co-CEO of Anatomy. “In healthcare, a quarter of insurance payments to providers are on paper checks. With an AI-powered lockbox, we can enable full digitization of financial workflows for healthcare organizations. We were looking for a technology forward lockbox partner who is continuing to invest in their lockbox technology, and CheckAlt’s technology platform and customer centricity are best in class.”

What You Should Know: 

– Otsuka America, Inc. (OAI) today announced the formation of Otsuka Precision Health (OPH), a new subsidiary dedicated to transforming patient care through innovative digital solutions and a data-driven approach.

– OPH will leverage cutting-edge technology, including artificial intelligence (AI) and digital therapeutics, to personalize patient care journeys across various conditions, from mental health to nephrology.

A Patient-Centric Approach Powered by Data

OPH prioritizes the patient experience, aiming to achieve better outcomes by tailoring interventions to individual needs. This data-driven approach stands in contrast to traditional pharmaceutical models and seeks to unlock new possibilities for improved patient journeys.

Rejoyn™ Paves the Way for Personalized Mental Health Care

The recent FDA clearance of Rejoyn™, the first prescription digital therapeutic for major depressive disorder (MDD), exemplifies OPH’s commitment to bringing groundbreaking technologies to market. Rejoyn™ serves as a testament to the potential of digital therapeutics in improving patient experiences.

Combining Pharmaceutical Expertise with Digital Innovation

By combining the proven scientific rigor of Otsuka Pharmaceutical with a data-centric focus on patient experience, OPH has a unique advantage. This approach allows for faster development and commercialization of promising healthcare innovations.

Deepening Otsuka’s Commitment to Technology

Otsuka’s investment in OPH underscores its unwavering belief in the power of technology to improve patient lives and empower healthcare teams. OPH aims to:

• Personalize care: Tailor interventions to individual patient needs and journeys.
• Increase access: Unlock doors to healthcare solutions for a wider range of patients.
• Unify the healthcare experience: Bridge the gaps between different aspects of care delivery for a more seamless experience.

Otsuka Precision Health’s current focus areas include:

• Developing and delivering prescription digital therapeutics like Rejoyn™.
• Creating innovative technological solutions to address individual health needs.
• Providing non-promotional patient support services.

“Changes are needed to realize the potential of technology in health, and we’re ready to boldly address the barriers patients face in receiving care by taking a fundamentally new approach,” said Sanket Shah, president of OPH. “This Company will allow us to build on our commitment to the digital and technology space and continue building momentum with products such as, Rejoyn™, in a way that traditional pharmaceutical companies have not been able to explore.”

What You Should Know:

– Harnessing the power of AI for healthcare just got simpler. NVIDIA announced the integration of NVIDIA NIM, a collection of cloud-native AI microservices, with Amazon Web Services (AWS). 

– The strategic collaboration empowers developers to leverage pre-trained AI models for drug discovery, medical imaging analysis, and genomics research – all accessible through user-friendly APIs.

Streamlined Access to Powerful AI Tools

NIM integrates seamlessly with popular AWS services like SageMaker (for machine learning model development) and ParallelCluster (for high-performance computing). Additionally, AWS HealthOmics, a specialized service for biological data analysis, can orchestrate NIM workflows. This integration simplifies the process of deploying cutting-edge AI models for healthcare and life sciences companies already using the AWS cloud infrastructure.

Benefits of NVIDIA NIM on AWS

• Faster Development: Researchers can bypass complex model development and packaging, accelerating the deployment of generative AI solutions.
• Multimodal Workflows: NIM facilitates the creation of workflows combining AI models from various sources, like protein sequences, medical images, and patient records.
• Enhanced Drug Discovery: BioNeMo, a foundation for AI models in drug discovery, is included in NIM. Companies like Amgen are already utilizing BioNeMo to train protein design models.

Real-World Examples of Success

• A-Alpha Bio: This company developing protein interaction prediction tools saw a 10x speedup by utilizing BioNeMo models optimized for NVIDIA GPUs on AWS.
• Agilent: This life sciences leader used NVIDIA Parabricks, a genomics analysis tool within NIM, to significantly improve processing speeds for variant calling workflows.

Beyond Drug Discovery and Genomics

NIM offers more than just scientific applications. It also includes:

• Large Language Models: These powerful language processing tools can be used to create conversational AI healthcare assistants for patient education and clinician support.
• Visual Generative AI: This technology allows for the development of digital avatars and chatbots for a more engaging user experience.

What You Should Know:

– A new study by researchers at Mass General Brigham suggests large language models (LLMs),  a type of artificial intelligence (AI), could be a helpful tool for doctors to streamline communication with patients. However, the study also highlights the importance of human oversight to ensure patient safety.

–  The findings, published in The Lancet Digital Health, emphasize the need for a measured approach to LLM implementation.

The Burden of Physician Communication

Physicians today face increasing administrative tasks, including responding to patient portal messages. This can contribute to burnout and hinder patient care. The study investigated the potential of AI to assist doctors in drafting replies to patient messages.

AI Generates Draft Responses for Review

Researchers used a powerful LLM called GPT-4 to create draft responses to 100 hypothetical patient questions about cancer. Radiation oncologists then reviewed and edited these AI-generated responses.

Promising Results, But Caution Needed

The study found that:

• Doctors perceived AI assistance as efficient.
• Over 80% of AI-generated responses were deemed safe by doctors.
• Nearly 60% of these responses required no further editing before sending to patients.

However, the study also identified potential risks:

• A small percentage (7.1%) of unedited AI responses could mislead patients and pose health risks.
• In rare cases (0.6%), these responses could even delay essential medical care.

Importance of Maintaining Human Oversight

Interestingly, physicians often retained the educational content generated by the AI when editing responses. While this highlights the potential benefit of AI-generated patient education, the study emphasizes the importance of human oversight to mitigate safety risks.

Mass General Brigham Committment to Responsible AI

Mass General Brigham is committed to responsible AI development and implementation. They are currently conducting a pilot program integrating AI message drafting into their electronic health records system. Future research will focus on patient perception of AI-generated communication and potential bias in AI algorithms.
“Generative AI has the potential to provide a ‘best of both worlds’ scenario of reducing burden on the clinician and better educating the patient in the process,” said corresponding author Danielle Bitterman, MD, a faculty member in the Artificial Intelligence in Medicine (AIM) Program at Mass General Brigham and a physician in the Department of Radiation Oncology at Brigham and Women’s Hospital. “However, based on our team’s experience working with LLMs, we have concerns about the potential risks associated with integrating LLMs into messaging systems. With LLM-integration into EHRs becoming increasingly common, our goal in this study was to identify relevant benefits and shortcomings.”

What You Should Know:

– BioPhy, an AI drug development company, and Every Cure, a non-profit dedicated to unlocking the potential of existing drugs for new uses, today announced a strategic partnership to revolutionize drug repurposing through artificial intelligence (AI).

– The partnership follows Every Cure’s recent funding from the Advanced Research Projects Agency for Health (ARPA-H). A successful pilot using AI led to the identification of potential treatments for diseases like sickle cell disease, ALS, and autism spectrum disorder.

Unlocking Hidden Cures on the Pharmacy Shelf

Every Cure aims to identify new uses for existing medications, potentially saving patients from suffering while effective treatments remain undiscovered. This partnership will leverage BioPhy’s BioLogicAI platform to:

• Identify Promising Drug-Disease Matches: BioLogicAI’s AI engine will help Every Cure evaluate potential repurposing opportunities with high value.
• Optimize Clinical Trials: The partnership will focus on simulating and optimizing clinical trials for these potential new uses, maximizing success rates and reducing costs.

BioLogicAI: A Powerful Tool for Drug Development

BioLogicAI is a comprehensive AI engine that offers a range of benefits for life science companies:

• Clinical Trial Endpoint Predictability: BioLogicAI predicts successful clinical trial endpoints, a critical factor in drug development.
• Informed Decision-Making: The platform provides data-driven insights for various stages of drug development, including indication selection, licensing, and asset management.
• Benchmarking Preclinical Assets: BioLogicAI compares preclinical drug candidates to existing drugs and FDA-approved medications, informing development strategies.

Enhancing Drug Repurposing with AI

This collaboration will focus on several key areas to advance drug repurposing with AI:

• Building AI Infrastructure: The partnership will establish public and private benchmark datasets and knowledge graphs, crucial for AI development.
• Data Integration: Proprietary and novel data will be incorporated into the AI platform to enhance its capabilities.
• Refining Drug-Disease Matching: Ranking algorithms for drug-disease queries will be further optimized.
• Simulated Clinical Trials: AI will be used to simulate and optimize clinical trials for potential drug repurposing candidates.

“At BioPhy, we’re committed to creating a world where pharmaceutical companies won’t be forced to waste billions of dollars as a result of failed clinical trials. Every Cure shares that mission, while also unlocking new ways FDA-approved drugs can be used to accelerate treatment to patients suffering from diseases,” said Dave Latshaw II, CEO and Co-Founder of BioPhy. “We look forward to partnering with Every Cure to uncover even more diseases that all existing drugs can treat.”