Point-of-care ultrasound (POCUS) is changing the way clinicians diagnose and manage patients by enabling real-time ultrasound exams directly at the bedside. Unlike traditional ultrasound, where a technician performs the exam and a specialist interprets the images without examining the patient, POCUS allows clinicians to make rapid diagnoses and perform procedures more accurately and safely, including IV placements, central venous access, and nerve blocks.
POCUS vs. Traditional Ultrasound
While both POCUS and traditional ultrasound use the same core technology, their design and function are different. Traditional machines are bulky, stationary devices, requiring patient transport or a large space, but they do offer premium-quality imaging. POCUS machines are smaller and portable, allowing clinicians to bring the device to the bedside. POCUS devices have simpler controls for quick image acquisition, making them ideal for specific, rapid assessments, but they also sacrifice on quality. As simpler machines, POCUS devices are generally more affordable.
Traditional ultrasound is comprehensive and often requires extensive training to operate, while POCUS machines are more user-friendly, allowing for faster learning and broader application in emergency, critical care, and primary care settings. This emphasis on speed and simplicity is especially valuable in environments where timely decision-making is critical, such as emergency departments (EDs) and intensive care units (ICUs), where POCUS is most commonly used.
Primary care practices — particularly those in rural areas with limited access to comprehensive imaging — are also ideal settings for POCUS, because it helps clinicians triage patients who may need advanced imaging referrals. However, POCUS is not suitable for scenarios requiring advanced sonographic techniques, such as elastography or myocardial strain imaging, as these require specialized settings and training beyond the scope of most POCUS applications.
From Cart-Based to Handheld POCUS
Cart-based POCUS machines improved portability but still posed limitations. Clinicians often needed to leave the bedside to retrieve a machine, creating delays that defeated the purpose of POCUS. Moving these devices across multiple units or floors could also be cumbersome. The early 2010s saw the introduction of handheld POCUS devices that fit in a lab coat pocket, offering a solution to these limitations. However, early models were limited to phased array transducers, suitable only for cardiac imaging.
As the technology evolved, handheld devices began to offer curvilinear and linear transducers, connecting to smartphones and tablets via apps. This expansion allowed for more diverse applications at a lower cost. However, users still needed to carry multiple transducers for comprehensive use, reducing portability and increasing costs.
Whole-Body Handheld POCUS
In 2018, chip-based transducers were introduced as a cheaper alternative to traditional piezoelectric crystals, reducing costs and enabling “whole-body POCUS.” These transducers function as phased, linear, or curvilinear probes, making it possible to perform a range of exams with a single device. This innovation greatly enhanced portability, allowing clinicians to use one handheld device for a variety of ultrasound applications. By connecting to smartphones, these devices became even more accessible, providing high-quality bedside imaging at a fraction of the cost of traditional machines.
Image Quality: Crystals vs. Chips
While piezoelectric crystal-based machines offer higher image resolution, newer chip-based devices provide sufficient quality for most POCUS applications. At this time, chip-based devices cannot perform advanced cardiac techniques, such as use of continuous wave Doppler. As technology advances, the image quality of chip-based devices continues to improve, closing the gap with traditional machines. For many clinicians, the slight reduction in image quality is outweighed by the benefits of lower cost and greater portability.
Artificial Intelligence (AI) in POCUS
AI is increasingly being integrated into POCUS, enhancing both education and interpretation. AI algorithms in handheld devices label anatomical structures, guide probe placement, and calculate key metrics, such as ejection fraction and bladder volume. This helps new users improve their skills while ensuring more consistent and accurate results.
AI also plays a role in detecting specific findings, such as B-lines in lung ultrasound and needle visualization during procedures. These features help clinicians make quicker and more reliable diagnoses, further improving patient care.
Expanded Applications and Improved Patient Care
Handheld POCUS has expanded ultrasound’s reach across clinical settings. In emergency departments, where time and space are limited, handheld devices allow for quick assessments in critical cases. Their small size makes them easy to maneuver in crowded areas, providing valuable diagnostic information without delay.
Handheld POCUS is also transforming prehospital care, allowing EMS teams to assess patients for conditions like pneumothorax, pulmonary edema, or hemoperitoneum before reaching the hospital. In global health settings, these devices enable clinicians to bring imaging to underserved areas, offering critical diagnostic support where resources are limited. Handheld devices can also be used for training local providers, making POCUS a more sustainable option for global health initiatives.
Teleguidance and Remote Education
The integration of handheld POCUS with smartphones and tablets has opened up opportunities for teleguidance, enabling real-time feedback from remote experts. This is especially beneficial in remote areas, where expertise may be limited. Additionally, many devices allow for easy sharing of de-identified images or videos, supporting quality assurance and remote training.
Handheld POCUS also supports distance learning, allowing clinicians to receive feedback and guidance without having to travel for training. This capability is particularly valuable in rural or underserved settings, where access to training can be limited.
Cost-Effectiveness and Return on Investment
Traditional ultrasound machines have been prohibitively expensive for small practices and individual providers. Handheld POCUS offers an affordable alternative, making ultrasound accessible to private practices, solo practitioners, and outpatient clinics. Handheld devices are reimbursed at the same rates as cart-based machines, allowing for a rapid return on investment. With consistent use, handheld POCUS can be profitable within weeks, turning it into an indispensable asset for any practice.
Overcoming Integration Challenges
Early challenges with integrating handheld POCUS into clinical workflows — such as image archiving, EMR reporting, and billing — have largely been resolved. Most devices now offer seamless integration with hospital systems or in-app archival systems, allowing clinicians to save images, generate reports, and submit billing information directly from their phones. This integration makes handheld POCUS not only a diagnostic tool but also an efficient part of the clinical workflow.
Handheld ultrasound has reshaped the landscape of bedside diagnostics, offering unmatched portability, cost-effectiveness, and versatility. As AI-driven advancements continue to improve image quality and diagnostic accuracy, handheld POCUS is set to become an indispensable tool across all healthcare settings. From emergency departments to global health missions, handheld ultrasound enhances patient care and expands access to essential diagnostic tools. For clinicians considering handheld POCUS, the benefits are clear: improved outcomes, cost savings, and better access to imaging across diverse settings.
Joshua Guttman, MD, is an associate professor in the Department of Emergency Medicine at Emory University School of Medicine in Atlanta.
Disclosures
Guttman is the founder and CEO of Peachtree POCUS, a POCUS consulting company.
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Source link : https://www.medpagetoday.com/opinion/second-opinions/112804
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Publish date : 2024-11-10 17:00:00
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