Technology Solutions Can Help Achieve Accurate Ultrasound Reports

Technology solutions, supported by artificial intelligence and digital integration, allows ultrasound teams to do their best collaborative work with the best technology available.

Clear, accurate and consistent ultrasound reports play an important role in patient care and can reduce the burden on radiology teams. Too often, however, reports are unclear, inaccurate and/or inconsistent. Consider this: More than one in five radiology reports includes at least one error.1 Some may be minor. Others may cost lives and money.

Why are these errors so common? You might be surprised. In 2023, despite all the advances in imaging and communications technology, some radiologists are still dictating measurements from a handwritten sonographer worksheet scanned into electronic picture archiving and communication systems (PACS). That process leaves a frightening amount of room for error, especially given that radiologists face an overwhelming workload, interpreting hundreds of images daily.

It's also worth noting that speech-recognition software can introduce errors, including measurements, laterality errors, and even incorrect dates. Potentially confusing statements occur in more than 20% of routine radiology reports dictated with speech-recognition software.2 Common errors involve the substitution of a wrong word, such as "normally" substituted for "minimally," "lateral" for "bilateral," "ill-defined" for "well-defined", and "renal" for "adrenal."3

Even when errors are relatively minor, they can cause confusion for referring providers and patients. Members of the radiology team end up spending even more time fielding calls from referring providers to get clarification and then having to add an addendum. All this additional stress contributes to frustration, fatigue, and possibly more errors.

There's really no reason for radiology departments to use mid-20th century tools. The right technology—properly deployed—can help organizations avoid errors and create accurate, actionable ultrasound reports. Accuracy, however, is merely the baseline.

Beyond Accuracy: Best Practices in Ultrasound Reports

An ultrasound report must be clear and accurate. Beyond that, experts may quibble, because as there's no one perfect way to craft a radiology report. However, a solid report must include certain elements. Among the most important are the following:

  • Concise, logical structure: A structured reporting format may reduce diagnostic errors: It provides a checklist of sorts, ensuring that the radiologists include relevant information. It also makes it easier for the referring physician to understand without having to dig through the report for key information.4 How the term "structured" is defined is a matter of debate in the profession, but it generally refers to the use of a standard design and common terminology. There's been an effort across the industry to standardize report structures. For example, the Radiological Society of North America has created a free repository of report templates for an array of common procedures across specialties. They have been reviewed by an international panel of radiologists.

  • Accessible to the intended audience: Radiologists write the reports primarily for busy referring physicians, so the reports should be easy to understand and avoid overly technical terms that have more meaning to radiologists than other clinicians. Clarity has become even more important now that patients are increasingly reading these reports.5

  • Consistency: This has less to do with any single report than all the reports across a healthcare setting or network. Aligning radiology teams around a common workflow increases efficiency and decreases frustration. In contrast, a lack of consistency across the healthcare setting leads to reporting variability and inconsistent adherence to standards. For efficiency, patient safety, user experience, and regulatory compliance, everyone in the department should be adhering to the same protocols and standards, and using the same terms and formats in the report.

The right technology can make this happen.

Turning to Technology

With automated data transfer, measurements are sent directly from the ultrasound system into the digital sonographer worksheet, eliminating the need for dictation into the PACS system. This reduces manual data entry, which increases sonographer efficiency and accuracy and eliminates the confusion associated with speech-recognition software. Moreover, with the right technology, radiologists anywhere can quickly connect with sonographers if they need additional information to make an accurate diagnosis.

Technology also improves the images themselves. Accurate image interpretation requires the best images possible. Integrating artificial intelligence and other digital tools into ultrasound technology can help support this.6 For instance, some solutions enable radiologists to segment lesions and identify vessels more easily, leading to more accurate diagnoses.

The right technology solutions can improve overall digital accuracy and reduce variation in ultrasound reporting by driving standardization, including in protocols and reporting templates.

Technology solutions, supported by AI and digital integration, allows radiology teams to do their best collaborative work, confident they are using the best technology available. This supports report accuracy, drives clinical and operational efficiency, and aims to enhance patient outcomes and the patient/clinician experience while controlling costs.



1.  Frequency and Spectrum of Errors in Final Radiology Reports Generated With Automatic Speech Recognition Technology; Quint, Leslie E. et al.; Journal of the American College of Radiology, Volume 5, Issue 12, 1196 – 1199.

2. Femi-Abodunde A, Olinger K, Burke LMB, et al. Radiology dictation errors with covid-19 protective equipment: does wearing a surgical mask increase the dictation error rate? Journal of Digital Imaging. 2021; 34(5):1294-1301. DOI: 10.1007/s10278-021-00502-w

3. Quint LE, Quint DJ, Myles JD. Frequency and spectrum of errors in final radiology reports generated with automatic speech recognition technology. J Am Coll Radiol. 2008 Dec;5(12):1196-9. doi: 10.1016/j.jacr.2008.07.005

4. Makary M and Xie J. Reinventing radiology reports in the age of value-based care. Diagnostic Imaging. October 2022;

5. Mehan WA, Brink JA, and Hirsch JA. 21st Century Cures Act: Patient-facing implications of information blocking. Journal of the American College of Radiology. July 2021; 18(7):1012-1016. DOI: 10.1016/j.jacr.2021.01.016

6. Hosny A, Parmar C, Quackenbush J, Schwartz LH, et al. Artificial intelligence in radiology. Nature Reviews Cancer. 2018; 18(8):500-510. DOI:10.1038/s41568-018-0016-5