Ultrasound is more essential than ever in patient care, with its use expanding across a wide range of clinical settings. But with growth comes new challenges. Managing devices, optimizing workflows, and keeping up with rising demand. To stay ahead, organizations need innovative digital solutions that enhance efficiency and scale with their needs.
Artificial intelligence (AI) is a key enabler of efficiency, but it is not the only solution. Meaningful improvements require a broader digital strategy that integrates AI with advanced reporting, remote device management, and clinical collaboration. By adopting a comprehensive approach, hospitals and health systems can maximize resources, reduce bottlenecks, and ensure ultrasound remains a high-performing diagnostic tool.
The power of ultrasound + AI
“AI is one of the key tools that can help with workflow efficiency and reducing clinician burnout,” explains Mustafa Hassan, PhD, Senior Analyst at Signify Research Limited. “It’s about improving how ultrasound imaging is standardized and utilized, which is a problem within ultrasound systems.”
AI is addressing these problems by making exams faster, more consistent, and accessible to a wider range of users. Real-time scan guidance helps operators capture organs, blood vessels, and abnormalities while providing feedback on probe positioning, imaging techniques, and necessary additional views. Visual cues highlight anatomical landmarks and guide procedures.
According to Hassan, “Ultrasound guidance solutions can help new or inexperienced users obtain high-quality images quickly. These tools reduce dependence on a small number of experts and alleviate workload pressures.”
Beyond image acquisition, AI supports clinical efficiency by automating anatomical measurements. It enhances cardiac imaging with more precise left ventricular ejection fraction estimation in cardiology1 and automatically detects and classifies endometrial thickness and ovarian cysts in OBGYN2. AI-enabled ultrasound systems can also automate organ labeling in abdominal exams, reducing manual steps. In breast ultrasound screening, AI integration has been shown to cut radiologists’ reading time by 38% without compromising diagnostic accuracy3.
AI is one part of an efficient, innovative ultrasound ecosystem
While AI is a powerful tool, achieving maximum efficiency in ultrasound requires integrating complementary digital solutions. These technologies address workflow challenges that AI alone cannot resolve, ensuring ultrasound systems function effectively across departments and care settings.
Documenting all ultrasound exams reliably and efficiently
The rapid adoption of POCUS offers clinical benefits but also creates data integration challenges. Without proper integration, hospitals risk accumulating “unsolicited images,” or scans that are disconnected from patient records and billing workflows. These gaps can lead to inefficiencies, hinder collaboration, and result in lost revenue.
“As ultrasound usage picks up in the coming years, this will be a bigger concern,” notes Hassan.
Structured bedside ultrasound reporting helps ensure POCUS exams are accurately documented and properly archived. Configurable templates tailored to different clinical settings improve workflow efficiency and data accuracy. By embedding structured documentation into the imaging process, healthcare organizations can strengthen care coordination, maintain compliance, and optimize reimbursement.
Managing large fleets of ultrasound devices
Growth in ultrasound adoption across health systems means IT, biomedical engineering, and health technology management teams are navigating growing complexities related to software updates, compliance, maintenance, risk mitigation, and utilization. Without a structured approach, these tasks can become overwhelming.
Remote fleet management solutions provide centralized oversight, enabling teams to update software, monitor device performance, and ensure security compliance without on-site intervention. These systems also offer valuable utilization insights, allowing organizations to make data-driven decisions about asset deployment. By analyzing usage patterns, IT teams can optimize device availability and improve efficiency across departments.
Simplifying ultrasound reporting
Inconsistent data entry, variable terminology, and incomplete sonographer reports can disrupt workflows, delay diagnoses, and increase the administrative burden on radiologists. Without standardized reporting, inconsistencies in documentation can lead to inefficiencies, miscommunication, and errors in patient records.
Advanced ultrasound reporting solutions simplify documentation by enforcing structured data entry and automating portions of the reporting process. Standardized templates ensure that sonographers provide complete and consistent information, improving report quality for radiologists. Additionally, automated mapping of sonographer worksheets into predefined report templates minimizes dictation and manual entry, allowing radiologists to focus on interpretation rather than administrative tasks.
By reducing documentation time, these solutions improve workflow efficiency and accelerate report turnaround times. Investing in structured and automated reporting tools is a strategic way to optimize resource utilization, enhance data accuracy, and ensure ultrasound findings are fully integrated into electronic medical records (EMRs).
Enabling new ultrasound care models
As workforce shortages persist, ultrasound collaboration tools are helping healthcare organizations extend expertise across locations. Tele-ultrasound capabilities enable a single expert to train multiple clinicians in real time, expanding access to specialized knowledge without requiring a dedicated specialist at every site.
This shift from one-to-one to one-to-many collaboration optimizes clinical resources while maintaining high-quality imaging. By adopting technologies that support real-time image sharing, remote system training, and cross-site collaboration, IT leaders can play a role in shaping the effective distribution of their organization’s ultrasound expertise.
A holistic approach to efficiency in ultrasound
AI is reshaping ultrasound, but true efficiency requires a comprehensive set of digital solutions. Hospitals and health systems that adopt a range of integrated digital technologies can optimize workflows, reduce clinician workload, and enhance diagnostic capabilities across their organizations.
To learn more about how Verisound digital ultrasound solutions can help your organization maximize ultrasound efficiency, visit GE HealthCare at HIMSS.
About Signify Research
Signify Research provides independent healthtech market intelligence powered by data. Their coverage areas are Medical Imaging, Clinical Care, Digital Health, Diagnostic and Lifesciences, Healthcare IT and AI in Healthcare. Their market analysis reports and subscriptions provide data-driven insights which business leaders use to guide strategic decisions.
REFERENCES
- Matthias Schneider et al., “A machine learning algorithm supports ultrasound-naïve novices in the acquisition of diagnostic echocardiography loops and provides accurate estimation of LVEF,” The International Journal of Cardiovascular Imaging 37, no. 2 (2021): 577-586.
- L. Drukker et al., “Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology,” Ultrasound in Obstetrics & Gynecology 56, no. 4 (2020): 498-505.
- Yulei Jiang et al., “Interpretation time using a concurrent-read computer-aided detection system for automated breast ultrasound in breast cancer screening of women with dense breast tissue,” American Journal of Roentgenology 211, no. 2 (2018): 452-461.
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