Streamlining the radiology workflow to improve efficiency and capacity

Advanced medical imaging continues to be a vital patient touchpoint in healthcare diagnostics, however one of the most significant challenges facing radiology departments is the need to improve workflow efficiencies and meet increasing demands. Additionally, they are also combatting high-stress levels and radiology staff burnout. Therefore, it is essential to find opportunities to address these issues by streamlining workflows and reducing inefficiencies, while continuing to provide high-quality imaging diagnostics that can improve patient outcomes.

Imaging technology hardware and software have continued to advance to propel radiologists’ ability to deliver more personalized care as well as earlier diagnoses and treatment of diseases. One benefit is the generation of high-quality medical images, often hundreds of images per exam. This growing volume of images for analysis is a contributing factor to the heavy workload of radiologists. Radiology staff shortages are putting pressure on health systems already constrained by limited resources, aging patient populations, and increasing demands for imaging. One of the glaring results is physician burnout. In one survey, forty-five percent of radiologists reported symptoms of burnout.^[1]

Addressing radiology workflow efficiency

Amidst managing increasing exam complexities and staff shortages, some radiology departments can find it challenging to acquire and operate cutting-edge imaging technology if it requires a sizable capital expenditure, additional staff training, or additional operating staff. However, in a report on Global Imaging Department Priorities and Outlook, more than 70 percent of radiologists who responded reported that their top departmental priorities include keeping their department up to date with state-of-the-art technology, as well as improving department workflow efficiency and productivity.^[2] Additionally, only 26 percent of respondents felt their current operational capacity was sufficient to meet their anticipated growth in procedure volumes over the next two to three years.^[3]

GE Healthcare is committed to developing innovative solutions to help radiology departments navigate these interrelated changes and improve efficiencies in the radiology workflow. With advanced imaging technology, intuitive design, and sustainable cost of ownership, radiology departments can be better equipped to handle increasing imaging volumes as well as alleviating radiology burnout and improving radiologists’ day-to-day work environment. 

“We believe solving key challenges in radiology such as improving efficiency can help ease the capacity problem and reduce rework for radiologists and technologists, while improving patient care,” said Scott Miller, Chief Marketing Officer, Imaging at GE Healthcare. “In this new era in healthcare, we’re developing solutions to streamline the radiology workflow, reduce variation across exams, and leverage AI to improve speed and quality. The future of healthcare is focused, collaborative and integrated. Our holistic approach to advancing innovation and imaging technology can help providers overcome today’s challenges and also provide sustainable, long-term solutions.”

Streamlining exam workflows with AI and automation

The increasing use of AI and digitization to improve exam workflows is making an impact in radiology across clinical applications. The American College of Radiology (ACR) suggests AI adoption in the specialty went from zero to 30 percent between 2015 and 2020.^[4]  AI and machine learning are proving to be well-suited for radiology, from automating repetitive tasks and using algorithms to automatically detect complex abnormal patterns in image data to providing an assistive diagnosis for patients.

By leveraging AI and machine learning technologies, innovative solutions can help increase efficiencies across the entire radiology workflow without increasing the administrative and training burden on clinicians. As a diagnostic aid to radiologists, machine learning and AI algorithms can help in the assessment of clinical conditions such as coronary artery calcifications, bone mineral density, abdominal aortic aneurysms, and numerous other applications.^[5] Often, they can be configured to alert the radiologist as well as populate findings into the imaging report directly.

On X-ray systems, for example, GE Healthcare has developed automated tools intended to assist technologists with correct anatomical positioning, quality control, and to confirm protocol selections at the time of the scan as well as auto-rotate images to save time for radiologists. To improve the triage of urgent cases, the X-ray on-device AI algorithm also automatically analyzes images, upon acquisition, for critical findings such as pneumothorax. Triage notifications are sent directly to PACS and flagged for prioritized radiologist review.

Additionally, in computed tomography (CT), optimized protocols and expanded patient positioning options can help expedite exams and accommodate more patients. GE Healthcare’s suite of AI solutions personalizes scans accurately and automatically for each patient. As a result, the technologist can position patients with a high degree of accuracy, select the correct protocols based on automated suggestions, and set up and complete the exam in less time because of a dramatic reduction in clicks required on the equipment and workstations, enabling an effortless workflow.

AI technology, when implemented in support of a user-centric design, can be like a “personal assistant” that provides automation and support to technologists – helping to reduce physical workload and improving operational efficiency while maximizing a technologist’s time at the patient’s bedside to help deliver the best patient care possible.

Optimizing imaging reconstruction with AI and deep learning

Applying AI and deep-learning algorithms to magnetic resonance imaging (MRI) image reconstruction is an exciting realization of technology that is enabling improvements in MRI that haven’t been possible using traditional reconstruction methods. Healthcare providers are using these new technologies to produce high-quality images with shorter scan times, overcoming the historical trade-offs in MRI between scan time and image quality.

Forward-thinking innovations in image reconstruction software are enabling higher image quality to inform clinical decisions and impact patient care. GE Healthcare’s deep-learning MR reconstruction technology* is a trained algorithm to reconstruct sharper images by leveraging all of the raw MRI acquisition data. It can be applied upon acquiring new systems, but it can also be added on existing installed MRI systems to enable wider access to this clinically impactful technology. Powerful improvements can be seen in image quality and in spatial resolution that were made possible using deep-learning image reconstruction techniques and can be obtained with just a software upgrade.

Higher image quality can have a significant impact on supporting radiologists reading the images for a more confident diagnosis. Innovations such as this not only allow for improved image quality but can also ease the training burden on technologists with standardized image protocols to drive more consistent clinical outcomes, with up to 50 percent reduced scan time, improving productivity, as well as the patient experience.

Managing staffing challenges and imaging consistency with remote capabilities

Today’s healthcare delivery environment is rapidly expanding. Patients have increasing access to many care options and demand is increasing for remote access to services, such as medical imaging. One way to successfully scale an imaging operation over multiple sites is moving to a distributed imaging model. Sophisticated tools help to manage staffing challenges and reduce variation in image acquisitions. Radiology departments with multiple service sites can work more efficiently to help manage imaging protocols, staff training, and enable collaboration. Optimizing imaging operations with remote tools can help support radiology’s need to provide consistent radiology services. Referring physicians as well as patients can rely on the same, high-quality imaging from any of a health system’s main or satellite locations when imaging services are provided with consistency.

Managing protocols remotely to share, edit and monitor across imaging devices and locations can help ensure image consistency. Additionally, it can help monitor variations in radiation dose to patients, ensure consistent performance by technologists, and monitor quality across all locations to ensure uniform care delivery.

GE Healthcare provides a robust set of imaging protocols on each new digital system, and also designed a digital tool to help eliminate the traditionally manual process of updating scanner protocols after the system is operational. The protocol management tool is an automated solution to distribute and edit imaging protocols remotely for a health system’s entire fleet of scanners to effectively maintain and keep protocols up to date. Customers can receive continued support through remote clinical training applications and protocol optimization tools.

Enabling sustainable operational efficiencies in radiology

Advanced imaging technology and efficient solutions can help improve clinical decisions and support stronger radiology department operations with sustainable benefits to healthcare providers.   Streamlining equipment usability with intuitive user interfaces, AI-based tools, and optimized workflows can help to holistically solve department efficiencies, as well as reduce stress and radiology staff burnout. Industry partners like GE Healthcare are committed to helping transform technological advancements to improve efficiency and capacity in radiology, creating a more efficient, sustainable environment that can support improved patient outcomes.

 

Disclaimers:

Not all products or features are available in all geographies. Check with your local GE Healthcare representative for availability in your country.

*AIR™ Recon DL for PROPELLER and 3D is 510(k) cleared in the USA. Not CE Marked, not available for sale in all regions

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