A laser focus on smart improvements will make radiologists’ jobs easier, allowing them to better prioritize cases and reduce burnout. The results of this will be more precise and personalized patient care.
For example, many screening mammograms are interpreted using CADe technology. This has become a standard practice in most US mammography centers.
Streamlined Workflow
The workflow of radiology is constantly changing, but the technology that supports it doesn’t have to be. Smart connected imaging systems streamline the workflow for greater productivity and quality of care. Using an AI-based quality care solution like GenAI to provide the right information to technologists and radiologists at just the right time can help you improve patient outcomes and increase efficiency.
For example, GE’s next-generation Definium 656 HD fixed X-ray features intelligent workflow solutions that support technologists. These tools, such as Position Assist and Technique Assist, help ensure consistent, efficient positioning for better results by automatically rotating images during the exam. This reduces errors during the image capture process, which can lead to a number of costly retakes. It also eliminates the need to manually search multiple systems for clinical data that is needed for proper patient positioning. According to RSNA, incomplete or inaccurate patient data leads to 21% of incorrect diagnoses.
Another important factor in the workflow is the ability to prioritize cases for review. For example, if a patient is experiencing symptoms of a brain bleed, the AI can identify and prioritize this scan over other exams in the queue. This reduces the amount of waiting for a diagnosis and allows physicians to treat patients sooner for improved outcomes.
In addition to reducing the number of times an image needs to be retaken, AI-based quality care solutions can also help prevent errors during the exam. For example, GE’s GenAI can assist radiographic technologist by providing them with guidance on correct positioning and technique for the best result. This can help avoid a number of common mistakes that can be made in radiology, including not positioning the patient correctly, which is responsible for up to 25 percent of retakes.
Another way to improve the radiology workflow is by integrating AI tools within PACS. This makes it easier for radiologists to use these tools when they need them, as opposed to having to launch a separate system or program. One example of this is Clario SmartWorklist, an intelligent workflow platform that enables users to access AI tools from within their PACS interface. The platform can monitor workflow performance and identify times when accuracy is most vulnerable. For example, this software can detect if an unfavorable peer review score occurs more frequently during a particular time of day and determine what steps to take to address the problem.
Better Patient Care
Getting the right patients to the right radiologist at the right time is one of the biggest challenges in radiology. But with smart connected imaging systems and data integration, this process is getting easier.
For example, smart imaging solutions can automatically rotate images for radiographers, which saves them time and reduces errors. This frees up time for radiologists to focus on the most pressing cases and allows them to provide better patient care.
Additionally, intelligent imaging can improve safety in the operating room. Virtual reality (VR) and augmented reality (AR) technologies enable surgeons to visualize complex anatomical structures without having to disrobe or step outside. This helps them make better treatment decisions during surgical procedures and ensures safe surgery for patients.
The same technology can also help doctors better understand their own patients’ health. For example, some smart imaging systems can detect a patient’s heart rate through their body heat and display it on a screen, which gives doctors an immediate view of their patient’s health. This can be particularly helpful when diagnosing a patient with cardiac abnormalities.
With a smart DR solution, radiologists can also easily recognize a patient by their name and image data, which allows them to prioritize and allocate scans more efficiently. In addition, GenAI can also help radiologist improve the quality of their reports by optimizing and predefining views and reducing re-readings.
In the future, these types of smart systems will help create a seamless radiology workflow that’s focused on the patient, which can lead to improved clinical outcomes and increased efficiency. This includes providing referring physicians with standardized, patient-specific images and ensuring that the correct protocols are used in order to obtain high-quality, diagnostically relevant images.
Other innovations include automated protocoling, which helps radiologist streamline the scanning and reporting processes by providing a set of rules for scanning each patient. This frees radiologist’s time to focus on more critical tasks like interpreting results, which can improve patient outcomes.
Increased Efficiency
Using advanced digital technologies like AI and machine learning, vendors and independent start-ups are rethinking how medical imaging equipment is engineered and operated. This is driving a shift in healthcare technology and workflows for both patients and physicians.
One area of particular interest is how image processing software used in MRI, CT, PET/MR, and nuclear imaging is changing. These advances allow the software to be accessed remotely, on any device. This removes the need for a dedicated workstation and makes it possible to access this software from anywhere on an organization’s network. This allows for more efficient use of the available resources, and it also improves data security by making it easier to control who has access to specific imaging studies.
This type of software can also reduce report turnaround times and eliminate the need for typing and data entry by enabling physicians to dictate in real time. It also helps to ensure the correct patient information is entered, which cuts errors. This software solution has been particularly useful in the ED, where even a small delay can have a serious impact on patient care.
Another example is GenAI, a new X-ray scanner solution from Philips that uses AI to streamline radiology workflows and deliver tailored, reproducible, consistent exams. The system can suggest optimal scanning protocols, automatically recognizing a patient’s unique health status and prior results. It can also detect subtle or complex patterns in images and flag them for radiologist review, delivering triage notifications to PACS at the same time as the DICOM image with no additional processing time.
GenAI can also help to reduce exam repeats, which is a significant expense and potential patient safety risk. This is accomplished by identifying and analyzing a patient’s previous scans to create an “embedded” database that helps to identify patterns of disease progression or benign incidental findings. The AI is then able to identify these characteristics in future scans, reducing the need for re-imaging and decreasing costs while providing better patient care.
Increased Revenue
In the field of medical imaging, new technology is constantly changing and enhancing diagnostics. With the increasing emergence of AI and machine learning, medical imaging companies can leverage these technologies to increase patient care and improve efficiency.
In addition to being able to reduce costs, they can also capture non-covered revenue through a variety of solutions. These include automated reimbursement systems, telemedicine, and clinical decision support. By integrating these capabilities into their platforms, radiology companies can help their customers make more informed decisions on how to manage patients.
This is especially important for hospitals and clinics that need to adhere to strict regulatory guidelines and maintain high operational standards. Using AI-driven enterprise imaging solutions, like those offered by Visage Imaging, can help them meet these compliance requirements and increase their profitability.
Radiology has been among the most successful healthcare sectors in embracing digital transformation. From the early days of analog film to today’s sophisticated MRI, CT, and PET scanners, medical imaging has evolved into a powerful diagnostic tool with the potential to save lives. With the continued growth of smart imaging technology, the future of radiology promises to be even more transformative.
As technology evolves, it is creating a better patient experience and providing new opportunities for imaging companies to grow their business. For example, virtual reality (VR) and augmented reality (AR) are becoming more common in medical settings. Both are used to enhance the visualization of data, making it easier for clinicians to understand and use. These tools are also helping surgeons and interventional radiologists visualize in three dimensions rather than relying on 2-D images from scans. This will allow them to plan procedures more accurately, avoid complications such as misalignments, and perform biopsies more efficiently.
Another opportunity for imaging companies is to expand into cancer diagnostics and therapeutics. By developing radiopharmaceuticals, or ligands that bind to a tumor, these companies can create more accurate and cost-effective ways to identify cancerous cells.
A growing number of imaging devices produce massive amounts of digitized data that need to be stored securely. One solution is blockchain, which provides an encrypted storage system that is easy to access for patients and providers. This allows for secure sharing of patient data and streamlines collaboration between different hospital facilities.