Author: Partner Content

Molecular MRI Adds Certainty to Cancer Diagnosis

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MRI has become an important tool in the detection, diagnosis, and treatment planning for many cancers, especially solid tumors. However, up until now, a lack of specificity has held back the full potential of MRI.  

While MRI is very good at identifying areas of interest, factors such as infection, benign tumors, post-traumatic areas, and inflammation can all increase vascularity and, therefore, enhancement of contrast and signal changes.  

  • As a result, MRI has a high rate of false positives – findings that may be flagged as something of concern but that are not necessarily malignant lesions.  

This lack of accuracy results in clinical care teams performing too many confirmatory biopsies, with most being benign.

Now a novel class of molecular imaging contrast agents developed by Imagion Biosystems brings a new level of specificity to MRI. 

  • The company’s MagSense imaging agents have the potential to improve the clinical utility of the large installed base of MRI systems across the globe through improved accuracy of interpretation, avoiding biopsies of benign lesions, driving earlier intervention and improving outcomes and quality of life.

Unlike gadolinium-based agents that non-specifically enhance tissue vascularity regardless of cause, MagSense imaging agents target receptors on cancer cells.  

  • By combining magnetic nanoparticles that have high susceptibility and r2 relaxivity with cancer-specific biomarkers, molecular MRI becomes possible.

Imagion’s superparamagnetic iron oxide nanoparticles are coated with a cancer-specific targeting moiety, such as an antibody or peptide.

  • The cancer biomarker molecule causes the particles to bind to target-specific cancer cells, if present. If the lesion in question is not the target cancer, the particles do not bind.

Where the imaging agent has become attached to the tissue, the nanoparticles produce an identifiable change in MRI signal. 

  • This signal is easily detected by radiological review and can be quantitatively assessed.

Imagion has developed cancer-specific contrast imaging agents for HER2 breast cancer, prostate cancer, and ovarian cancer, and the MagSense platform can be adapted for any type of cancer for which there is a targeting moiety.  

  • Imagion is now preparing to initiate a multisite phase 2 study in the U.S. in HER2+ breast cancer patients to optimize imaging parameters and compare MagSense imaging to the standard of care.  

The Takeaway

Molecular-specific imaging agents like the MagSense technology from Imagion Biosystems create the opportunity for molecular MRI to fundamentally change how radiologists detect and monitor cancers. 

The company is publicly traded (ASX:IBX) and is looking to expand its U.S. investor base as it advances through its clinical programs. To become involved as an investigator or investor or to learn more visit their website.

Integrated Solutions for Managing Incidental CAC Findings

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The rising prominence of coronary artery calcium as a prognostic marker for heart disease has created an emerging challenge for radiologists: how should they manage incidental CAC findings discovered on routine CT exams? Fortunately, new industry collaborations are making it possible to deliver CAC reports to clinicians without disrupting workflow. 

Routine CT scans are revealing data beyond their original diagnostic intent.

  • AI solutions – such as AVIEW CAC from Coreline Soft – play a pivotal role in identifying risks for cardiovascular disease, osteoporosis, and metabolic disorders – all from a single scan.

AI allows one CT scan to assess lung, cardiovascular, and skeletal health, improving diagnosis and treatment planning.

One imaging services provider that has put AVIEW CAC into use is 3DR Labs, which has been actively integrating the solution into its nationwide clinical network.

  • The partnership enables 3DR Labs radiologists to generate consistent, high-quality CAC reports directly within PACS, while significantly reducing turnaround times.

3DR Labs is finding that AVIEW CAC optimizes workflow efficiency and significantly reduces the time required for CAC assessment. 

  • It also ensures that radiologic technologists can perform quick QA checks, enhancing consistency and reliability in the delivery of the report.

The latest generation of the FDA-cleared AVIEW CAC features an upgraded user interface and advanced batch-scoring functionality. 

  • 3DR Labs is now working to expand AI-driven insights into lung and neuroimaging through Coreline’s broader AVIEW platform (AVIEW ILA for interstitial lung abnormalities and AVIEW BAS for brain CT).

Beyond diagnostic imaging, this collaboration supports growing demands for cost-efficiency in healthcare. 

  • As U.S. insurers and government agencies recognize the ROI potential of early AI detection, platforms like AVIEW CAC offer scalable, high-performance solutions that lower costs and streamline care delivery.

3DR Labs has also highlighted Coreline Soft’s role as a founding partner in AI Labs, the company’s vendor-neutral platform to deliver the latest AI innovations to radiology workflows.

The Takeaway

New partnerships like the collaboration between Coreline Soft and 3DR Labs are advancing the future of AI in radiology – focusing on automation, early detection, and better patient outcomes through powerful, clinically validated technologies. Such partnerships not only reflect increasing adoption of AI in U.S. healthcare but set the stage for global transformation in diagnostic imaging.

AI-Driven Diagnostics Detects Multiple Chest Diseases from Single CT Scan

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A new generation of AI solutions is enabling clinicians to detect multiple chest pathologies from a single CT scan. Lung cancer, cardiovascular disease, and chronic obstructive pulmonary disease (COPD) can all be detected in just one imaging session, ushering in a new era of more efficient imaging that benefits both providers and patients. 

Advances in CT lung cancer screening have been generating headlines as new research highlights the improved clinical outcomes possible when lung cancer is detected early. 

  • But lung cancer is just one of a “big three” of thoracic comorbidities – the others being cardiovascular disease and COPD – that can result from long-term exposure to toxic substances like tobacco smoke. 

These co-morbidities will be encountered more often as health systems ramp up lung cancer screening efforts, creating challenges for radiologists in managing the many incidental findings discovered with chest CT scans.

  • And it’s common knowledge that radiologists already have their hands full in an era of personnel shortages and rising imaging volumes. 

Fortunately, new AI technologies offer a solution. One of these is Coreline Soft’s AVIEW LCS Plus, an integrated three-in-one solution that enables simultaneous detection of lung cancer, cardiovascular disease, and COPD from a single chest CT scan. 

  • AVIEW LCS Plus is the only solution adopted for national lung cancer screening projects across key countries, including Korea (K-LUCAS), Germany (HANSE), Italy (RISP), and the pan-European consortium (4ITLR). 

Coreline’s solution is widely recognized as a pioneering AI platform for an era where unexpected findings can save lives, gaining increasing attention in academic journals and health policy reports alike.

  • In the U.S., AVIEW LCS Plus has been adopted by Temple Health, and the Pennsylvania system’s use of the solution in their Temple Healthy Chest initiative has been recognized as an innovative healthcare model within the Philadelphia region. 

Temple Health clinicians are finding that AI contributes to early detection of incidental findings, improved survival rates, and more proactive care planning.

  • AVIEW LCS Plus is streamlining lung cancer screening, helping identify chest conditions at earlier stages, when treatment is most effective. It is finding not only lung nodules but also undetected comorbidities that were often missed with conventional CT workflow. 

Coreline Soft will be presenting AVIEW LCS Plus in collaboration with Temple Health at the upcoming American Thoracic Society (ATS 2025) international conference in San Francisco from May 16-21. 

  • Attendees will be able to learn how AI in medical imaging can establish new standards, not just in diagnostics, but across policy, patient care, and hospital strategy. 

High-Risk Breast Clinics: A Smart Move for Imaging Providers

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High-risk breast cancer clinics are no longer just a good idea – they’re becoming a strategic imperative. These programs, focused on identifying and managing women at elevated risk for breast cancer, are proving their value clinically and financially.

For imaging providers, they present an opportunity both to improve care and grow service lines in a value-based care environment, while also differentiating themselves in increasingly competitive markets. A recently published white paper offers a full explanation of the benefits of high-risk breast clinics.

Treating late-stage breast cancer is extremely costly – $76,000+ in the final year of life alone – and it represents a major portion of oncology spend nationwide. 

  • By identifying high-risk patients early and offering enhanced surveillance with breast MRI, clinics can diagnose more cancers at early stages, when treatment is more effective and less expensive. 

Studies show MRI screening in BRCA1 carriers is cost-effective at ~$50,900 per QALY. 

  • This makes it a smart investment from both a patient and payor perspective.

Historically, preventive programs were considered cost centers. Not so with high-risk breast clinics. 

  • Once a patient is flagged as high risk, the care pathway includes reimbursable   genetic counseling and testing, supplemental imaging (MRI or contrast-enhanced mammography), biopsies, chemoprevention, and even risk-reducing surgeries. Each step creates downstream revenue for imaging centers and affiliated specialists – all while improving patient care.

Integration is key. Embedding risk assessment tools like Tyrer-Cuzick or AI-based models (e.g. Mirai) into the high-risk clinic’s imaging workflow enables automatic triage. 

  • Patients with ≥20% lifetime risk can be directly referred to the high-risk clinic. Some models now use short-term risk from imaging data alone to identify the top 5-10% women most likely to develop cancer within five years – significantly outperforming traditional tools in clinical studies.

Successful clinics rely on multidisciplinary teams. Advanced-practice providers manage most visits. Genetic counselors – in person or via telehealth – manage testing results and family history. Patient navigators coordinate follow-ups and authorizations. 

  • This team-based approach keeps physician time focused and costs under control, ensuring the clinic operates efficiently and sustainably.

The Takeaway

For imaging providers, high-risk breast clinics offer a powerful blend of patient impact and business growth. They reduce expensive late-stage cancers, drive high-value imaging, and create long-term patient relationships. In an era of value-based care, they’re not just a clinical upgrade – they’re a strategic advantage. Forward-thinking imaging leaders are recognizing this model as essential to the future of preventive breast care.

Bridging Quality and Efficiency: Why Radiology Groups Are Adopting AI for Mammography Workflows

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By Dr. Roger Yang, President, University Radiology Group, and Mo Abdolell, CEO, Densitas

Radiology groups offering mammography services operate under ever-tightening demands, including MQSA EQUIP and ACR accreditation standards. Manual case selection, cumbersome paperwork, and lengthy review cycles often divert radiologists and technologists from what matters most – patient care.

But change is coming. By leveraging AI and mammography workflow automation, private radiology groups are reshaping how they manage quality, reduce administrative overhead, and advance patient care. 

AI-powered platforms can significantly streamline mammography quality management by:

  • Automating case selection for EQUIP reviews.
  • Measuring positioning metrics in near real-time.
  • Centralizing documentation to simplify compliance.

Some practices have reported up to a 90% reduction in EQUIP review time and 80% workload reduction in ACR accreditation using AI. But time savings are only part of the story.

Rather than waiting months for sporadic audits, technologists gain instant insights into positioning accuracy. This rapid feedback loop…

  • Accelerates targeted training.
  • Encourages continuous quality improvement.
  • Empowers technologists to self-monitor performance and identify gaps earlier. 

Today’s vendor-agnostic AI solutions integrate seamlessly with diverse imaging systems across multiple sites. 

  • Standards-based platforms can grow from a single mammography unit to dozens, helping radiology groups expand without adding complexity.

In a crowded marketplace, radiology practices that adopt AI-driven mammography quality management and automation stand out as forward-thinking leaders. Advantages include…

  • Enhancing patient perception: Offering efficient exams and high-quality imaging underscores a commitment to excellence, boosting satisfaction and referrals.
  • Leveraging analytics: Aggregated data on image quality and positioning helps leadership identify trends, optimize workflows, and highlight innovation.
  • Attracting top talent: Skilled technologists and radiologists gravitate toward practices with cutting-edge tools.

By integrating AI early, private practices can differentiate themselves, paving the way for growth and success.

Successful AI adoption and mammography workflow automation relies on more than just software. It requires:

  • Deep mammography expertise from vendors.
  • Robust training programs for staff.
  • Change training programs for staff.
  • Responsive customer support that fosters trust.

Mammography workflow automation cuts administrative burdens, curtails physician burnout, and speeds accreditation. Technologists receive clear, timely feedback, improving morale and performance. 

  • Meanwhile, patients benefit from streamlined workflows and consistent image quality, reinforcing trust in the practice.

The Takeaway

By embracing AI-driven mammography workflow automation and quality management, radiology groups can stay focused on delivering exceptional patient care while meeting regulatory requirements. This strategic investment propels private practices toward sustained growth and innovation, securing a competitive edge in a rapidly evolving healthcare landscape. Learn more.

Unlocking Body Composition Insights with Voronoi Health Analytics

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Body composition plays a pivotal role in monitoring organ and tissue health and predicting treatment outcomes. Accurate changes in body composition metrics can indicate reduced muscle quantity and quality – a sign of sarcopenia – as well as altered fat distribution in organs such as the liver in metabolic diseases, epicardial and paracardial fats in cardiovascular health, and more.

However, manual segmentation is time-consuming and labor-intensive. 

  • Voronoi Health Analytics eliminates this bottleneck by combining cutting-edge AI with efficient visualization tools, automating the extraction of body composition metrics from CT and MRI scans. The company’s solutions transform imaging data into actionable insights, improving patient outcomes.

Voronoi Health Analytics provides innovative, intuitive AI tools that enable clinicians and researchers to extract quantitative body composition measurements rapidly and with high accuracy – no programming required. 

  • The company’s platforms are trusted by over 175 research labs across 25 countries, with numerous publications validating their accuracy and impact on clinical care and medical research.

Voronoi has two flagship solutions …

  • DAFS: A comprehensive 3D segmentation platform for analyzing multiple tissues, organs, lesions, and vasculature across CT and PET/CT imaging. DAFS also overlays CT segmentations onto PET scans, enabling rapid, high-accuracy assessments of PET tracer uptake in organs, tissues, and lesions.
  • DAFS Express: Optimized for single-slice body composition analysis from CT and MRI scans, this tool delivers precise measurements of skeletal muscle, visceral fat, intermuscular fat, and subcutaneous fat in seconds, making it ideal for high-throughput clinical settings.

Accurate body composition analysis is critical for staging body habitus, detecting onset of signatures of adverse health such as metabolic or cardiovascular disorders, evaluating disease progression, and monitoring organ and tissue health as a function of disease and intervention. Voronoi’s platforms address key challenges such as …

  • Reducing Workloads: Automate routine segmentation tasks and allow clinicians to focus on complex cases.
  • Improving Precision: Deliver consistent, reproducible results across patients and studies.
  • Advancing Care: Provide predictive insights that help optimize treatment strategies.

DAFS and DAFS Express seamlessly integrate into existing imaging workflows, enhancing efficiency without disrupting operations.

Body composition analysis goes beyond measuring muscle and fat. It quantifies all organs and tissues, creating data that drives predictive models. 

  • Voronoi’s vision is to empower healthcare professionals with tools that simplify complexity, support proactive care, and enhance patient outcomes.

Discover how Voronoi Health Analytics is revolutionizing body composition analysis. Visit the company’s website to request a demo and elevate your workflow today.

Time to Embrace X-Ray AI for Early Lung Cancer Detection

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Each year approximately 2 billion chest X-rays are performed globally. They are fast, noninvasive, and a relatively inexpensive radiological examination for front-line diagnostics in outpatient, emergency, or community settings. 

  • But beyond the simplicity of CXR lies a secret weapon in the fight against lung cancer: artificial intelligence. 

Be it serendipitous screening, opportunistic detection, or incidental identification, there is potential for AI incorporated into CXR to screen patients for disease when they are getting an unrelated medical examination. 

  • This could include the patient in the ER undergoing a CXR for suspected broken ribs after a fall, or an individual referred by their doctor for a CXR with suspected pneumonia. These people, without symptoms, may unknowingly have small yet growing pulmonary nodules. 

AI can find these abnormalities and flag them to clinicians as a suspicious finding for further investigation. 

  • This has the potential to find nodules earlier, in the very early stages of lung cancer when it is easier to biopsy or treat. 

Indeed, only 5.8% of eligible ex-smoking Americans undergo CT-based lung cancer screening. 

  • So the ability to cast the detection net wider through incidental pulmonary nodule detection has significant merits. 

Early global studies into the power of AI for incidental pulmonary nodules (IPNs) shows exciting promise.

  • The latest evidence shows one lung cancer detected for every 1,120 CXRs has major implications to diagnose and treat people earlier – and potentially save lives. 

The qXR-LN chest X-ray AI algorithm from Qure.ai is raising the bar for incidental pulmonary nodule detection. In a retrospective study performed on missed or mislabelled US CXR data, qXR-LN achieved an impressive negative predictive value of 96% and an AUC score of 0.99 for detection of pulmonary nodules. 

  • By acting as a second pair of eyes for radiologists, qXR-LN can help detect subtle anatomical anomalies that may otherwise go unnoticed, particularly in asymptomatic patients.

The FDA-cleared solution serves as a crucial second reader, assisting in the review of chest radiographs on the frontal projection. 

  • In another multicenter study involving 40 sites from across the U.S., the qXR-LN algorithm demonstrated an impressive AUC of 94% for scan-level nodule detection, highlighting its potential to significantly impact patient outcomes by identifying early signs of lung cancer that can be easily missed. 

The Takeaway 

By harnessing the power of AI for opportunistic lung cancer surveillance, healthcare providers can adopt a proactive approach to early detection, without significant new investment, and ultimately improving patient survival rates.

Qure.ai will be exhibiting at RSNA 2024, December 1-4. Visit booth #4941 for discussion, debate, and demonstrations.

Sources

AI-based radiodiagnosis using Chest X-rays: A review. Big Data Analytics for Social Impact, Volume 6 – 2023

Results from a feasibility study for integrated TB & lung cancer screening in Vietnam, Abstract presentation UNION CONF 2024: 2560   

Performance of a Chest Radiography AI Algorithm for Detection of Missed or Mislabelled Findings: A Multicenter Study. Diagnostics 12, no. 9 (2022): 2086

Qure.ai. Qure.ai’s AI-Driven Chest X-ray Solution Receives FDA Clearance for Enhanced Lung Nodule Detection. Qure.ai, January 7, 2024

Using AI-Powered Automation to Help Solve Today’s Radiology Crisis

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Reimbursement cuts. Radiologist and staff shortages. Rising costs. Surging imaging volumes. Overwhelming staff workloads. Shrinking margins. 

Sound familiar?

Radiology departments, imaging centers, and radiology practices are facing a perfect storm of challenges to deliver high-quality patient care while remaining profitable and competitive. 

  • This familiar narrative emphasizes the need for change and to embrace automation, AI, and technology solutions that automate routine tasks. 

RADIN Health has developed an innovative, cloud-based (SaaS), all-in-one technology stack based on the firsthand experience of radiologist Alejandro Bugnone, MD, CEO and medical director of Total Medical Imaging (TMI), a teleradiology group that reads for imaging centers and hospital systems nationally.  

  • Dr. Bugnone and his team of radiologists were similarly suffering from supply and demand imbalance, reimbursement cuts, increasing study volumes, and customer pressures to maintain their margin. 

As a software developer and seasoned radiologist, Dr. Bugnone was equally frustrated by the lack of a comprehensive, end-to-end technology solution in the market to address these same issues for his teleradiology practice.  

  • In evaluating numerous RIS, PACS, AI voice recognition, and workflow management solutions, his team found that each required expensive interfaces, separate company fees, and ongoing support, yet as an ecosystem still did not deliver a seamless experience that would provide a return on investment. 

An alternative is a system based on straight-through processing, a concept first pioneered in the financial services industry in which automation electronically processes transactions without manual intervention. 

“I knew there had to be a better way forward. I founded RADIN Health for healthcare and teleradiology practices [like TMI], imaging centers, and radiology departments based on straight-through processing, similar to how Wall Street sped up financial transactions without any human intervention,” Dr. Bugnone said. 

RADIN Health is a cloud-based platform that combines RIS, PACS, dictation AI, and workflow management into an all-in-one software solution. 

  • It leverages artificial intelligence, machine learning, OCR/AI, natural language processing (NLP), and other intellectual property.

Dr. Bugnone said TMI has achieved remarkable efficiencies with RADIN. 

“Our results at TMI have been staggering since implementing RADIN over the past 18 months for our complex teleradiology practice,” Dr. Bugnone noted. “With RADIN DICTATION AI, our radiologists have increased their productivity and efficiency, reducing dictation times 30% to 50%.” 

By adding RADIN SELECT, TMI reduced its SLAs more than 50% and FTEs by 70% for managing operational workflow tasks, all while adding 35% in study volumes.  

  • RADIN’s all-in-one technology solution has enabled Total Medical Imaging to meet the challenges of the radiology crisis without hiring new personnel – simply by unlocking the efficiency of their existing staff. 

“We have enjoyed significant growth in 2024 without the need to hire additional staff,” Dr. Bugnone concluded.

Watch the video below to see how RADIN’s all-in-one solution can help your practice.

Reduce the Mess, Reduce the Stress: Automating and Accelerating Efficiency in Complex Medical Imaging Environments

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Repetitive, arduous tasks are a major contributor to burnout – an increasingly prevalent issue in healthcare. While digital innovation is transformative, introducing more technology to workflows often creates additional layers of complexity, hindering efficiency, performance monitoring, and ultimately the quality of care.

As a result, once-simple traditional workflows have grown cumbersome over time, filled with many interconnected tasks that are difficult to manage. 

  • As these processes become more complex, it’s clear that healthcare needs to reduce, subtract, and simplify to maintain high standards of care.

Every traditional (or macro) workflow consists of multiple smaller tasks or steps (micro-workflows), many of which are still performed manually. 

  • Consider a wound care scenario where a practitioner takes images, searches for the patient’s record in the EHR, uploads the images, and manually enters encounter details. 

While each individual task may seem small, when multiplied by dozens of similar interactions each day, these repetitive steps …

  • Decrease the time providers have for meaningful patient interactions.
  • Lower overall productivity.
  • Increase the potential for human error.
  • Contribute to burnout and fatigue.

Micro-workflows address this by breaking down processes into discrete, manageable steps. For example, by …

  • Identifying the patient within the EHR.
  • Capturing the image.
  • Automatically inputting relevant metadata.
  • Seamlessly sharing the image with the care team.

This granular approach enables automation, allowing individual components to be optimized or modified without disrupting the entire process. 

  • Micro-workflows offer adaptability, efficiency, and responsiveness, meeting evolving clinical requirements while reducing complexity.

Moreover, micro-workflows make it possible to monitor individual tasks with precision. 

  • This approach allows healthcare organizations to pinpoint workflow gaps, troubleshoot issues, and resolve performance bottlenecks. 
  • In multi-vendor environments, where integrating various systems and applications can be a challenge, the ability to streamline processes and automate tasks becomes especially valuable.

Strings by Paragon is a platform specifically designed to help healthcare organizations harness the power of micro-workflows. 

  • By breaking traditional workflows into smaller, more manageable steps, Strings enables automation, real-time performance tracking, and monitoring across a wide range of applications and infrastructure. 

The platform’s single-pane-of-glass interface provides visibility into complex, multi-vendor environments.

  • Strings offers actionable insights and automated optimizations tailored to specific clinical workflows.

With Strings, organizations can proactively identify workflow bottlenecks, implement targeted optimizations, and measure performance and ROI with precision – leading to improved efficiency, enhanced imaging quality, better patient outcomes, and a value-driven approach to care.

Learn more about Strings by visiting Paragon Health IT’s website, or visit them at RSNA 2024 at booth #1849.

Optimizing Front Office Operations through Integrated Apps and Cloud-Based RIS/PACS

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Paradox of High Patient Volumes

At first glance, it may appear having more patients should naturally lead to higher revenue. When you consider extra labor costs and the fact that reimbursements are decreasing, increased volume can turn into diminishing returns.

  • Basically, the cost of adding more staff can end up being higher than the value of additional patient volumes.

Optimal management of growing patient volumes requires a new way of working with automation and cloud-based apps that replace the heavy burden of manual processes.

  • By using technology to eliminate processes, medical facilities manage patient loads better without the need for more labor costs. 

This proactive approach not only improves efficiencies but also lets front office staff focus on patient needs instead of getting bogged down with administrative tasks. 

  • Ultimately, shifting towards automation and consolidation of tasks is key to maintaining clinic profitability and keeping high standards of care, especially with increasing medical demands.

How RamSoft Can Help Simplify Front Office Operations 

Achieving workflow excellence starts with a single sign-on into a unified RIS/PACS and providing access to complementary medical imaging apps via a single worklist in the cloud. 

  • By leveraging cloud applications with scalability across facilities, organizations can “build as they grow,” while maintaining control and flexibility.

RamSoft PowerServer and OmegaAI RIS/PACS platforms reduce administrative burdens and costs associated with manual processes. Here’s how…

  • Blume – Patient Portal: Patient access to diagnostic images and reports, imaging sharing with referring clinicians and family, self-scheduling, intake forms, and appointment notifications. These self-service features decrease the number of phone calls, the time needed for patient registration, and the manual process of intake form completion and filing. 
  • pVerify: Batch verification and real-time eligibility (authorization available soon) eliminates the need to call multiple insurance providers, freeing up staff time while reducing denials. 
  • PracticeSuite: An embedded solution including workflow options to accommodate entries from the RIS/PACS worklist or within the billing module. Quickly accesses top billing functions, Payment Ledger for balances and eligibility, and Payment Entry to add payment and print a receipt. 
  • openDoctor: Automated appointment notifications through SMS and email which replaces lists of confirmation calls and reduces missed appointments. 
  • InterFAX by Upland: Integrated digital workflow for inbound (available soon) and outbound faxes, reducing the need for manual acceptance and processing of referral or report faxes. 

Mobile Applications Are Building a Patient-Centric Experience

Protecting patient data is business-critical for all medical practices, as it is for RamSoft. We’re using Microsoft Azure Cloud to ensure all data and applications are secure.

  • Workflow optimization in medical imaging can significantly impact the patient experience, leading to increased loyalty and satisfaction. 

Is Your Practice Operating Optimally?

Explore how RamSoft’s new automation applications, including patient engagement tools, integrated with cloud-based RIS/PACS can improve operations and profitability of your practice. 

Learn more on the company’s website or book a demo at RSNA 2024 for booth #6513 in the North Hall.  

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